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CCI Publications by year

 

2020  |  2019  |  2018  |  2017  |  2016  |  2015  |  2014  |  2013  |  2012

2020

Baird, M; Chai, F; Ciavatta, S; Dutkiewicz, S; Edwards, C; Evers-King, H; Friedrichs, M; Frolov, S; Gehlen, Ma; Henson, S; Hickman, A; Jahn, O; Jones, E; Kaufman, D; Mélin, F; Mouw, C; Muhling, B; Rousseaux, C; Shulman, I; Wiggert, J. Synergy between Ocean Colour and Biogeochemical/Ecosystem Models. IOCCG Report Number 19 (2020)

Bergstedt H., A. Bartsch, A. Neureiter, A. Höfler, B. Widhalm, N. Pepin, and J, Hjort, Deriving a Frozen Area Fraction From Metop ASCAT Backscatter Based on Sentinel-1, IEEE Transactions on Geoscience and Remote Sensing, https://doi.org/10.1109/TGRS.2020.2967364 (Early Access)

Coldewey-Egbers, M., Loyola, D. G., Labow, G., and Frith, S. M.: Comparison of GTO-ECV and adjusted MERRA-2 total ozone columns from the last 2 decades and assessment of interannual variability, Atmos. Meas. Tech., 13, 1633–1654, https://doi.org/10.5194/amt-13-1633-2020, 2020

Gliß, J., Mortier, A., Schulz, M., Andrews, E., Balkanski, Y., Bauer, S. E., Benedictow, A. M. K., Bian, H., Checa-Garcia, R., Chin, M., Ginoux, P., Griesfeller, J. J., Heckel, A., Kipling, Z., Kirkevåg, A., Kokkola, H., Laj, P., Le Sager, P., Lund, M. T., Lund Myhre, C., Matsui, H., Myhre, G., Neubauer, D., van Noije, T., North, P., Olivié, D. J. L., Sogacheva, L., Takemura, T., Tsigaridis, K., and Tsyro, S. G.: Multi-model evaluation of aerosol optical properties in the AeroCom phase III Control experiment, using ground and space based columnar observations from AERONET, MODIS, AATSR and a merged satellite product as well as surface in-situ observations from GAW sites, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1214, in review, 2020

He, Z., Lei, L., Zhang, Y., Sheng, M., Wu, C., Li, L., Zeng, Z.-C., Welp, L.R., Spatio-Temporal Mapping of Multi-Satellite Observed Column Atmospheric CO2 Using Precision-Weighted Kriging Method, Remote Sens., 12, 576, 2020

Kulk, Gemma & Platt, Trevor & Dingle, James & Jackson, Thomas & Jönsson, Bror & Bouman, Heather & Babin, Marcel & Brewin, Bob & Doblin, Martina & Estrada, Marta & Figueiras, F.G. & Furuya, Ken & González-Benítez, Natalia & Gudfinnsson, Hafsteinn & Gudmundsson, Kristinn & Huang, Bangqin & Isada, Tomonori & Kovač, Žarko & Lutz, Vivian & Sathyendranath, Shubha. (2020). Primary Production, an Index of Climate Change in the Ocean: Satellite-Based Estimates over Two Decades. Remote Sensing. 12. 826. 10.3390/rs12050826

Loyola, D. G., Xu, J., Heue, K.-P., and Zimmer, W.: Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements, Atmos. Meas. Tech., 13, 985–999, https://doi.org/10.5194/amt-13-985-2020, 2020

Mahecha, M. D., Gans, F., Brandt, G., Christiansen, R., Cornell, S. E., Fomferra, N., Kraemer, G., Peters, J., Bodesheim, P., Camps-Valls, G., Donges, J. F., Dorigo, W., Estupiñan-Suarez, L., Gutierrez-Velez, V. H., Gutwin, M., Jung, M., Londoño, M. C., Miralles, D. G., Papastefanou, P., and Reichstein, M. (2020) Earth system data cubes unravel global multivariate dynamics, Earth Syst. Dynam., 11, 201–234, 2020. https://doi.org/10.5194/esd-11-201-2020

Mei, L., Vandenbussche, S., Rozanov, V., Proestakis, E., Amiridis, V., Callewaert, S., Vountas, M. and Burrows, J.P., 2020. On the retrieval of aerosol optical depth over cryosphere using passive remote sensing. Remote Sensing of Environment, 241, p.111731

Moesinger, L., Dorigo, W., Jeu, R. de, Schalie, R. van der, Scanlon, T., Teubner, I., Forkel, M. (2020) The Global Long-term Microwave Vegetation Optical Depth Climate Archive (VODCA). Earth System Science Data 12, 177–196.https://doi.org/10.5194/essd-12-177-2020

Paul, F. (2020): A 60-year chronology of glacier surges in the central Karakoram from the analysis of satellite image time-series. Geomorphology, 352, 106993

Pitarch, J.; Bellacicco, M.; Organelli, E.; Volpe, G.; Colella, S.; Vellucci, V.; Marullo, S. Retrieval of Particulate Backscattering Using Field and Satellite Radiometry: Assessment of the QAA Algorithm. Remote Sens. 2020, 12, 77

Popp Thomas, Michaela I. Hegglin, Rainer Hollmann, Fabrice Ardhuin, Annett Bartsch, Ana Bastos, Victoria Bennett, Jacqueline Boutin, Michael Buchwitz, Emilio Chuvieco, Philippe Ciais, Wouter Dorigo, Darren Ghent, Richard Jones, Thomas Lavergne, Christopher Merchant, Benoit Meyssignac, Frank Paul, Shaun Quegan, Tracy Scanlon, Marc Schröder, Stefan Simis, Ulrika Willén, Consistency of satellite climate data records for Earth system monitoring, Bulletin of the American Meteorological Society, in review, 2020

Reul, N., Grodsky, S. A., Arias, M., Boutin, J., Catany, R., Chapron, B., D’Amico, F., Dinnat, E., Donlon, C., Fore, A., Fournier, S., Guimbard, S., Hasson, A., Kolodziejczyk, N., Lagerloef, G., Lee,  T., Le Vine, D. M., Lindstrom, E., Maes, C., Mecklenburg, S., Meissner, T., Olmedo, E., Sabia, R., Tenerelli, J., Thouvenin-Masson, C., Turiel,  A., Vergely,  J.L., Vinogradova, N., Wentz, F., and Yue, S. (2020), Title: Sea Surface Salinity estimates from Spaceborne L-band radiometers: an overview of the first decade of observation (2010-2019), Remote Sensing of Environment

Reuter, M., Buchwitz, M., Schneising, O., Noel, S., Bovensmann, H., Burrows, J. P., Boesch, H., Di Noia, A., Anand, J., Parker, R. J., Somkuti, P., Wu, L., Hasekamp, O. P., Aben, I., Kuze, A., Suto, H., Shiomi, K., Yoshida, Y., Morino, I., Crisp, D., O'Dell, C. W., Notholt, J., Petri, C., Warneke, T., Velazco, V. A., Deutscher, N. M., Griffith, D. W. T., Kivi, R., Pollard, D. F., Hase, F., Sussmann, R., Te, Y. V., Strong, K., Roche, S., Sha, M. K., De Maziere, M., Feist, D. G., Iraci, L. T., Roehl, C. M., Retscher, C., and Schepers, D.: Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003-2018) for carbon and climate applications, Atmos. Meas. Tech., 13, 789-819, https://doi.org/10.5194/amt-13-789-2020, 2020

Sayer, A. M., Govaerts, Y., Kolmonen, P., Lipponen, A., Luffarelli, M., Mielonen, T., Patadia, F., Popp, T., Povey, A. C., Stebel, K., and Witek, M. L.: A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing, Atmospheric Measurements and Techniques, 13, 373–404, https://doi.org/10.5194/amt-13-373-2020, 2020

Schlembach, F.; Passaro, M.; Quartly, G.D.; Kurekin, A.; Nencioli, F.; Dodet, G.; Piollé, J.-F.; Ardhuin, F.; Bidlot, J.; Schwatke, C.; Seitz, F.; Cipollini, P.; Donlon, C. Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height. Remote Sens. 2020, 12, 1254.   https://doi.org/10.3390/rs12081254, 2020

Schutgens, N., Sayer, A. M., Heckel, A., Hsu, C., Jethva, H., de Leeuw, G., Leonard, P. J. T., Levy, R. C., Lipponen, A., Lyapustin, A., North, P., Popp, T., Poulson, C., Sawyer, V., Sogacheva, L., Thomas, G., Torres, O., Wang, Y., Kinne, S., Schulz, M., and Stier, P.: An AeroCom/AeroSat study: Intercomparison of Satellite AOD Datasets for Aerosol Model Evaluation, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1193, in review, 2020

Shepherd, A., Ivins, E., Rignot, E. et al. Mass balance of the Greenland Ice Sheet from 1992 to 2018. Nature 579, 233–239 (2020). https://doi.org/10.1038/s41586-019-1855-2

Shubha, Trevor Platt, Zarko Kovac, James Dingle, Thomas Jackson, Robert Brewin, Peter Franks, Emilio Maranon, Gemma Kulk, and Heather Bouman (In press) Reconciling models of primary production and photoacclimation. Applied Optics. 10.1364/AO.386252

Sogacheva Larisa, Thomas Popp, Andrew M. Sayer, Oleg Dubovik, Michael J. Garay, Andreas Heckel, N. Christina Hsu, Hiren Jethva, Ralph A. Kahn, Pekka Kolmonen, Miriam Kosmale, Gerrit de Leeuw, Robert C. Levy, Pavel Litvinov, Alexei Lyapustin, Peter North, Omar Torres and Antti Arola, Merging regional and global aerosol optical depth records from major available satellite products, Atmospheric Chemistry and Physics, 20, 2031 – 2056, https://doi.org/10.5194/acp-20-2031-2020, 2020

Strozzi T., R. Caduff, N. Jones, C. Barboux, R. Delaloye, X. Bodin, A. Kääb, E. Mätzler and L. Schrott, Monitoring Rock Glacier Kinematics with Synthetic Aperture Radar, Remote Sensing, 12(3), 559, 2020, https://www.mdpi.com/2072-4292/12/3/559.

Tanase, M.A., Belengher-Plomer, M.A., Roteta, E., Bastarrika, A., Wheeler, J. Fernández-Carrillo, A., Tansey, K., Wiedermann, W., Navratil, P., Lohberger, S., Siegert, F., Chuvierco, E. (2020) Burned Area Detection and Mapping: Intercomparison of Sentinel-1 and Sentinel-2 Based Algorithms over Tropical Africa. Remote Sensing 12 (2), 334, https://doi.org/10.3390/rs12020334

Wu, Y., C.R. Duguay and L. Xu (2020). Lake ice classification from MODIS TOA reflectance imagery using a convolutional neural network: a case study of Great Slave Lake, Canada. Proceedings of 2020 IEEE International Geoscience & Remote Sensing Symposium, Waikoloa, Hawaii, USA, 19-24 July, 4 pp

Zemp, M., Huss, M., Eckert, N., Thibert, E., Paul, F., Nussbaumer, S.U. and Gärtner-Roer, I. (2020): Brief communication: Ad hoc estimation of glacier contributions to sea-level rise from latest glaciological observations. The Cryosphere, 14, 1043–1050.

Zhang, G., Xiao, X., Dong, J., Xin, F., Zhang, Y., Qin, Y., Doughty, R. B., Moore III, B., Fingerprint of rice paddies in spatial–temporal dynamics of atmospheric methane concentration in monsoon Asia, Nat. Commun. 11, 554, 2020.

Xaver, A., Zappa, L.,Rab, G., Pfeil, I.,Vreugdenhil, M., Hemmet, D.,Dorigo, W. (2020). Evaluating the suitability of the consumer low-cost Parrot Flower Power soil moisture sensor for scientific environmental applications. Geosci. Instrum. Method. and Data Syst. https://doi.org/10.5194/gi-2019-38 

2019

Altena, B., Scambos, T., Fahnestock, M., and Kääb, A. (2019): Extracting recent short-term glacier velocity evolution over southern Alaska and the Yukon from a large collection of Landsat data. The Cryosphere, 13, 795-814.  https://doi.org/10.5194/tc-13-795-2019

Ardhuin, Fabrice & Stopa, Justin & Chapron, Bertrand & Collard, Fabrice & Jensen, Robert & Johannessen, Johnny & Husson, Romain & Mouche, Alexis & Passaro, Marcello & Quartly, Graham & Swail, Val & Young, Ian. (2018). Observing sea states. Frontiers in Marine Science 2019 vol: 6 pp: 124. doi: 10.3389/fmars.2019.00124.

Belenguer-Plomer, M. A., Chuvieco, E. and Tanase, M. A. (2019) ‘Temporal Decorrelation of C-Band Backscatter Coefficient in Mediterranean Burned Areas’, Remote Sensing. Multidisciplinary Digital Publishing Institute, 11(22), p. 2661. doi: 10.3390/rs11222661.

Brennan, J. et al. (2019) ‘Theoretical uncertainties for global satellite-derived burned area estimates’, Biogeosciences, 16(16), pp. 3147–3164. doi: 10.5194/bg-16-3147-2019.

Berzaghi, F., Longo, M., Ciais, P., Blake, S., Bretagnolle, F., Vieira, S., Scaranello, M., Scarascia-Mugnozza, G. and Doughty, C. E. (2019) Carbon stocks in central African forests enhanced by elephant disturbance. Nat. Geosci. 12, 725–729 (2019). https://doi.org/10.1038/s41561-019-0395-6

Ceamanos, X. et al. (2019) ‘Assessing the Potential of Geostationary Satellites for Aerosol Remote Sensing Based on Critical Surface Albedo’, Remote Sensing, 11(24), p. 2958. doi: 10.3390/rs11242958.

Chave, J., Davies, S. J., Phillips, O. L., Lewis, S. L., Sist, P., Schepaschenko, D., ... & Duncanson, L. (2019). Ground data are essential for biomass remote sensing missions. Surveys in Geophysics, 40 (4): 863-880. DOI:10.1007/s10712-019-09528-w.

Chevallier, F. et al. (2019) ‘Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions’, Atmospheric Chemistry and Physics, 19(22), pp. 14233–14251. doi: 10.5194/acp-19-14233-2019.

Chuvieco Emilio, Florent Mouillot, Guido R. van der Werf, Jesús San Miguel, Mihai Tanase, Nikos Koutsias, Mariano García, Marta Yebra, Marc Padilla, Ioannis Gitas, Angelika Heil, Todd J. Hawbaker, Louis Giglio (2019) Historical background and current developments for mapping burned area from satellite Earth observation, Remote Sensing of Environment 225, 45-64, https://doi.org/10.1016/j.rse.2019.02.013.

De Rydt, J., Gudmundsson, G. H., Nagler, T., and Wuite, J.: Calving cycle of the Brunt Ice Shelf, Antarctica, driven by changes in ice-shelf geometry, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-46, in review, 2019.

Deschamps-Berger, C., C. Nuth, W. Van Pelt, E. Berthier, J. Kohler & B. Altena (2019): Closing the mass budget of a tidewater glacier, an example of Kronebreen, Svalbard. JGlaciol., 65(249) 136-148. DOI: https://doi.org/10.1017/jog.2018.98

Dodet, G., Melet, A., Ardhuin, F., Bertin, X., Idier, D., Almar, R., 2019. The Contribution of Wind-Generated Waves to Coastal Sea-Level Changes. Surv Geophys. https://doi.org/10.1007/s10712-019-09557-5

Duncanson, L., Armston, J., Disney, M., Avitabile, V., Barbier, N., Calders, K., Carter, S., Chave, J., Herold, M., Crowther, T. W., Falkowski, M., Kellner, J. R., Labrière, N., Lucas, R., MacBean, N., McRoberts, R. E., Meyer, V., Næsset, E., Nickeson, J. E., Paul, K. I., Phillips, O. L., Réjou-Méchain, M., Román, M., Roxburgh, S., Saatchi, S., Schepaschenko, D., Scipal, K., Siqueira, P. R., Whitehurst, A. & Williams, M. (2019). The Importance of Consistent Global Forest Aboveground Biomass Product Validation. Surveys in Geophysics 40 (4): 979-999. DOI:10.1007/s10712-019-09538-8

Eliasson, S., Karlsson, K. G., van Meijgaard, E., Meirink, J. F., Stengel, M., and Willén, U. (2019) The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model, Geosci. Model Dev., 12, 829-847, https://doi.org/10.5194/gmd-12-829-2019, 2019

Eyring, V. et al. (2019) Taking climate model evaluation to the next level. Nature Climate Change, Vol 9, 102, 102–110. https://doi.org/10.1038/s41558-018-0355-y

Falaschi, D., Kääb, A., Paul, F., Tadono, T., Rivera, J.A. and Lenzano, L.E. (2019): Brief communication: Collapse of 4 Mm3of ice from a cirque glacier in the Central Andes of Argentina. The Cryosphere, 13, 997-1004. https://doi.org/10.5194/tc-13-997-2019

Fischer, F.J., Marechaux, I., Chave, J. (2019). Improving plant allometry by fusing forest models and remote sensing. https://doi.org/10.1111/nph.15810.

Forkel, M., Andela, N., Harrison, S. P., Lasslop, G., van Marle, M., Chuvieco, E., Dorigo, W., Forrest, M., Hantson, S., Heil, A., Li, F., Melton, J., Sitch, S., Yue, C., and Arneth, A. (2019) Emergent relationships on burned area in global satellite observations and fire-enabled vegetation models. Biogeosciences 16, 57-76, https://doi.org/10.5194/bg-16-57-2019. 

Galytska, E., Rozanov, A., Chipperfield, M. P., Dhomse, Sandip. S., Weber, M., Arosio, C., Feng, W., and Burrows, J. P.: Dynamically controlled ozone decline in the tropical mid-stratosphere observed by SCIAMACHY, Atmos. Chem. Phys., 19, 767-783, https://doi.org/10.5194/acp-19-767-2019, 2019.

Gerland, S., D. Barber, W. N. Meier, C. J. Mundy, M. Holland, S. Kern, Z. Li, C. Michel, D. Perovich, and T. Tamura: Essential gaps and uncertainties in the understanding of the roles and functions of Arctic sea ice, Environmental Research Letters, 14(4), https://iopscience.iop.org/article/10.1088/1748-9326/ab09b3, 2019.

Groh, A. et al. (2019) ‘Evaluating GRACE Mass Change Time Series for the Antarctic and Greenland Ice Sheet—Methods and Results’, Geosciences. Multidisciplinary Digital Publishing Institute, 9(10), p. 415. doi: 10.3390/geosciences9100415.

Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture Climate Data Records and their underlying merging methodology. Earth Syst. Sci. Data Discusshttps://doi.org/10.5194/essd-2019-21.

Herold, M., Carter, S., Avitabile, V. et al. (2019) The Role and Need for Space-Based Forest Biomass-Related Measurements in Environmental Management and Policy. Surveys in Geophysics 40: 757. https://doi.org/10.1007/s10712-019-09510-6.

Inness, A., Flemming, J., Heue, K.-P., Lerot, C., Loyola, D., Ribas, R., Valks, P., van Roozendael, M., Xu, J., and Zimmer, W.: Monitoring and assimilation tests with TROPOMI data in the CAMS system: near-real-time total column ozone, Atmos. Chem. Phys., 19, 3939-3962, https://doi.org/10.5194/acp-19-3939-2019, 2019.

Isbekov, K. B. et al (2019) Impacts of water changes in the fauna, flora and physical properties over the Balkhash Lake watershed. Lakes & Reservoirs  https://doi.org/10.1111/lre.12263.

Kern, S. et al. (2019) ‘Satellite passive microwave sea-ice concentration data set intercomparison: closed ice and ship-based observations’, The Cryosphere, 13(12), pp. 3261–3307. doi: 10.5194/tc-13-3261-2019.

Kochtitzky, W., Jiskoot, H., Copland, L., Enderlin, E., McNabb, R., Kreutz, K., & Main, B.(n.d.). Ter-minus advance, kinematics and mass redistribution during eight surges of Donjek Glacier, St. Elias Range, Canada, 1935 to 2016. Journal of Glaciology, 1-15. doi:10.1017/jog.2019.34

Lavergne Thomas, Atle Macdonald Sørensen, Stefan Kern, Rasmus Tonboe, Dirk Notz, Signe Aaboe, Louisa Bell, Gorm Dybkjær, Steinar Eastwood, Carolina Gabarro, Georg Heygster, Mari Anne Killie, Matilde Brandt Kreiner, John Lavelle, Roberto Saldo, Stein Sandven, and Leif Toudal Pedersen: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49-78, 2019 https://doi.org/10.5194/tc-13-49-2019.

Lizundia-Loiola, J. et al. (2020) ‘A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data’, Remote Sensing of Environment. Elsevier, 236, p. 111493. doi: 10.1016/J.RSE.2019.111493.

Lizundia-Loiola, J., Pettinari, M. L. and Chuvieco, E. (2020) ‘Temporal Anomalies in Burned Area Trends: Satellite Estimations of the Amazonian 2019 Fire Crisis’, Remote Sensing. Multidisciplinary Digital Publishing Institute, 12(1), p. 151. doi: 10.3390/rs12010151.

Lunt, M. F. et al. (2019) ‘An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data’, Atmospheric Chemistry and Physics, 19(23), pp. 14721–14740. doi: 10.5194/acp-19-14721-2019.

Maasakkers, J. D., Jacob, D. J., Sulprizio, M. P., et al.: Global distribution of methane emissions, emission trends, and OH concentrations and trends inferred from an inversion of GOSAT satellite data for 2010–2015, Atmos. Chem. Phys., 19, 7859–7881, https://doi.org/10.5194/acp-19-7859-2019, 2019.

Marti F., Cazenave A., Birol F., Passaro, M. Leger F., Nino F., Almar R., Benveniste J. and Legeais J.F., Altimetry-based sea level trends along the coasts of western Africa, Advances in Space Research, published online 24 May2019, https://doi.org/10.1016/j.asr.2019.05.033, 2019.

Merchant, C. J. et al. (2019) ‘Satellite-based time-series of sea-surface temperature since 1981 for climate applications’, Scientific Data. Nature Publishing Group, 6(1), p. 223. doi: 10.1038/s41597-019-0236-x.

Miller, S. M., A. M. Michalak, R. G. Detmers, O. P. Hasekamp, L. M. P Bruhwiler, S. Schwietzke, China’s cola mine methane regularions have not curbed growing emissions, Nature Communications, https://www.nature.com/articles/s41467-018-07891-7, Vol. 10, Article 303, 2019.

Mottram, R; B Simonsen, S.; Høyer Svendsen, S.; Barletta, V.R.; Sandberg Sørensen, L.; Nagler, T.; Wuite, J.; Groh, A.; Horwath, M.; Rosier, J.; Solgaard, A.; Hvidberg, C.S.; Forsberg, R.:  An Integrated View of Greenland Ice Sheet Mass Changes Based on Models and Satellite Observations. Remote Sensing 11 (12), 1407; https://doi.org/10.3390/rs11121407

Nuth, C., A. Gilbert, A. Köhler, R. McNabb, T. Schellenberger, H. Sevestre, C. Weidle, L. Girod, A. Luckman & A. Kääb (2019): Dynamic vulnerability revealed in the collapse of an Arctic tidewater glacier. Scientific Reports, 9, 5541 (doi: 10.1038/s41598-019-41117-0).

Obu, J. S. Westermann, A. Bartsch, N. Berdnikov, H.H. Christiansen, A. Dashtseren, R. Delaloye, B. Elberling, B. Etzelmüller, A. Kholodov, A. Khomutov, A. Kääb, M.O. Leibman, A.G. Lewkowicz, S.K. Panda, V. Romanovsky, R.G. Way, A. Westergaard-Nielsen, T. Wu, J. Yamkhin, D. Zou (2019). Northern Hemisphere permafrost map based on TTOP modelling for 2000-2016 at 1 km2 scaleEarth-Science Reviews, Volume 193, Pages 299-316. https://doi.org/10.1016/j.earscirev.2019.04.023

Otosaka, I., Shepherd, A. and McMillan, M. (2019) ‘Ice Sheet Elevation Change in West Antarctica From Ka‐Band Satellite Radar Altimetry’, Geophysical Research Letters. John Wiley & Sons, Ltd, 46(22), pp. 13135–13143. doi: 10.1029/2019GL084271.

Palmer, P. I. et al. (2019) ‘Net carbon emissions from African biosphere dominate pan-tropical atmospheric CO2 signal’, Nature Communications. Nature Publishing Group, 10(1), p. 3344. doi: 10.1038/s41467-019-11097-w.

Paul, F. (2019): Repeat glacier collapses and surges in the Amnye Machen mountain range, Tibet, possibly triggered by a developing rock-slope instability. Remote Sensing, 11(6), 708; doi: 10.3390/rs11060708.

Phillips, O.L., Sullivan, M.J.P., Baker, T.R., Monteagudo Mendoza, A., Nunez Vargas, P., Vasquez, R. (2019). Species Matter: Wood density Influences Tropical Forest Biomass at Multiple Scales. Surveys in Geophysics 40: 913. https://doi.org/10.1007/s10712-019-09540-0

Quartly, G.D., Rinne, E., Passaro, M., Andersen, O.B., Dinardo, S., Fleury, S., Guillot,A., Hendricks, S., Kurekin, A.A.; Müller, F.L., Ricker, R., Skourup, H., Tsamados, M. Retrieving Sea Level and Freeboard in the Arctic: A Review of Current Radar Altimetry Methodologies and Future Perspectives. Remote Sens. 2019, 11, 881. https://doi.org/10.3390/rs11070881

Quegan, S., Le Toan, T., Chave, J., Dall, J., Exbrayat, J. F., Minh, D. H. T., ... & Rocca, F. (2019). The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space. Remote Sensing of Environment, 227, 44-60. https://doi.org/10.1016/j.rse.2019.03.032

Rastner, P., C. Notarnicola, L. Nicholson, R. Prinz, R. Sailer, G. Schwaizer & Paul, F. (2019): Automated mapping of snow cover on glaciers and calculation of snow line altitudes from multi-temporal Landsat data. Remote Sens. 2019, 11(12), 1410; https://doi.org/10.3390/rs11121410

REINTHALER, J., PAUL, F., GRANADOS, H., RIVERA, A., & HUGGEL, C. (2019). Area changes of glaciers on active volcanoes in Latin America between 1986 and 2015 observed from multi-temporal satellite imagery. Journal of Glaciology, 65(252), 542-556. doi:10.1017/jog.2019.30

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Scarth, P., Armston, J. A., Lucas, R., & Bunting, P. (2019). A Structural Classification of Australian Vegetation Using ICESat/GLAS, ALOS PALSAR and Landsat Sensor Data. Remote Sensing, 11(2), [147]. https://doi.org/10.3390/rs11020147.

Schepaschenko, D., See, L., Lesiv, M., Bastin, J.F., Mollicone, D., Tsendbazar, N.E., Bastin, L., McCallum, I., Bayas, J.C.L., Baklanov, A. and Perger, C., (2019). Recent Advances in Forest Observation with Visual Interpretation of Very High-Resolution Imagery. Surveys in Geophysics (2019) 40:839–862 https://doi.org/10.1007/s10712-019-09533-z

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Shepherd, J. D., Bunting, P., & Dymond, J. R. (2019). Operational Large-Scale Segmentation of Imagery Based on Iterative Elimination. Remote Sensing, 11(6), 658. http://doi.org/10.3390/rs11060658

Shepherd, A., Ivins, E., Rignot, E. et al. Mass balance of the Greenland Ice Sheet from 1992 to 2018. Nature (2019). https://doi.org/10.1038/s41586-019-1855-2

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Stengel, M. et al. (2020) ‘Cloud_cci Advanced Very High Resolution Radiometer post meridiem (AVHRR-PM) dataset version 3: 35-year climatology of global cloud and radiation properties’, Earth System Science Data, 12(1), pp. 41–60. doi: 10.5194/essd-12-41-2020.

Stopa, J. E., Ardhuin, F., Stutzmann, E., & Lecocq, T. (2019). Sea state trends and variability: Consistency between models, altimeters, buoys, and seismic data (1979–2016). Journal of Geophysical Research: Oceans, 124. https://doi.org/10.1029/2018JC014607

Tebaldini, S., Minh, D. H. T., d’Alessandro, M. M., Villard, L., Le Toan, T., & Chave, J. (2019). The Status of Technologies to Measure Forest Biomass and Structural Properties: State of the Art in SAR Tomography of Tropical Forests. Surveys in Geophysics (2019) 40: 779. https://doi.org/10.1007/s10712-019-09539-7

 Treichler, D. et al. (2019) ‘Recent glacier and lake changes in High Mountain Asia and their relation to precipitation changes’, The Cryosphere, 13(11), pp. 2977–3005. doi: 10.5194/tc-13-2977-2019.

Turco M., Herrera S., Tourigny E., Chuvieco E., Provenzale A. (2019) A comparison of remotely-sensed and inventory datasets for burned area in Mediterranean Europe. International Journal of Applied Earth Observation and Geoinformation 82, 101887. https://doi.org/10.1016/j.jag.2019.05.020.

van Peet, J. C. A. and van der A, R. J. (2019) Deriving tropospheric ozone from assimilated profiles, Atmos. Chem. Phys., 19, 8297-8309, https://doi.org/10.5194/acp-19-8297-2019.

Wehrli, K. et al. (2019) ‘Identifying Key Driving Processes of Major Recent Heat Waves’, Journal of Geophysical Research: Atmospheres. John Wiley & Sons, Ltd, 124(22), pp. 11746–11765. doi: 10.1029/2019JD030635.

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Wuite, J. et al. (2019) ‘Sub-Annual Calving Front Migration, Area Change and Calving Rates from Swath Mode CryoSat-2 Altimetry, on Filchner-Ronne Ice Shelf, Antarctica’, Remote Sensing. Multidisciplinary Digital Publishing Institute, 11(23), p. 2761. doi: 10.3390/rs11232761.

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Albergel, C., Dutra, E., Munier, S., Calvet, J.-C., Munoz-Sabater, J., de Rosnay, P., & Balsamo, G. (2018). ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better? Hydrology and Earth System Sciences22(6), 3515–3532. http://doi.org/10.5194/hess-22-3515-2018

Albergel, C., Munier, S., Bocher, A., Bonan, B., Zheng, Y., Draper, C., … Calvet, J.-C. (2018). LDAS-Monde Sequential Assimilation of Satellite Derived Observations Applied to the Contiguous US: An ERA-5 Driven Reanalysis of the Land Surface Variables. Remote Sensing10(10), 1627. http://doi.org/10.3390/rs10101627

Allen, R. J., & Anderson, R. G. (2018). 21st century California drought risk linked to model fidelity of the El Niño teleconnection. Npj Climate and Atmospheric Science1(1), 21. http://doi.org/10.1038/s41612-018-0032-x

Bai, W., Gu, X., Li, S., Tang, Y., He, Y., Gu, X., … Bai, X. (2018). The Performance of Multiple Model-Simulated Soil Moisture Datasets Relative to ECV Satellite Data in China. Water10(10), 1384. http://doi.org/10.3390/w10101384

Ball, W. T., Alsing, J., Mortlock, D. J., Staehelin, J., Haigh, J. D., Peter, T., Tummon, F., Stübi, R., Stenke, A., Anderson, J., Bourassa, A., Davis, S. M., Degenstein, D., Frith, S., Froidevaux, L., Roth, C., Sofieva, V., Wang, R., Wild, J., Yu, P., Ziemke, J. R., and Rozanov, E. V.: Evidence for a continuous decline in lower stratospheric ozone offsetting ozone layer recovery, Atmos. Chem. Phys., 18, 1379-1394, https://doi.org/10.5194/acp-18-1379-2018, 2018.

Bassiouni, M., Higgins, C. W., Still, C. J., & Good, S. P. (2018). Probabilistic inference of ecohydrological parameters using observations from point to satellite scales. Hydrology and Earth System Sciences22(6), 3229–3243. http://doi.org/10.5194/hess-22-3229-2018

Blankenship, C. B., Case, J. L., Crosson, W. L., & Zavodsky, B. T. (2018). Correction of Forcing-Related Spatial Artifacts in a Land Surface Model by Satellite Soil Moisture Data Assimilation. IEEE Geoscience and Remote Sensing Letters15(4), 498–502. http://doi.org/10.1109/LGRS.2018.2805259

Boynard, A., Hurtmans, D., Garane, K., Goutail, F., Hadji-Lazaro, J., Koukouli, M. E., Wespes, C., Vigouroux, C., Keppens, A., Pommereau, J.-P., Pazmino, A., Balis, D., Loyola, D., Valks, P., Sussmann, R., Smale, D., Coheur, P.-F., and Clerbaux, C.: Validation of the IASI FORLI/EUMETSAT ozone products using satellite (GOME-2), ground-based (Brewer–Dobson, SAOZ, FTIR) and ozonesonde measurements, Atmos. Meas. Tech., 11, 5125-5152, https://doi.org/10.5194/amt-11-5125-2018, 2018.

Brühl, C., Schallock, J., Klingmüller, K., Robert, C., Bingen, C., Clarisse, L., … North, P. (2018). Stratospheric aerosol radiative forcing simulated by the chemistry climate model EMAC using aerosol CCI satellite data. Atmospheric Chemistry and Physics Discussions, 1–15. http://doi.org/10.5194/acp-2018-330

Buchwitz, M., Reuter, M., Schneising, O., Noël, S., Gier, B., Bovensmann, H., … O'Dell, C. (2018). Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003–2016. Atmospheric Chemistry and Physics Discussions, 1–22. http://doi.org/10.5194/acp-2018-158

Camici, S., Ciabatta, L., Massari, C., & Brocca, L. (2018). How reliable are satellite precipitation estimates for driving hydrological models: A verification study over the Mediterranean area. Journal of Hydrology563, 950–961. http://doi.org/10.1016/J.JHYDROL.2018.06.067

Carvalho-Santos, C., Monteiro, A., Arenas-Castro, S., Greifeneder, F., Marcos, B., Portela, A., … Honrado, J. P. (2018). Ecosystem Services in a Protected Mountain Range of Portugal: Satellite-Based Products for State and Trend Analysis. Remote Sensing10(10), 1573. http://doi.org/10.3390/rs10101573

Cazenave, A., Palanisamy, H., & Ablain, M. (2018). Contemporary sea level changes from satellite altimetry: What have we learned? What are the new challenges? Advances in Space Research62(7), 1639–1653. http://doi.org/10.1016/J.ASR.2018.07.017

Champagne, C., Zhang, Y., Cherneski, P., Hadwen, T., Champagne, C., Zhang, Y., … Hadwen, T. (2018). Estimating Regional Scale Hydroclimatic Risk Conditions from the Soil Moisture Active-Passive (SMAP) Satellite. Geosciences8(4), 127. http://doi.org/10.3390/geosciences8040127

Chedin, A., Capelle, V., & Scott, N. A. (2018). Detection of IASI dust AOD trends over Sahara: How many years of data required? Atmospheric Research212, 120–129. http://doi.org/10.1016/J.ATMOSRES.2018.05.004

Chen, F., Crow, W. T., Bindlish, R., Colliander, A., Burgin, M. S., Asanuma, J., & Aida, K. (2018). Global-scale evaluation of SMAP, SMOS and ASCAT soil moisture products using triple collocation. Remote Sensing of Environment214, 1–13. http://doi.org/10.1016/J.RSE.2018.05.008

Chuvieco, E., Lizundia-Loiola, J., Pettinari, M. L., Ramo, R., Padilla, M., Tansey, K., … Plummer, S. (2018). Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies. Earth System Science Data Discussions, 1–24. http://doi.org/10.5194/essd-2018-46

Ciabatta, L., Massari, C., Brocca, L., Gruber, A., Reimer, C., Hahn, S., … Wagner, W. (2018). SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture. Earth System Science Data10(1), 267–280. http://doi.org/10.5194/essd-10-267-2018

Ciavatta, S., Brewin, R. J. W., Skákala, J., Polimene, L., de Mora, L., Artioli, Y., & Allen, J. I. (2018). Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations. Journal of Geophysical Research: Oceans123(2), 834–854. http://doi.org/10.1002/2017JC013490

Dahigamuwa, T., Gunaratne, M., Li, M., Dahigamuwa, T., Gunaratne, M., & Li, M. (2018). An Improved Data-Driven Approach for the Prediction of Rainfall-Triggered Soil Slides Using Downscaled Remotely Sensed Soil Moisture. Geosciences8(9), 326. http://doi.org/10.3390/geosciences8090326

de Leeuw, G., Sogacheva, L., Rodriguez, E., Kourtidis, K., Georgoulias, A. K., Alexandri, G., … van der A, R. (2018). Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns. Atmospheric Chemistry and Physics18(3), 1573–1592. http://doi.org/10.5194/acp-18-1573-2018

Dirmeyer, P., Norton, H., Dirmeyer, P. A., & Norton, H. E. (2018). Indications of Surface and Sub-Surface Hydrologic Properties from SMAP Soil Moisture Retrievals. Hydrology5(3), 36. http://doi.org/10.3390/hydrology5030036

El Khalki, E. M., Tramblay, Y., El Mehdi Saidi, M., Bouvier, C., Hanich, L., Benrhanem, M., & Alaouri, M. (2018). Comparison of modeling approaches for flood forecasting in the High Atlas Mountains of Morocco. Arabian Journal of Geosciences11(15), 410. http://doi.org/10.1007/s12517-018-3752-7

Fan, L., Wigneron, J.-P., Xiao, Q., Al-Yaari, A., Wen, J., Martin-StPaul, N., … Kerr, Y. H. (2018). Evaluation of microwave remote sensing for monitoring live fuel moisture content in the Mediterranean region. Remote Sensing of Environment205, 210–223. http://doi.org/10.1016/J.RSE.2017.11.020

Gevaert, A. I., Renzullo, L. J., van Dijk, A. I. J. M., van der Woerd, H. J., Weerts, A. H., & de Jeu, R. A. M. (2018). Joint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimation. Hydrology and Earth System Sciences22(9), 4605–4619. http://doi.org/10.5194/hess-22-4605-2018

Gómez, D., Salvador, P., Sanz, J., Casanova, C., Casanova, J., Gómez, D., … Casanova, J. L. (2018). Detecting Areas Vulnerable to Sand Encroachment Using Remote Sensing and GIS Techniques in Nouakchott, Mauritania. Remote Sensing10(10), 1541. http://doi.org/10.3390/rs10101541

Gómez, D., Salvador, P., Sanz, J., Casanova, C., Taratiel, D., & Casanova, J. L. (2018). Machine learning approach to locate desert locust breeding areas based on ESA CCI soil moisture. Journal of Applied Remote Sensing12(03), 1. http://doi.org/10.1117/1.JRS.12.036011

Gruber, A., Crow, W. T., & Dorigo, W. A. (2018). Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain. Water Resources Research54(2), 1353–1367. http://doi.org/10.1002/2017WR021277

He, W., Ju, W., Schwalm, C. R., Sippel, S., Wu, X., He, Q., … Jain, A. K. (2018). Large-Scale Droughts Responsible for Dramatic Reductions of Terrestrial Net Carbon Uptake Over North America in 2011 and 2012. Journal of Geophysical Research: Biogeosciences123(7), 2053–2071. http://doi.org/10.1029/2018JG004520

Huang, M., Crawford, J. H., Diskin, G. S., Santanello, J. A., Kumar, S. V., Pusede, S. E., … Carmichael, G. R. (2018). Modeling Regional Pollution Transport Events During KORUS-AQ: Progress and Challenges in Improving Representation of Land-Atmosphere Feedbacks. Journal of Geophysical Research: Atmospheres. http://doi.org/10.1029/2018JD028554

Jia, B., Liu, J., Xie, Z., Shi, C., Jia, B., Liu, J., … Shi, C. (2018). Interannual Variations and Trends in Remotely Sensed and Modeled Soil Moisture in China. Journal of Hydrometeorology19(5), 831–847. http://doi.org/10.1175/JHM-D-18-0003.1

Jiménez, C., Martens, B., Miralles, D. M., Fisher, J. B., Beck, H. E., & Fernández-Prieto, D. (2018). Exploring the merging of the global land evaporation WACMOS-ET products based on local tower measurements. Hydrology and Earth System Sciences22(8), 4513–4533. http://doi.org/10.5194/hess-22-4513-2018

Jin, Y., Ge, Y., Wang, J., Heuvelink, G., Wang, L., Jin, Y., … Wang, L. (2018). Geographically Weighted Area-to-Point Regression Kriging for Spatial Downscaling in Remote Sensing. Remote Sensing10(4), 579. http://doi.org/10.3390/rs10040579

Jing, W., Song, J., & Zhao, X. (2018). Evaluation of Multiple Satellite-Based Soil Moisture Products over Continental U.S. Based on In Situ Measurements. Water Resources Management32(9), 3233–3246. http://doi.org/10.1007/s11269-018-1989-2

Jing, W., Song, J., Zhao, X., Jing, W., Song, J., & Zhao, X. (2018). Validation of ECMWF Multi-Layer Reanalysis Soil Moisture Based on the OzNet Hydrology Network. Water10(9), 1123. http://doi.org/10.3390/w10091123

Jing, W., Song, J., Zhao, X., Jing, W., Song, J., & Zhao, X. (2018). A Comparison of ECV and SMOS Soil Moisture Products Based on OzNet Monitoring Network. Remote Sensing10(5), 703. http://doi.org/10.3390/rs10050703

Jing, W., Zhang, P., & Zhao, X. (2018). Reconstructing Monthly ECV Global Soil Moisture with an Improved Spatial Resolution. Water Resources Management32(7), 2523–2537. http://doi.org/10.1007/s11269-018-1944-2

Kang, J., Jin, R., Li, X., Zhang, Y., Zhu, Z., Kang, J., … Zhu, Z. (2018). Spatial Upscaling of Sparse Soil Moisture Observations Based on Ridge Regression. Remote Sensing10(2), 192. http://doi.org/10.3390/rs10020192

KanthaRao, B., & Rakesh, V. (2018). Observational evidence for the relationship between spring soil moisture and June rainfall over the Indian region. Theoretical and Applied Climatology132(3–4), 835–849. http://doi.org/10.1007/s00704-017-2116-7

Keppens, A., Lambert, J.-C., Granville, J., Hubert, D., Verhoelst, T., Compernolle, S., Latter, B., Kerridge, B., Siddans, R., Boynard, A., Hadji-Lazaro, J., Clerbaux, C., Wespes, C., Hurtmans, D. R., Coheur, P.-F., van Peet, J. C. A., van der A, R. J., Garane, K., Koukouli, M. E., Balis, D. S., Delcloo, A., Kivi, R., Stübi, R., Godin-Beekmann, S., Van Roozendael, M., and Zehner, C.: Quality assessment of the Ozone_cci Climate Research Data Package (release 2017) – Part 2: Ground-based validation of nadir ozone profile data products, Atmos. Meas. Tech., 11, 3769-3800, https://doi.org/10.5194/amt-11-3769-2018, 2018.

Khaki, M., Awange, J., Forootan, E., & Kuhn, M. (2018). Understanding the association between climate variability and the Nile’s water level fluctuations and water storage changes during 1992–2016. Science of The Total Environment645, 1509–1521. http://doi.org/10.1016/J.SCITOTENV.2018.07.212

Khan, U., Ajami, H., Tuteja, N. K., Sharma, A., & Kim, S. (2018). Catchment scale simulations of soil moisture dynamics using an equivalent cross-section based hydrological modelling approach. Journal of Hydrology564, 944–966. http://doi.org/10.1016/J.JHYDROL.2018.07.066

Kim, D., Moon, H., Kim, H., Im, J., & Choi, M. (2018). Intercomparison of Downscaling Techniques for Satellite Soil Moisture Products. Advances in Meteorology2018, 1–16. http://doi.org/10.1155/2018/4832423

Kim, H., Parinussa, R., Konings, A. G., Wagner, W., Cosh, M. H., Lakshmi, V., … Choi, M. (2018). Global-scale assessment and combination of SMAP with ASCAT (active) and AMSR2 (passive) soil moisture products. Remote Sensing of Environment204, 260–275. http://doi.org/10.1016/J.RSE.2017.10.026

Kim, S., Paik, K., Johnson, F. M., & Sharma, A. (2018). Building a Flood-Warning Framework for Ungauged Locations Using Low Resolution, Open-Access Remotely Sensed Surface Soil Moisture, Precipitation, Soil, and Topographic Information. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing11(2), 375–387. http://doi.org/10.1109/JSTARS.2018.2790409

Konrad, H., Shepherd, A., Gilbert, L., Hogg, A. E., McMillan, M., Muir, A., & Slater, T. (2018). Net retreat of Antarctic glacier grounding lines. Nature Geoscience11(4), 258–262. http://doi.org/10.1038/s41561-018-0082-z

Land, P., Bailey, T., Taberner, M., Pardo, S., Sathyendranath, S., Nejabati Zenouz, K., … Quartly, G. D. (2018). A Statistical Modeling Framework for Characterising Uncertainty in Large Datasets: Application to Ocean Colour. Remote Sensing10(5), 695. http://doi.org/10.3390/rs10050695

Laurent, P., Mouillot, F., Moreno, M. V., Yue, C., & Ciais, P. (2018). Varying relationships between fire intensity and fire size at global scale. Biogeosciences Discussions, 1–18. http://doi.org/10.5194/bg-2018-334

Laurent, P., Mouillot, F., Yue, C., Ciais, P., Moreno, M. V., & Nogueira, J. M. P. (2018). FRY, a global database of fire patch functional traits derived from space-borne burned area products. Scientific Data5, 180132. http://doi.org/10.1038/sdata.2018.132

Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., … Pedersen, L. T. (2018). Version 2 of the EUMETSAT OSI SAF and ESA CCI Sea Ice Concentration Climate Data Records. The Cryosphere Discussions, 1–47. http://doi.org/10.5194/tc-2018-127

Legeais, J.-F., M. Ablain, L. Zawadzki, H. Zuo, J.A. Johannessen, M.G. Scharffenberg, L. Fenoglio-Marc,  M.J. Fernandes, O.B. Andersen, S. Rudenko, P. Cipollini, G.D. Quartly, M. Passaro, A. Cazenave, J. Benveniste, 2018. An improved and homogeneous altimeter sea level record: from the ESA Climate Change Initiative. Earth Sys. Sci. Data 10, 281-301. doi: 10.5194/essd-10-281-2018

Lindbäck, K., Kohler, J., Pettersson, R., Nuth, C., Langley, K., Messerli, A., … Brandt, O. (2018). Subglacial topography, ice thickness, and bathymetry of Kongsfjorden, northwestern Svalbard. Earth Syst. Sci. Data10, 1769–1781. http://doi.org/10.5194/essd-10-1769-2018

Liu, X., Devred, E., Johnson, C., Liu, X., Devred, E., & Johnson, C. (2018). Remote Sensing of Phytoplankton Size Class in Northwest Atlantic from 1998 to 2016: Bio-Optical Algorithms Comparison and Application. Remote Sensing10(7), 1028. http://doi.org/10.3390/rs10071028

Lobanova, P., Tilstone, G. H., Bashmachnikov, I., Brotas, V., Lobanova, P., Tilstone, G. H., … Brotas, V. (2018). Accuracy Assessment of Primary Production Models with and without Photoinhibition Using Ocean-Colour Climate Change Initiative Data in the North East Atlantic Ocean. Remote Sensing10(7), 1116. http://doi.org/10.3390/rs10071116

Lohberger, S., Stängel, M., Atwood, E. C., & Siegert, F. (2018). Spatial evaluation of Indonesia’s 2015 fire-affected area and estimated carbon emissions using Sentinel-1. Global Change Biology24(2), 644–654. http://doi.org/10.1111/gcb.13841

Loizu, J., Massari, C., Álvarez-Mozos, J., Tarpanelli, A., Brocca, L., & Casalí, J. (2018). On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation. Advances in Water Resources111, 86–104. http://doi.org/10.1016/J.ADVWATRES.2017.10.034

Lou, D., Wang, G., Shan, C., Hagan, D. F. T., Ullah, W., & Shi, D. (2018). Changes of Soil Moisture from Multiple Sources during 1988–2010 in the Yellow River Basin, China. Advances in Meteorology2018, 1–14. http://doi.org/10.1155/2018/1950529

Massari, C., Camici, S., Ciabatta, L., Brocca, L., Massari, C., Camici, S., … Brocca, L. (2018). Exploiting Satellite-Based Surface Soil Moisture for Flood Forecasting in the Mediterranean Area: State Update Versus Rainfall Correction. Remote Sensing10(2), 292. http://doi.org/10.3390/rs10020292

McNabb, R., Nuth, C., Kääb, A., & Girod, L. (2018). Sensitivity of geodetic glacier mass balance estimation to DEM void interpolation. The Cryosphere Discussions, 1–29. http://doi.org/10.5194/tc-2018-175

Mei, L., Rozanov, V., Vountas, M., & Burrows, J. P. (2018). The retrieval of ice cloud parameters from multi-spectral satellite observations of reflectance using a modified XBAER algorithm. Remote Sensing of Environment215, 128–144. http://doi.org/10.1016/J.RSE.2018.06.007

Mielonen, T., Hienola, A., Kühn, T., Merikanto, J., Lipponen, A., Bergman, T., … Kokkola, H. (2018). Summertime Aerosol Radiative Effects and Their Dependence on Temperature over the Southeastern USA. Atmosphere9(5), 180. http://doi.org/10.3390/atmos9050180

Mishra, V., Shah, R., Azhar, S., Modi, P., & Kumar, R. (2018). Reconstruction of droughts in India using multiple land-surface models (1951-2015). Hydrol. Earth Syst. Sci22, 2269–2284. http://doi.org/10.5194/hess-22-2269-2018

Mölg, N., Bolch, T., Rastner, P., Strozzi, T., & Paul, F. (2018). A consistent glacier inventory for Karakoram and Pamir derived from Landsat data: distribution of debris cover and mapping challenges. Earth Syst. Sci. Data10, 1807–1827. http://doi.org/10.5194/essd-10-1807-2018

Monolisha, S., Platt, T., Sathyendranath, S., Jayasankar, J., George, G., & Jackson, T. (2018). Optical Classification of the Coastal Waters of the Northern Indian Ocean. Frontiers in Marine Science5, 87. http://doi.org/10.3389/fmars.2018.00087

Niroula, S., Halder, S., & Ghosh, S. (2018). Perturbations in the initial soil moisture conditions: Impacts on hydrologic simulation in a large river basin. Journal of Hydrology561, 509–522. http://doi.org/10.1016/J.JHYDROL.2018.04.029

Pablos, M., González-Zamora, Á., Sánchez, N., Martínez-Fernández, J., Pablos, M., González-Zamora, Á., … Martínez-Fernández, J. (2018). Assessment of Root Zone Soil Moisture Estimations from SMAP, SMOS and MODIS Observations. Remote Sensing10(7), 981. http://doi.org/10.3390/rs10070981

Parker, R. J., H. Boesch, J. McNorton, E. Comyn-Platt, M. Gloor, C. Wilson, M. P. Chipperfield, G. D. Hayman, A. A. Bloom, Evaluating year-to-year anomalies in tropical wetland methane emissions using satellite CH4 observations, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2018.02.011, Vol. 211, 261-275, 2018.

Parinussa, R. M., Wang, G., Liu, Y., Lou, D., Hagan, D. F. T., Zhan, M., … Jiang, T. (2018). Improved surface soil moisture anomalies from Fengyun-3B over the Jiangxi province of the People’s Republic of China. International Journal of Remote Sensing, 1–13. http://doi.org/10.1080/01431161.2018.1500729

Passaro, M., Rose, S. K., Andersen, O. B., Boergens, E., Calafat, F. M., Dettmering, D., & Benveniste, J. (2018). ALES+: Adapting a homogenous ocean retracker for satellite altimetry to sea ice leads, coastal and inland waters. Remote Sensing of Environment211, 456–471. http://doi.org/10.1016/J.RSE.2018.02.074

Petropoulos, G., Srivastava, P., Piles, M., Pearson, S., Petropoulos, G. P., Srivastava, P. K., … Pearson, S. (2018). Earth Observation-Based Operational Estimation of Soil Moisture and Evapotranspiration for Agricultural Crops in Support of Sustainable Water Management. Sustainability10(2), 181. http://doi.org/10.3390/su10010181

Pinnington, E., Quaife, T., & Black, E. (2018). Impact of remotely sensed soil moisture and precipitation on soil moisture prediction in a data assimilation system with the JULES land surface model. Hydrology and Earth System Sciences22(4), 2575–2588. http://doi.org/10.5194/hess-22-2575-2018

Poméon, T., Diekkrüger, B., Springer, A., Kusche, J., Eicker, A., Poméon, T., … Eicker, A. (2018). Multi-Objective Validation of SWAT for Sparsely-Gauged West African River Basins—A Remote Sensing Approach. Water10(4), 451. http://doi.org/10.3390/w10040451

Prakash, S. (2018). Capabilities of satellite-derived datasets to detect consecutive Indian mon...: Discovery Service for European Space Agency. Current Science 114(11), 2362–2368. http://doi.org/10.18520/cs/v114/i11/2362-2368

Ramo, R., García, M., Rodríguez, D., & Chuvieco, E. (2018). A data mining approach for global burned area mapping. International Journal of Applied Earth Observation and Geoinformation73, 39–51. http://doi.org/10.1016/J.JAG.2018.05.027

Roteta, E. et al. (2018) Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa. Remote Sensing of Environment 222 (2019) 1–17.  https://doi.org/10.1016/j.rse.2018.12.011

Ruosteenoja, K., Markkanen, T., Venäläinen, A., Räisänen, P., & Peltola, H. (2018). Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century. Climate Dynamics50(3–4), 1177–1192. http://doi.org/10.1007/s00382-017-3671-4

Sawada, Y., Sawada, & Yohei. (2018). Quantifying Drought Propagation from Soil Moisture to Vegetation Dynamics Using a Newly Developed Ecohydrological Land Reanalysis. Remote Sensing10(8), 1197. http://doi.org/10.3390/rs10081197

Sevestre, H., Benn, D. I., Luckman, A., Nuth, C., Kohler, J., Lindbäck, K., & Pettersson, R. (2018). Tidewater Glacier Surges Initiated at the Terminus. Journal of Geophysical Research: Earth Surface123(5), 1035–1051. http://doi.org/10.1029/2017JF004358

Shalina, E. V., & Sandven, S. (2018). Snow depth on Arctic sea ice from historical in situ data. The Cryosphere12(6), 1867–1886. http://doi.org/10.5194/tc-12-1867-2018

Sheng, J.-X., Jacob, D. J., Turner, A. J., Maasakkers, J. D., Benmergui, J., Bloom, A. A., … Parker, R. J. (2018). 2010–2016 methane trends over Canada, the United States, and Mexico observed by the GOSAT satellite: contributions from different source sectors. Atmospheric Chemistry and Physics18(16), 12257–12267. http://doi.org/10.5194/acp-18-12257-2018

Skákala, J., Ford, D., Brewin, R. J. W., McEwan, R., Kay, S., Taylor, B., … Ciavatta, S. (2018). The Assimilation of Phytoplankton Functional Types for Operational Forecasting in the Northwest European Shelf. Journal of Geophysical Research: Oceans123(8), 5230–5247. http://doi.org/10.1029/2018JC014153

Stocker, B. D., Zscheischler, J., Keenan, T. F., Prentice, I. C., Peñuelas, J., & Seneviratne, S. I. (2018). Quantifying soil moisture impacts on light use efficiency across biomes. New Phytologist218(4), 1430–1449. http://doi.org/10.1111/nph.15123

Teubner, I. E., Forkel, M., Jung, M., Liu, Y. Y., Miralles, D. G., Parinussa, R., … Dorigo, W. A. (2018). Assessing the relationship between microwave vegetation optical depth and gross primary production. International Journal of Applied Earth Observation and Geoinformation65, 79–91. http://doi.org/10.1016/J.JAG.2017.10.006

van der Schalie, R., de Jeu, R., Parinussa, R., Rodríguez-Fernández, N., Kerr, Y., Al-Yaari, A., … Drusch, M. (2018). The Effect of Three Different Data Fusion Approaches on the Quality of Soil Moisture Retrievals from Multiple Passive Microwave Sensors. Remote Sensing10(2), 107. http://doi.org/10.3390/rs10010107

van Peet, J. C. A., van der A, R. J., Kelder, H. M., & Levelt, P. F. (2018). Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments. Atmospheric Chemistry and Physics18(3), 1685–1704. http://doi.org/10.5194/acp-18-1685-2018

Wang, H., He, B., Zhang, Y., Huang, L., Chen, Z., & Liu, J. (2018). Response of ecosystem productivity to dry/wet conditions indicated by different drought indices. Science of The Total Environment612, 347–357. http://doi.org/10.1016/j.scitotenv.2017.08.212

Wang, S., Mo, X., Hu, S., Liu, S., & Liu, Z. (2018). Assessment of droughts and wheat yield loss on the North China Plain with an aggregate drought index (ADI) approach. Ecological Indicators87, 107–116. http://doi.org/10.1016/J.ECOLIND.2017.12.047

Wang, Y., Yang, J., Chen, Y., De Maeyer, P., Li, Z., & Duan, W. (2018). Detecting the Causal Effect of Soil Moisture on Precipitation Using Convergent Cross Mapping. Scientific Reports8(1), 12171. http://doi.org/10.1038/s41598-018-30669-2

Weber, M., Coldewey-Egbers, M., Fioletov, V. E., Frith, S. M., Wild, J. D., Burrows, J. P., … Loyola, D. (2018). Total ozone trends from 1979 to 2016 derived from five merged observational datasets – the emergence into ozone recovery. Atmospheric Chemistry and Physics18(3), 2097–2117. http://doi.org/10.5194/acp-18-2097-2018

Xie, Y., Xue, Y., Che, Y., Guang, J., Mei, L., Voorhis, D., … Xu, H. (2018). Ensemble of ESA/AATSR Aerosol Optical Depth Products Based on the Likelihood Estimate Method With Uncertainties. IEEE Transactions on Geoscience and Remote Sensing56(2), 997–1007. http://doi.org/10.1109/TGRS.2017.2757910

Xu, X.-Y., Birol, F., Cazenave, A., Xu, X.-Y., Birol, F., & Cazenave, A. (2018). Evaluation of Coastal Sea Level Offshore Hong Kong from Jason-2 Altimetry. Remote Sensing10(2), 282. http://doi.org/10.3390/rs10020282

Yan, H., Zarekarizi, M., & Moradkhani, H. (2018). Toward improving drought monitoring using the remotely sensed soil moisture assimilation: A parallel particle filtering framework. Remote Sensing of Environment216, 456–471. http://doi.org/10.1016/J.RSE.2018.07.017

Yin, J., Shen, R., Meng, Q., Xu, H., & Wang, H. (2018). Satellite Soil Moisture and Its Applications. Advances in Meteorology2018, 1–2. http://doi.org/10.1155/2018/4328574

Zampieri, M., Carmona Garcia, G., Dentener, F., Gumma, M., Salamon, P., Seguini, L., … Toreti, A. (2018). Surface Freshwater Limitation Explains Worst Rice Production Anomaly in India in 2002. Remote Sensing10(2), 244. http://doi.org/10.3390/rs10020244

Zhang, Q., Li, J., Gu, X., & Shi, P. (2018). Is the Pearl River basin, China, drying or wetting? Seasonal variations, causes and implications. Global and Planetary Change166, 48–61. http://doi.org/10.1016/J.GLOPLACHA.2018.04.005

Zhao, W., Sánchez, N., Lu, H., & Li, A. (2018). A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression. Journal of Hydrology563, 1009–1024. http://doi.org/10.1016/J.JHYDROL.2018.06.081

Zheng, D., Wang, X., van der Velde, R., Ferrazzoli, P., Wen, J., Wang, Z., … Su, Z. (2018). Impact of surface roughness, vegetation opacity and soil permittivity on L-band microwave emission and soil moisture retrieval in the third pole environment. Remote Sensing of Environment209, 633–647. http://doi.org/10.1016/J.RSE.2018.03.011

Zwieback, S., Colliander, A., Cosh, M. H., Martínez-Fernández, J., Mcnairn, H., Starks, P. J., … Berg, A. (2018). Estimating time-dependent vegetation biases in the SMAP soil moisture product. Hydrol. Earth Syst. Sci22, 4473–4489. http://doi.org/10.5194/hess-22-4473-2018

WCRP Sea Level Budget Working Group. (2018). Global sea-level budget 1993–present. Earth System Science Data10(3), 1551–1590. http://doi.org/10.5194/essd-10-1551-2018

2017
 

Ablain, M., Legeais, J. F., Prandi, P., Marcos, M., Fenoglio-Marc, L., Dieng, H. B., … Cazenave, A. (2017). Satellite Altimetry-Based Sea Level at Global and Regional Scales. Surveys in Geophysics38(1), 7–31. http://doi.org/10.1007/s10712-016-9389-8

Adloff, F., Jordà, G., Somot, S., Sevault, F., Arsouze, T., Meyssignac, B., … Planton, S. (2017). Improving sea level simulation in Mediterranean regional climate models. Climate Dynamics, 1–12. http://doi.org/10.1007/s00382-017-3842-3

Afshar, M. H., & Yilmaz, M. T. (2017). The added utility of nonlinear methods compared to linear methods in rescaling soil moisture products. Remote Sensing of Environment196, 224–237. http://doi.org/10.1016/J.RSE.2017.05.017

AGARWAL, V., BOLCH, T., SYED, T. H., PIECZONKA, T., STROZZI, T., & NAGAICH, R. (2017). Area and mass changes of Siachen Glacier (East Karakoram). Journal of Glaciology63(237), 148–163. http://doi.org/10.1017/jog.2016.127

Al-Naimi, N., Raitsos, D., Ben-Hamadou, R., & Soliman, Y. (2017). Evaluation of Satellite Retrievals of Chlorophyll-a in the Arabian Gulf. Remote Sensing9(3), 301. http://doi.org/10.3390/rs9030301

Albergel, C., Munier, S., Leroux, D. J., Dewaele, H., Fairbairn, D., Barbu, A. L., … Calvet, J.-C. (2017). Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area. Geoscientific Model Development10(10), 3889–3912. http://doi.org/10.5194/gmd-10-3889-2017

Altena, B., & Kääb, A. (2017). Elevation Change and Improved Velocity Retrieval Using Orthorectified Optical Satellite Data from Different Orbits. Remote Sensing9(3), 300. http://doi.org/10.3390/rs9030300

Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R., Kasibhatla, P. S., … Randerson, J. T. (2017). A human-driven decline in global burned area. Science356(6345). Retrieved from http://science.sciencemag.org/content/356/6345/1356

Arosio, C., Rozanov, A., Malinina, E., Eichmann, K.-U., von Clarmann, T., & Burrows, J. P. (2017). Retrieval of ozone profiles from OMPS limb scattering observations. Atmospheric Measurement Techniques Discussions, 1–23. http://doi.org/10.5194/amt-2017-301

Bellprat, O., Massonnet, F., Siegert, S., Prodhomme, C., Macias-Gómez, D., Guemas, V., & Doblas-Reyes, F. (2017). Uncertainty propagation in observational references to climate model scales. Remote Sensing of Environment203, 101–108. http://doi.org/10.1016/J.RSE.2017.06.034

Bellprat, O., Massonnet, F., Siegert, S., Prodhomme, C., Macias-Gómez, D., Guemas, V., & Doblas-Reyes, F. (2017). Uncertainty propagation in observational references to climate model scales. Remote Sensing of Environment203, 101–108. http://doi.org/10.1016/J.RSE.2017.06.034

Bingen, C., Robert, C. E., Stebel, K., Brühl, C., Schallock, J., Vanhellemont, F., … Pinnock, S. (2017). Stratospheric aerosol data records for the climate change initiative: Development, validation and application to chemistry-climate modelling. Remote Sensing of Environment203, 296–321. http://doi.org/10.1016/j.rse.2017.06.002

Block, T., Embacher, S., Merchant, C. J., & Donlon, C. (2017). High Performance Software Framework for the Calculation of Satellite-to-Satellite Data Matchups (MMS version 1.2). Geoscientific Model Development Discussions, 1–15. http://doi.org/10.5194/gmd-2017-54

Blunden, J., & Arndt, D. S. (2017). State of the Climate in 2016. Bulletin of the American Meteorological Society98(8), Si-S277. http://doi.org/10.1175/2017BAMSStateoftheClimate.1

Brun, F., Berthier, E., Wagnon, P., Kääb, A., & Treichler, D. (2017). A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016. Nature Geoscience10(9), 668–673. http://doi.org/10.1038/ngeo2999

Buchwitz, M., Reuter, M., Schneising, O., Hewson, W., Detmers, R. G., Boesch, H., … Wunch, D. (2017). Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set. Remote Sensing of Environment203, 276–295. http://doi.org/10.1016/J.RSE.2016.12.027

Buchwitz, M., Schneising, O., Reuter, M., Heymann, J., Krautwurst, S., Bovensmann, H., … Turner, A. J. (2017). Satellite-derived methane hotspot emission estimates using a fast data-driven method. Atmospheric Chemistry and Physics17(9), 5751–5774. http://doi.org/10.5194/acp-17-5751-2017

C, G. K., Alexander, P., Singh, S., Pelt, van, J, W. J., Hilmar, G., … Andreassen, L. M. (2017). How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment. The Cryosphere11, 949–970. http://doi.org/10.5194/tc-11-949-2017

Cammalleri, C., Vogt, J. V., Bisselink, B., & de Roo, A. (2017). Comparing soil moisture anomalies from multiple independent sources over different regions across the globe. Hydrology and Earth System Sciences Discussions, 1–34. http://doi.org/10.5194/hess-2017-196

Carret, A., Johannessen, J. A., Andersen, O. B., Ablain, M., Prandi, P., Blazquez, A., & Cazenave, A. (2017). Arctic Sea Level During the Satellite Altimetry Era. Surveys in Geophysics38(1), 251–275. http://doi.org/10.1007/s10712-016-9390-2

Chambers, D. P., Cazenave, A., Champollion, N., Dieng, H., Llovel, W., Forsberg, R., … Wada, Y. (2017). Evaluation of the Global Mean Sea Level Budget between 1993 and 2014. Surveys in Geophysics38(1), 309–327. http://doi.org/10.1007/s10712-016-9381-3

Chipperfield, M. P., Bekki, S., Dhomse, S., Harris, N. R. P., Hassler, B., Hossaini, R., … Weber, M. (2017). Detecting recovery of the stratospheric ozone layer. Nature549(7671), 211–218. http://doi.org/10.1038/nature23681

Christensen, M. W., Neubauer, D., Poulsen, C. A., Thomas, G. E., McGarragh, G. R., Povey, A. C., … Grainger, R. G. (2017). Unveiling aerosol–cloud interactions – Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate. Atmospheric Chemistry and Physics17(21), 13151–13164. http://doi.org/10.5194/acp-17-13151-2017

Christensen, M. W., Neubauer, D., Poulsen, C., Thomas, G., McGarragh, G., Povey, A. C., … Grainger, R. G. (2017). Unveiling aerosol-cloud interactions Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate. Atmospheric Chemistry and Physics Discussions, 1–21. http://doi.org/10.5194/acp-2017-450

Cipollini, P., Calafat, F. M., Jevrejeva, S., Melet, A., & Prandi, P. (2017). Monitoring Sea Level in the Coastal Zone with Satellite Altimetry and Tide Gauges. Surveys in Geophysics38(1), 33–57. http://doi.org/10.1007/s10712-016-9392-0

Cui, C., Xu, J., Zeng, J., Chen, K.-S., Bai, X., Lu, H., … Zhao, T. (2017). Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over Two Dense Network Regions at Different Spatial Scales. Remote Sensing10(2), 33. http://doi.org/10.3390/rs10010033

Dantec-Nédélec, S., Ottlé, C., Wang, T., Guglielmo, F., Maignan, F., Delbart, N., … Jouzel, J. (2017). Testing the capability of ORCHIDEE land surface model to simulate Arctic ecosystems: Sensitivity analysis and site-level model calibration. Journal of Advances in Modeling Earth Systems9(2), 1212–1230. http://doi.org/10.1002/2016MS000860

Dorigo, W., Chung, D., Gruber, A., Hahn, S., Mistelbauer, T., Parinussa, R., … Wagner, W. (2017). Hydrological cycle: Soil Moisture in "State of the Climate in 2016" Bull. Amer. Meteor. Soc98(8), 30–32. http://doi.org/10.1175/2017BAMSStateoftheClimate

Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., … Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. Remote Sensing of Environment203, 185–215. http://doi.org/10.1016/J.RSE.2017.07.001

Evers-King, H., Martinez-Vicente, V., Brewin, R. J. W., Dall’Olmo, G., Hickman, A. E., Jackson, T., … Sathyendranath, S. (2017). Validation and Intercomparison of Ocean Color Algorithms for Estimating Particulate Organic Carbon in the Oceans. Frontiers in Marine Science4, 251. http://doi.org/10.3389/fmars.2017.00251

Ford, D., & Barciela, R. (2017). Global marine biogeochemical reanalyses assimilating two different sets of merged ocean colour products. Remote Sensing of Environment203, 40–54. http://doi.org/10.1016/j.rse.2017.03.040

Forkel, M., Dorigo, W., Lasslop, G., Teubner, I., Chuvieco, E., & Thonicke, K. (2017). A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1). Geoscientific Model Development10(12), 4443–4476. http://doi.org/10.5194/gmd-10-4443-2017

Forsberg, R., Sorensen, L., Simonsen, S., Sørensen, L., & Simonsen, S. (2017). Greenland and Antarctica Ice Sheet Mass Changes and Effects on Global Sea Level. Surveys in Geophysics38(1), 89–104. http://doi.org/10.1007/s10712-016-9398-7

Girod, L., Nuth, C., Kääb, A., Etzelmüller, B., & Kohler, J. (2017). Terrain changes from images acquired on opportunistic flights by SfM photogrammetry. The Cryosphere11(2), 827–840. http://doi.org/10.5194/tc-11-827-2017

Girod, L., Nuth, C., Kääb, A., McNabb, R., & Galland, O. (2017). MMASTER: Improved ASTER DEMs for Elevation Change Monitoring. Remote Sensing9(7), 704. http://doi.org/10.3390/rs9070704

Gittings, J. A., Raitsos, D. E., Racault, M.-F., Brewin, R. J. W., Pradhan, Y., Sathyendranath, S., & Platt, T. (2017). Seasonal phytoplankton blooms in the Gulf of Aden revealed by remote sensing. Remote Sensing of Environment189, 56–66. http://doi.org/10.1016/J.RSE.2016.10.043

Goerlich, F., Bolch, T., Mukherjee, K., & Pieczonka, T. (2017). Glacier Mass Loss during the 1960s and 1970s in the Ak-Shirak Range (Kyrgyzstan) from Multiple Stereoscopic Corona and Hexagon Imagery. Remote Sensing9(3), 275. http://doi.org/10.3390/rs9030275

Gourmelen, N., Goldberg, D. N., Snow, K., Henley, S. F., Bingham, R. G., Kimura, S., … van de Berg, W. J. (2017). Channelized Melting Drives Thinning Under a Rapidly Melting Antarctic Ice Shelf. Geophysical Research Letters44(19), 9796–9804. http://doi.org/10.1002/2017GL074929

Gruber, A., Dorigo, W. A., Crow, W., & Wagner, W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing55(12), 6780–6792. http://doi.org/10.1109/TGRS.2017.2734070

Guo, L., Xiu, P., Chai, F., Xue, H., Wang, D., & Sun, J. (2017). Enhanced Chlorophyll Concentrations Induced by Kuroshio Intrusion Fronts in the Northern South China Sea. Geophysical Research Letters44(22), 11,565-11,572. http://doi.org/10.1002/2017GL075336

Hartley, A. J., MacBean, N., Georgievski, G., & Bontemps, S. (2017). Uncertainty in plant functional type distributions and its impact on land surface models. Remote Sensing of Environment203, 71–89. http://doi.org/10.1016/J.RSE.2017.07.037

He, B., Wang, H., Huang, L., Liu, J., & Chen, Z. (2017). A new indicator of ecosystem water use efficiency based on surface soil moisture retrieved from remote sensing. Ecological Indicators75, 10–16. http://doi.org/10.1016/j.ecolind.2016.12.017

Heimhuber, V., Tulbure, M. G., & Broich, M. (2017). Modeling multidecadal surface water inundation dynamics and key drivers on large river basin scale using multiple time series of Earth-observation and river flow data. Water Resources Research53(2), 1251–1269. http://doi.org/10.1002/2016WR019858

Heymann, J., Reuter, M., Buchwitz, M., Schneising, O., Bovensmann, H., Burrows, J. P., … Crisp, D. (2017). CO2 emission of Indonesian fires in 2015 estimated from satellite-derived atmospheric CO2 concentrations. Geophysical Research Letters44(3), 1537–1544. http://doi.org/10.1002/2016GL072042

Hieronymi, M., M?ller, D., & Doerffer, R. (2017). The OLCI Neural Network Swarm (ONNS): A Bio-Geo-Optical Algorithm for Open Ocean and Coastal Waters. Frontiers in Marine Science4, 140. http://doi.org/10.3389/fmars.2017.00140

Hogg, A. E., & Gudmundsson, G. H. (2017). Impacts of the Larsen-C Ice Shelf calving event. Nature Climate Change7(8), 540–542. http://doi.org/10.1038/nclimate3359

Hogg, A. E., Shepherd, A., Cornford, S. L., Briggs, K. H., Gourmelen, N., Graham, J. A., … Wuite, J. (2017). Increased ice flow in Western Palmer Land linked to ocean melting. Geophysical Research Letters44(9), 4159–4167. http://doi.org/10.1002/2016GL072110

Huber, J., Cook, A. J., Paul, F., & Zemp, M. (2017). A complete glacier inventory of the Antarctic Peninsula based on Landsat 7 images from 2000 to 2002 and other preexisting data sets. Earth Syst. Sci. Data9, 115–131. Retrieved from www.earth-syst-sci-data.net/9/115/2017/

Hunt, K. M. R., Turner, A. G., Hunt, K. M. R., & Turner, A. G. (2017). The Effect of Soil Moisture Perturbations on Indian Monsoon Depressions in a Numerical Weather Prediction Model. Journal of Climate30(21), 8811–8823. http://doi.org/10.1175/JCLI-D-16-0733.1

Jackson, T., Sathyendranath, S., & Mélin, F. (2017). An improved optical classification scheme for the Ocean Colour Essential Climate Variable and its applications. Remote Sensing of Environment203, 152–161. http://doi.org/10.1016/j.rse.2017.03.036

Jin, Q., Wei, J., Yang, Z.-L., & Lin, P. (2017). Irrigation-Induced Environmental Changes around the Aral Sea: An Integrated View from Multiple Satellite Observations. Remote Sensing9(9), 900. http://doi.org/10.3390/rs9090900

Kääb, A., Altena, B., & Mascaro, J. (2017). Coseismic displacements of the 14 November 2016 Mw 7.8 Kaikoura, New Zealand, earthquake using the Planet optical cubesat constellation. Natural Hazards and Earth System Sciences17(5), 627–639. http://doi.org/10.5194/nhess-17-627-2017

Kaminski, T., Scholze, M., Vossbeck, M., Knorr, W., Buchwitz, M., & Reuter, M. (2017). Constraining a terrestrial biosphere model with remotely sensed atmospheric carbon dioxide. Remote Sensing of Environment203, 109–124. http://doi.org/10.1016/J.RSE.2017.08.017

Karthikeyan, L., Pan, M., Wanders, N., Kumar, D. N., & Wood, E. F. (2017). Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons. Advances in Water Resources109, 236–252. http://doi.org/10.1016/J.ADVWATRES.2017.09.010

Karthikeyan, L., Pan, M., Wanders, N., Kumar, D. N., & Wood, E. F. (2017). Four decades of microwave satellite soil moisture observations: Part 1. A review of retrieval algorithms. Advances in Water Resources109, 106–120. http://doi.org/10.1016/J.ADVWATRES.2017.09.006

Kim, S., Balakrishnan, K., Liu, Y., Johnson, F., & Sharma, A. (2017). Spatial Disaggregation of Coarse Soil Moisture Data by Using High-Resolution Remotely Sensed Vegetation Products. IEEE Geoscience and Remote Sensing Letters14(9), 1604–1608. http://doi.org/10.1109/LGRS.2017.2725945

Klüser, L., Popp, T., & Popp, T. (2017). Large-Scale Analysis of Relationships between Mineral Dust, Ice Cloud Properties, and Precipitation from Satellite Observations Using a Bayesian Approach: Theoretical Basis and First Results for the Tropical Atlantic Ocean. Advances in Meteorology2017, 1–18. http://doi.org/10.1155/2017/5278120

Kolassa, J., Gentine, P., Prigent, C., Aires, F., & Alemohammad, S. H. (2017). Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 2: Product evaluation. Remote Sensing of Environment195, 202–217. http://doi.org/10.1016/j.rse.2017.04.020

Koldunov, N. V., Köhl, A., Serra, N., & Stammer, D. (2017). Sea ice assimilation into a coupled ocean–sea ice model using its adjoint. The Cryosphere11(5), 2265–2281. http://doi.org/10.5194/tc-11-2265-2017

Krug, L. A., Platt, T., Sathyendranath, S., & Barbosa, A. B. (2017). Unravelling region-specific environmental drivers of phytoplankton across a complex marine domain (off SW Iberia). Remote Sensing of Environment203, 162–184. http://doi.org/10.1016/J.RSE.2017.05.029

Kundu, D., Vervoort, R. W., & van Ogtrop, F. F. (2017). The value of remotely sensed surface soil moisture for model calibration using SWAT. Hydrological Processes31(15), 2764–2780. http://doi.org/10.1002/hyp.11219

Kylling, A., Vandenbussche, S., Capelle, V., Cuesta, J., Klüser, L., Lelli, L., … Veefkind, P. (2017). Comparison of dust layer heights from active and passive satellite sensors. Atmospheric Measurement Techniques Discussions, 1–45. http://doi.org/10.5194/amt-2017-362

Liu, L., Liao, J., Chen, X., Zhou, G., Su, Y., Xiang, Z., … Shao, H. (2017). The Microwave Temperature Vegetation Drought Index (MTVDI) based on AMSR-E brightness temperatures for long-term drought assessment across China (2003–2010). Remote Sensing of Environment199, 302–320. http://doi.org/10.1016/J.RSE.2017.07.012

Liu, Y., Wang, W., & Hu, Y. (2017). Investigating the impact of surface soil moisture assimilation on state and parameter estimation in SWAT model based on the ensemble Kalman filter in upper Huai River basin. Journal of Hydrology and Hydromechanics65(2). http://doi.org/10.1515/johh-2017-0011

M. Reuter;, M. Buchwitz;, M. Hilker;, J. Heymann;, H. Bovensmann;, J. P. Burrows;, … M. Reichstein; (2017). How Much CO2 Is Taken Up by the European Terrestrial Biosphere? AMERICAN METEOROLOGICAL SOCIETY, (APRIL 2017), 665. http://doi.org/DOI:10.1175/BAMS-D-15-00310.1

Ma, S., Wu, Q., Wang, J., & Zhang, S. (2017). Temporal Evolution of Regional Drought Detected from GRACE TWSA and CCI SM in Yunnan Province, China. Remote Sensing9(11), 1124. http://doi.org/10.3390/rs9111124

Mao, Y., Wu, Z., He, H., Lu, G., Xu, H., & Lin, Q. (2017). Spatio-temporal analysis of drought in a typical plain region based on the soil moisture anomaly percentage index. Science of the Total Environment576, 752–765. http://doi.org/10.1016/j.scitotenv.2016.10.116

Martínez-Vicente, V., Evers-King, H., Roy, S., Kostadinov, T. S., Tarran, G. A., Graff, J. R., … Sathyendranath, S. (2017). Intercomparison of Ocean Color Algorithms for Picophytoplankton Carbon in the Ocean. Frontiers in Marine Science4, 378. http://doi.org/10.3389/fmars.2017.00378

Marzeion, B., Champollion, N., Haeberli, W., Langley, K., Leclercq, P., & Paul, F. (2017). Observation-Based Estimates of Global Glacier Mass Change and Its Contribution to Sea-Level Change. Surveys in Geophysics38(1), 105–130. http://doi.org/10.1007/s10712-016-9394-y

McGarragh, G. R., Poulsen, C. A., Thomas, G. E., Povey, A. C., Sus, O., Stapelberg, S., … Grainger, R. G. (2017). The Community Cloud retrieval for CLimate (CC4CL). Part II: The optimal estimation approach. Atmospheric Measurement Techniques Discussions, 1–55. http://doi.org/10.5194/amt-2017-333

McNally, A., Arsenault, K., Kumar, S., Shukla, S., Peterson, P., Wang, S., … Verdin, J. P. (2017). A land data assimilation system for sub-Saharan Africa food and water security applications. Scientific Data4, 170012. http://doi.org/10.1038/sdata.2017.12

Mélin, F., Vantrepotte, V., Chuprin, A., Grant, M., Jackson, T., & Sathyendranath, S. (2017). Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll-a data. Remote Sensing of Environment203, 139–151. http://doi.org/10.1016/j.rse.2017.03.039

Meng, X., Li, R., Luan, L., Lyu, S., Zhang, T., Ao, Y., … Ma, Y. (2017). Detecting hydrological consistency between soil moisture and precipitation and changes of soil moisture in summer over the Tibetan Plateau. Climate Dynamics. http://doi.org/10.1007/s00382-017-3646-5

Merchant, C. J., Paul, F., Popp, T., Ablain, M., Bontemps, S., Defourny, P., … Wagner, W. (2017). Uncertainty information in climate data records from Earth observation. Earth System Science Data9(2), 511–527. http://doi.org/10.5194/essd-9-511-2017

Meyssignac, B., Piecuch, C. G., Merchant, C. J., Racault, M.-F., Palanisamy, H., MacIntosh, C., … Brewin, R. (2017). Causes of the Regional Variability in Observed Sea Level, Sea Surface Temperature and Ocean Colour Over the Period 1993-2011. Surveys in Geophysics38(1), 187–215. http://doi.org/10.1007/s10712-016-9383-1

Momen, M., Wood, J. D., Novick, K. A., Pangle, R., Pockman, W. T., McDowell, N. G., & Konings, A. G. (2017). Interacting Effects of Leaf Water Potential and Biomass on Vegetation Optical Depth. Journal of Geophysical Research: Biogeosciences122(11), 3031–3046. http://doi.org/10.1002/2017JG004145

Narama, C., Daiyrov, M., Tadono, T., Yamamoto, M., Kääb, A., Morita, R., & Ukita, J. (2017). Seasonal drainage of supraglacial lakes on debris-covered glaciers in the Tien Shan Mountains, Central Asia. Geomorphology286, 133–142. http://doi.org/10.1016/j.geomorph.2017.03.002

Nicolai-Shaw, N., Zscheischler, J., Hirschi, M., Gudmundsson, L., & Seneviratne, S. I. (2017). A drought event composite analysis using satellite remote-sensing based soil moisture. Remote Sensing of Environment203, 216–225. http://doi.org/10.1016/J.RSE.2017.06.014

Nieto, K., & Melin, F. (2017). Variability of chlorophyll-a concentration in the Gulf of Guinea and its relation to physical oceanographic variables. Progress in Oceanography151, 97–115. http://doi.org/10.1016/j.pocean.2016.11.009

Nitta, T., Yoshimura, K., Abe-Ouchi, A., Nitta, T., Yoshimura, K., & Abe-Ouchi, A. (2017). Impact of Arctic Wetlands on the Climate System: Model Sensitivity Simulations with the MIROC5 AGCM and a Snow-Fed Wetland Scheme. Journal of Hydrometeorology18(11), 2923–2936. http://doi.org/10.1175/JHM-D-16-0105.1

Nogueira, J. M. P., Ruffault, J., Chuvieco, E., & Mouillot, F. (2017). Can we go beyond burned area in the assessment of global remote sensing products with fire patch metrics? Remote Sensing9(1), 7. http://doi.org/10.3390/rs9010007

Nogueira, J., Rambal, S., Barbosa, J., & Mouillot, F. (2017). Spatial Pattern of the Seasonal Drought/Burned Area Relationship across Brazilian Biomes: Sensitivity to Drought Metrics and Global Remote-Sensing Fire Products. Climate5(2), 42. http://doi.org/10.3390/cli5020042

Padhee, S. K., Nikam, B. R., Dutta, S., & Aggarwal, S. P. (2017). Using satellite-based soil moisture to detect and monitor spatiotemporal traces of agricultural drought over Bundelkhand region of India. GIScience & Remote Sensing54(2), 144–166. http://doi.org/10.1080/15481603.2017.1286725

Padilla, M., Olofsson, P., Stehman, S. V., Tansey, K., & Chuvieco, E. (2017). Stratification and sample allocation for reference burned area data. Remote Sensing of Environment203, 240–255. http://doi.org/10.1016/J.RSE.2017.06.041

Park, J., Baik, J., & Choi, M. (2017). Satellite-based crop coefficient and evapotranspiration using surface soil moisture and vegetation indices in Northeast Asia. CATENA156, 305–314. http://doi.org/10.1016/J.CATENA.2017.04.013

Paul, F., Bolch, T., Briggs, K., Kääb, A., McMillan, M., McNabb, R., … Wuite, J. (2017). Error sources and guidelines for quality assessment of glacier area, elevation change, and velocity products derived from satellite data in the Glaciers_cci project. Remote Sensing of Environment203, 256–275. http://doi.org/10.1016/J.RSE.2017.08.038

Paul, F., Strozzi, T., Schellenberger, T., & Kääb, A. (2017). The 2015 Surge of Hispar Glacier in the Karakoram. Remote Sensing9(9), 888. http://doi.org/10.3390/rs9090888

Peng, J., & Loew, A. (2017). Recent Advances in Soil Moisture Estimation from Remote Sensing. Water9(7), 530. http://doi.org/10.3390/w9070530

Peng, J., Loew, A., & Crueger, T. (2017). The relationship between the Madden-Julian oscillation and the land surface soil moisture. Remote Sensing of Environment203, 226–239. http://doi.org/10.1016/J.RSE.2017.07.004

Pieczka, I., Pongrácz, R., Szabóné André, K., Kelemen, F. D., & Bartholy, J. (2017). Sensitivity analysis of different parameterization schemes using RegCM4.3 for the Carpathian region. Theoretical and Applied Climatology130(3–4), 1175–1188. http://doi.org/10.1007/s00704-016-1941-4

Plummer, S., Lecomte, P., & Doherty, M. (2017). The ESA Climate Change Initiative (CCI): A European contribution to the generation of the Global Climate Observing System. Remote Sensing of Environment. http://doi.org/10.1016/j.rse.2017.07.014

Protopapadaki, S. E., Stubenrauch, C. J., & Feofilov, A. G. (2017). Upper tropospheric cloud systems derived from IR sounders: Properties of cirrus anvils in the tropics. Atmospheric Chemistry and Physics17(6), 3845–3859. http://doi.org/10.5194/acp-17-3845-2017

Quartly, G. D., Legeais, J.-F., Ablain, M., Zawadzki, L., Fernandes, M. J., Rudenko, S., … Benveniste, J. (2017). A new phase in the production of quality-controlled sea level data. Earth Syst. Sci. Data Discuss., Doi:10.5194/Essd-2017-23in review, 1–22. http://doi.org/10.5194/essd-2017-23

Racault, M.-F., Sathyendranath, S., Menon, N., & Platt, T. (2017). Phenological Responses to ENSO in the Global Oceans. Surveys in Geophysics38(1), 277–293. http://doi.org/10.1007/s10712-016-9391-1

Racault, M.-F., Sathyendranath, S., Brewin, R. J. W., Raitsos, D. E., Jackson, T., & Platt, T. (2017). Impact of El Niño Variability on Oceanic Phytoplankton. Frontiers in Marine Science4, 133. http://doi.org/10.3389/fmars.2017.00133

Ramo, R., & Chuvieco, E. (2017). Developing a Random Forest Algorithm for MODIS Global Burned Area Classification. Remote Sensing9(11), 1193. http://doi.org/10.3390/rs9111193

Rastner, P., Strozzi, T., & Paul, F. (2017). Fusion of Multi-Source Satellite Data and DEMs to Create a New Glacier Inventory for Novaya Zemlya. Remote Sensing9(11), 1122. http://doi.org/10.3390/rs9111122

Reuter, M., Buchwitz, M., Schneising, O., Noël, S., Bovensmann, H., & Burrows, J. (2017). A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering—Part 2: Application to XCO2 Retrievals from OCO-2. Remote Sensing9(11), 1102. http://doi.org/10.3390/rs9111102

Reuter, M., Buchwitz, M., Schneising, O., Noël, S., Rozanov, V., Bovensmann, H., & Burrows, J. (2017). A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering—Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup. Remote Sensing9(11), 1159. http://doi.org/10.3390/rs9111159

Ricker, R., Hendricks, S., Kaleschke, L., Tian-Kunze, X., King, J., & Haas, C. (2017). A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data. The Cryosphere11(4), 1607–1623. http://doi.org/10.5194/tc-11-1607-2017

Rigden, A. J., & Salvucci, G. D. (2017). Stomatal response to humidity and CO2 implicated in recent decline in US evaporation. Global Change Biology23(3), 1140–1151. http://doi.org/10.1111/gcb.13439

Rudenko, S., Neumayer, K.-H., Dettmering, D., Esselborn, S., Schöne, T., & Raimondo, J.-C. (2017). Improvements in Precise Orbits of Altimetry Satellites and Their Impact on Mean Sea Level Monitoring. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING. Retrieved from http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7882715

Sathyendranath, S., Brewin, R. J. W., Jackson, T., Mélin, F., & Platt, T. (2017). Ocean-colour products for climate-change studies: What are their ideal characteristics? Remote Sensing of Environment203, 125–138. http://doi.org/10.1016/J.RSE.2017.04.017

Scholze, M., Buchwitz, M., Dorigo, W., Guanter, L., & Quegan, S. (2017). Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems. Biogeosciences14(14), 3401–3429. http://doi.org/10.5194/bg-14-3401-2017

Shepherd, A., & Nowicki, S. (2017). Improvements in ice-sheet sea-level projections. Nature Climate Change7(10), 672–674. http://doi.org/10.1038/nclimate3400

Shrivastava, S., Kar, S. C., & Sharma, A. R. (2017). Intraseasonal Variability of Summer Monsoon Rainfall and Droughts over Central India. Pure and Applied Geophysics174(4), 1827–1844. http://doi.org/10.1007/s00024-017-1498-x

Siegert, S., Bellprat, O., Ménégoz, M., Stephenson, D. B., Doblas-Reyes, F. J., Siegert, S., … Doblas-Reyes, F. J. (2017). Detecting Improvements in Forecast Correlation Skill: Statistical Testing and Power Analysis. Monthly Weather Review145(2), 437–450. http://doi.org/10.1175/MWR-D-16-0037.1

Sofieva, V. F., Kyrölä, E., Laine, M., Tamminen, J., Degenstein, D., Bourassa, A., … Bhartia, P. K. (2017). Merged SAGE II, Ozone_cci and OMPS ozone profile dataset and evaluation of ozone trends in the stratosphere. Atmospheric Chemistry and Physics17(20), 12533–12552. http://doi.org/10.5194/acp-17-12533-2017

Sofieva, V. F., Kyrölä, E., Laine, M., Tamminen, J., Degenstein, D., Bourassa, A., … Bhartia, P. K. (2017). Merged SAGE II, Ozone_cci and OMPS ozone profiles dataset and evaluation of ozone trends in the stratosphere. Atmospheric Chemistry and Physics Discussions, 1–28. http://doi.org/10.5194/acp-2017-598

Stengel, M., Stapelberg, S., Sus, O., Schlundt, C., Poulsen, C., Thomas, G., … Hollmann, R. (2017). Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project. Earth System Science Data9(2), 881–904. http://doi.org/10.5194/essd-9-881-2017

Strozzi, T., Kaab, A., & Schellenberger, T. (2017). Frontal destabilization of Stonebreen, Edgeoya, Svalbard. Cryosphere,11(1), 553–566. http://doi.org/10.5194/tc-11-553-2017

Strozzi, T., Paul, F., Wiesmann, A., Schellenberger, T., & Kääb, A. (2017). Circum-Arctic Changes in the Flow of Glaciers and Ice Caps from Satellite SAR Data between the 1990s and 2017. Remote Sensing9(9), 947. http://doi.org/10.3390/rs9090947

Stubenrauch, C. J., Feofilov, A. G., Protopapadaki, S. E., & Armante, R. (2017). Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications. Atmospheric Chemistry and Physics17(22), 13625–13644. http://doi.org/10.5194/acp-17-13625-2017

Sus, O., Stengel, M., Stapelberg, S., McGarragh, G., Poulsen, C., Povey, A. C., … Hollmann, R. (2017). The Community Cloud retrieval for Climate (CC4CL). Part I: A framework applied to multiple satellite imaging sensors. Atmospheric Measurement Techniques Discussions, 1–42. http://doi.org/10.5194/amt-2017-334

Tang, B., Wu, D., Zhao, X., Zhou, T., Zhao, W., & Wei, H. (2017). The Observed Impacts of Wind Farms on Local Vegetation Growth in Northern China. Remote Sensing9(4), 332. http://doi.org/10.3390/rs9040332

Tian, L., Chen, J., & Zhang, Y. (2017). Growing season carries stronger contributions to albedo dynamics on the Tibetan plateau. PLOS ONE12(9), e0180559. http://doi.org/10.1371/journal.pone.0180559

Tobin, K. J., Torres, R., Crow, W. T., & Bennett, M. E. (2017). Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS. Hydrology and Earth System Sciences Discussions, 1–33. http://doi.org/10.5194/hess-2017-118

Treichler, D., & Kääb, A. (2017). Snow depth from ICESat laser altimetry — A test study in southern Norway. Remote Sensing of Environment191, 389–401. http://doi.org/10.1016/j.rse.2017.01.022

Trofaier, A. M., Westermann, S., & Bartsch, A. (2017). Progress in space-borne studies of permafrost for climate science: Towards a multi-ECV approach. Remote Sensing of Environment203, 55–70. http://doi.org/10.1016/j.rse.2017.05.021

Wang, H.-L., An, R., You, J., Wang, Y., Chen, Y., Shen, X., … Quaye-Ballard, J. A. (2017). Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China. Journal of Applied Remote Sensing11(04), 1. http://doi.org/10.1117/1.JRS.11.045003

Xi, H., Hieronymi, M., Krasemann, H., & Röttgers, R. (2017). Phytoplankton Group Identification Using Simulated and In situ Hyperspectral Remote Sensing Reflectance. Frontiers in Marine Science4, 272. http://doi.org/10.3389/fmars.2017.00272

Yan, H., Moradkhani, H., & Zarekarizi, M. (2017). A probabilistic drought forecasting framework: A combined dynamical and statistical approach. Journal of Hydrology548, 291–304. http://doi.org/10.1016/j.jhydrol.2017.03.004

Yu, Y., Notaro, M., Wang, F., Mao, J., Shi, X., & Wei, Y. (2017). Observed positive vegetation-rainfall feedbacks in the Sahel dominated by a moisture recycling mechanism. Nature Communications8(1), 1873. http://doi.org/10.1038/s41467-017-02021-1

Yuan, S., & Quiring, S. M. (2017). Evaluation of soil moisture in CMIP5 simulations over the contiguous United States using in situ and satellite observations. Hydrol. Earth Syst. Sci21, 2203–2218. http://doi.org/10.5194/hess-21-2203-2017

Zohaib, M., Kim, H., & Choi, M. (2017). Evaluating the patterns of spatiotemporal trends of root zone soil moisture in major climate regions in East Asia. Journal of Geophysical Research: Atmospheres122(15), 7705–7722. http://doi.org/10.1002/2016JD026379

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2016

Al-Yaari, A., Wigneron, J. P., Kerr, Y., de Jeu, R., Rodriguez-Fernandez, N., van der Schalie, R., … Ducharne, A. (2016). Testing regression equations to derive long-term global soil moisture datasets from passive microwave observations. Remote Sensing of Environment180, 453–464. http://doi.org/10.1016/j.rse.2015.11.022

Ashton, I. G., Shutler, J. D., Land, P. E., Woolf, D. K., & Quartly, G. D. (2016). A sensitivity analysis of the impact of rain on regional and global sea-air fluxes of CO2. PLoS ONE11(9), e0161105. http://doi.org/10.1371/journal.pone.0161105

Barrett, B., Pratola, C., Gruber, A., & Dwyer, E. (2016). Intercomparison of soil moisture retrievals from in-situ, ASAR and ECV SM datasets over different European sites. In G. P. Petropoulos (Ed.), Satellite Soil Moisture Retrievals: Techniques & Applications. Elsevier. Retrieved from http://eprints.gla.ac.uk/109134/1/109134.pdf

Bartsch, A., Höfler, A., Kroisleitner, C., & Trofaier, A. (2016). Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges. Remote Sensing 2016, Vol. 8, Page 9798(12), 979. http://doi.org/10.3390/RS8120979

Belo Couto, A., Brotas, V., Mélin, F., Groom, S., & Sathyendranath, S. (2016). Inter-comparison of OC-CCI chlorophyll- aestimates with precursor data sets. International Journal of Remote Sensing37(18), 4337–4355. http://doi.org/10.1080/01431161.2016.1209313

BHATTACHARYA, A., BOLCH, T., MUKHERJEE, K., PIECZONKA, T., KROPÁČEK, J., & BUCHROITHNER, M. F. (2016). Overall recession and mass budget of Gangotri Glacier, Garhwal Himalayas, from 1965 to 2015 using remote sensing data. Journal of Glaciology62(236), 1115–1133. http://doi.org/10.1017/jog.2016.96

Boynard, A., Hurtmans, D., Koukouli, M. E., Goutail, F., Bureau, J., Safieddine, S., … Clerbaux, C. (2016). Seven years of IASI ozone retrievals from FORLI: validation with independent total column and vertical profile measurements. Atmospheric Measurement Techniques9(9), 4327–4353. http://doi.org/10.5194/amt-9-4327-2016

Brewin, R. J. W., Dall’Olmo, G., Pardo, S., van Dongen-Vogels, V., & Boss, E. S. (2016). Underway spectrophotometry along the Atlantic Meridional Transect reveals high performance in satellite chlorophyll retrievals. Remote Sensing of Environment183, 82–97. http://doi.org/10.1016/j.rse.2016.05.005

Buchwitz, M., Schneising, O., Reuter, M., Heymann, J., Krautwurst, S., Bovensmann, H., … Frankenberg, C. (2016). Satellite-derived methane hotspot emission estimates using a fast data-driven method. Atmospheric Chemistry and Physics Discussions, 1–40. http://doi.org/10.5194/acp-2016-755

Cañas, I. A., & Salinero, E. C. (2016). DESARROLLO DE UN ALGORITMO GLOBAL DE ÁREA QUEMADA PARA IMÁGENES DEL SENSOR ENVISAT-MERIS. GeoFocus. Revista Internacional de Ciencia y Tecnología de La Información Geográfica0(17), 3–25. Retrieved from http://www.geofocus.org/index.php/geofocus/article/view/423/350

Che, Y., Xue, Y., Mei, L., Guang, J., She, L., Guo, J., … Fan, C. (2016). Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China. Atmospheric Chemistry and Physics16(15), 9655–9674. http://doi.org/10.5194/acp-16-9655-2016

Chen, T., McVicar, T., Wang, G., Chen, X., de Jeu, R., Liu, Y., … Dolman, A. (2016). Advantages of Using Microwave Satellite Soil Moisture over Gridded Precipitation Products and Land Surface Model Output in Assessing Regional Vegetation Water Availability and Growth Dynamics for a Lateral Inflow Receiving Landscape. Remote Sensing8(5), 428. http://doi.org/10.3390/rs8050428

Chuvieco, E., Yue, C., Heil, A., Mouillot, F., Alonso-Canas, I., Padilla, M., … Tansey, K. (2016). A new global burned area product for climate assessment of fire impacts. Global Ecology and Biogeography25(5), n/a-n/a. http://doi.org/10.1111/geb.12440

Ciabatta, L., Brocca, L., Massari, C., Moramarco, T., Gabellani, S., Puca, S., & Wagner, W. (2016). Rainfall-runoff modelling by using SM2RAIN-derived and state-of-the-art satellite rainfall products over Italy. International Journal of Applied Earth Observation and Geoinformation48, 163–173. http://doi.org/10.1016/j.jag.2015.10.004

de Jeu, R., & Dorigo, W. (2016). On the importance of satellite observed soil moisture. International Journal of Applied Earth Observation and Geoinformation45, 107–109. http://doi.org/10.1016/j.jag.2015.10.007

Dorigo, W., & de Jeu, R. (2016). Satellite soil moisture for advancing our understanding of earth system processes and climate change. International Journal of Applied Earth Observation and Geoinformation48, 1–4. http://doi.org/10.1016/j.jag.2016.02.007

Dragani, R. (2016). A comparative analysis of UV nadir-backscatter and infrared limb-emission ozone data assimilation. Atmospheric Chemistry and Physics16(13), 8539–8557. http://doi.org/10.5194/acp-16-8539-2016

Eberenz, J., Verbesselt, J., Herold, M., Tsendbazar, N. E., Sabatino, G., & Rivolta, G. (2016). Evaluating the potential of proba-v satellite image time series for improving lc classification in semi-arid african landscapes. Remote Sensing8(12), 987. http://doi.org/10.3390/rs8120987

Enenkel, M., Reimer, C., Dorigo, W., Wagner, W., Pfeil, I., Parinussa, R., & De Jeu, R. (2016). Combining satellite observations to develop a global soil moisture product for near-real-time applications. Hydrology and Earth System Sciences20(10), 4191–4208. http://doi.org/10.5194/hess-20-4191-2016

Enenkel, M., Steiner, C., Mistelbauer, T., Dorigo, W., Wagner, W., See, L., … Rogenhofer, E. (2016). A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations. Remote Sensing8(4), 340. http://doi.org/10.3390/rs8040340

FALASCHI, D., BOLCH, T., RASTNER, P., LENZANO, M. G., LENZANO, L., LO VECCHIO, A., & MORAGUES, S. (2016). Mass changes of alpine glaciers at the eastern margin of the Northern and Southern Patagonian Icefields between 2000 and 2012. Journal of Glaciology, 1–15. http://doi.org/10.1017/jog.2016.136

Feng, L., Palmer, P. I., Parker, R. J., Deutscher, N. M., Feist, D. G., Kivi, R., … Sussmann, R. (2016). Estimates of European uptake of CO2 inferred from GOSAT XCO2 retrievals: sensitivity to measurement bias inside and outside Europe. Atmospheric Chemistry and Physics16(3), 1289–1302. http://doi.org/10.5194/acp-16-1289-2016

Feng, L., Palmer, P. I., Bösch, H., Parker, R. J. ., Webb, A. J., Correia, C. S. C., … Zahn, A. (2016). Consistent regional fluxes of CH4 and CO2 inferred from GOSAT proxy XCH4:XCO2 retrievals, 2010–2014. Atmospheric Chemistry and Physics Discussions, pp: 1-33. http://doi.org/10.5194/acp-2016-868

Fernandes, M., & Lázaro, C. (2016). GPD+ Wet Tropospheric Corrections for CryoSat-2 and GFO Altimetry Missions. Remote Sensing8(10), 851. http://doi.org/10.3390/rs8100851

Forkel, M., Dorigo, W., Lasslop, G., Teubner, I., Chuvieco, E., & Thonicke, K. (2016). Identifying required model structures to predict global fire activity from satellite and climate data. Geoscientific Model Development Discussions, 1–35. http://doi.org/10.5194/gmd-2016-301

Gevaert, A. I., Parinussa, R. M., Renzullo, L. J., van Dijk, A. I. J. M., & de Jeu, R. A. M. (2016). Spatio-temporal evaluation of resolution enhancement for passive microwave soil moisture and vegetation optical depth. International Journal of Applied Earth Observation and Geoinformation45, 235–244. http://doi.org/10.1016/j.jag.2015.08.006

Gruber, A., Su, C.-H., Crow, W. T., Zwieback, S., Dorigo, W. A., & Wagner, W. (2016). Estimating error cross-correlations in soil moisture data sets using extended collocation analysis. Journal of Geophysical Research: Atmospheres121(3), 1208–1219. http://doi.org/10.1002/2015JD024027

Gruber, A., Su, C.-H., Zwieback, S., Crow, W., Dorigo, W., & Wagner, W. (2016). Recent advances in (soil moisture) triple collocation analysis. International Journal of Applied Earth Observation and Geoinformation45, 200–211. http://doi.org/10.1016/j.jag.2015.09.002

Guemas, V., Chevallier, M., Déqué, M., Bellprat, O., & Doblas-Reyes, F. (2016). Impact of sea ice initialization on sea ice and atmosphere prediction skill on seasonal timescales. Geophysical Research Letters43(8), 3889–3896. http://doi.org/10.1002/2015GL066626

Harper, A. B., Cox, P. M., Friedlingstein, P., Wiltshire, A. J., Jones, C. D., Sitch, S., … Van Bodegom, P. (2016). Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information. Geoscientific Model Development9(7), 2415–2440. http://doi.org/10.5194/gmd-9-2415-2016

Herold, M., See, L., Tsendbazar, N.-E., & Fritz, S. (2016). Towards an Integrated Global Land Cover Monitoring and Mapping System. Remote Sensing8(12), 1036. http://doi.org/10.3390/rs8121036

Heue, K.-P., Coldewey-Egbers, M., Delcloo, A., Lerot, C., Loyola, D., Valks, P., & van Roozendael, M. (2016). Trends of tropical tropospheric ozone from 20 years of European satellite measurements and perspectives for the Sentinel-5 Precursor. Atmospheric Measurement Techniques9(10), 5037–5051. http://doi.org/10.5194/amt-9-5037-2016

Hieronymi, M. (2016). Polarized reflectance and transmittance distribution functions of the ocean surface. Optics Express24(14), A1045. http://doi.org/10.1364/OE.24.0A1045

Hubert, D., Lambert, J.-C., Verhoelst, T., Granville, J., Keppens, A., Baray, J.-L., … Zawodny, J. M. (2016). Ground-based assessment of the bias and long-term stability of 14 limb and occultation ozone profile data records. Atmospheric Measurement Techniques9(6), 2497–2534. http://doi.org/10.5194/amt-9-2497-2016

Ikonen, J., Vehviläinen, J., Rautiainen, K., Smolander, T., Lemmetyinen, J., Bircher, S., & Pulliainen, J. (2016). The Sodankylä in situ soil moisture observation network: an example application of ESA CCI soil moisture product evaluation. Geoscientific Instrumentation, Methods and Data Systems5(1), 95–108. http://doi.org/10.5194/gi-5-95-2016

Kääb, A., Winsvold, S., Altena, B., Nuth, C., Nagler, T., & Wuite, J. (2016). Glacier Remote Sensing Using Sentinel-2. Part I: Radiometric and Geometric Performance, and Application to Ice Velocity. Remote Sensing8(7), 598. http://doi.org/10.3390/rs8070598

Kauppi, A., Tuinder, O. N. E., Tukiainen, S., Sofieva, V., & Tamminen, J. (2016). Comparison of GOME-2/Metop-A ozone profiles with GOMOS, OSIRIS and MLS measurements. Atmospheric Measurement Techniques9(1), 249–261. http://doi.org/10.5194/amt-9-249-2016

Kern, S., Rösel, A., Pedersen, L. T., Ivanova, N., Saldo, R., & Tonboe, R. T. (2016). The impact of melt ponds on summertime microwave brightness temperatures and sea ice concentrations. The Cryosphere Discussions, 1–54. http://doi.org/10.5194/tc-2015-202

Kern, S., & Ozsoy-Çiçek, B. (2016). Satellite Remote Sensing of Snow Depth on Antarctic Sea Ice: An Inter-Comparison of Two Empirical Approaches. Remote Sensing8(6), 450. http://doi.org/10.3390/rs8060450

Kern, S., Ozsoy-Çiçek, B., & Worby, A. (2016). Antarctic Sea-Ice Thickness Retrieval from ICESat: Inter-Comparison of Different Approaches. Remote Sensing8(7), 538. http://doi.org/10.3390/rs8070538

Kern, S., Rösel, A., Pedersen, L. T., Ivanova, N., Saldo, R., & Tonboe, R. T. (2016). The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations. The Cryosphere10(5), 2217–2239. http://doi.org/10.5194/tc-10-2217-2016

Kersalé, M., Petrenko, A. A., Doglioli, A. M., Nencioli, F., Bouffard, J., Blain, S., … Dekeyser, I. (2016). Lateral diffusivity coefficients from the dynamics of a SF6 patch in a coastal environment. Journal of Marine Systems153, 42–54. http://doi.org/10.1016/j.jmarsys.2015.09.003

Khvorostovsky, K., & Rampal, P. (2016). On retrieving sea ice freeboard from ICESat laser altimeter. The Cryosphere10(5), 2329–2346. http://doi.org/10.5194/tc-10-2329-2016

Klaus-Peter, H., Melanie, C.-E., Andy, D., Christophe, L., Diego, L., Pieter, V., & Michel, R. (2016). Trends of tropical tropospheric ozone from twenty years of European satellite measurements and perspectives for Sentinel-5 Precursor. Atmos. Meas. Tech. Discuss5194(10), 2016–139. http://doi.org/10.5194/amt-2016-139

Korsgaard, N. J., Nuth, C., Khan, S. A., Kjeldsen, K. K., Bjørk, A. A., Schomacker, A., … Krabill, W. B. (2016). Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978–1987. Scientific Data3, 160032. http://doi.org/10.1038/sdata.2016.32

Koukouli, M. E., Zara, M., Lerot, C., Fragkos, K., Balis, D., van Roozendael, M., … van der A, R. J. (2016). The impact of the ozone effective temperature on satellite validation using the Dobson spectrophotometer network. Atmospheric Measurement Techniques9(5), 2055–2065. http://doi.org/10.5194/amt-9-2055-2016

Kulawik, S., Wunch, D., O'Dell, C., Frankenberg, C., Reuter, M., Oda, T., … Wolf, J. (2016). Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON. Atmospheric Measurement Techniques9(2), 683–709. http://doi.org/10.5194/amt-9-683-2016

Lauer, A., Eyring, V., Righi, M., Buchwitz, M., Defourny, P., Evaldsson, M., … Will??n, U. (2016). Benchmarking CMIP5 models with a subset of ESA CCI Phase 2 data using the ESMValTool. Remote Sensing of Environment. http://doi.org/10.1016/j.rse.2017.01.007

Legeais, J.-F., Prandi, P., & Guinehut, S. (2016). Analyses of altimetry errors using Argo and GRACE data. Ocean Science12(3), 647–662. http://doi.org/10.5194/os-12-647-2016

Lelli, L., Weber, M., & Burrows, J. P. (2016). Evaluation of SCIAMACHY ESA/DLR Cloud Parameters Version 5.02 by Comparisons to Ground-Based and Other Satellite Data. Frontiers in Environmental Science4, 43. http://doi.org/10.3389/fenvs.2016.00043

Levinsen, J. F., Simonsen, S. B., Sorensen, L. S., & Forsberg, R. (2016). The Impact of DEM Resolution on Relocating Radar Altimetry Data Over Ice Sheets. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing9(7), 3158–3163. http://doi.org/10.1109/JSTARS.2016.2587684

Loew, A., Andersson, A., Trentmann, J., & Schrӧder, M. (2016). Assessing Surface Solar Radiation Fluxes in the CMIP Ensembles. Journal of Climate, JCLI-D-14-00503.1. http://doi.org/10.1175/JCLI-D-14-00503.1

Maes, K., Vandenbussche, S., Klüser, L., Kumps, N., & de Mazière, M. (2016). Vertical Profiling of Volcanic Ash from the 2011 Puyehue Cordón Caulle Eruption Using IASI. Remote Sensing8(2), 103. http://doi.org/10.3390/rs8020103

Marcos, M., Marzeion, B., Dangendorf, S., Slangen, A. B. A., Palanisamy, H., & Fenoglio-Marc, L. (2016). Internal Variability Versus Anthropogenic Forcing on Sea Level and Its Components. Surveys in Geophysics, 1–20. http://doi.org/10.1007/s10712-016-9373-3

Massart, S., Agustí-Panareda, A., Heymann, J., Buchwitz, M., Chevallier, F., Reuter, M., … Velazco, V. A. (2016). Ability of the 4-D-Var analysis of the GOSAT BESD XCO2 retrievals to characterize atmospheric CO2 at large and synoptic scales. Atmospheric Chemistry and Physics16(3), 1653–1671. http://doi.org/10.5194/acp-16-1653-2016

Massonnet, F., Bellprat, O., Guemas, V., & Doblas-Reyes, F. J. (2016). Using climate models to estimate the quality of global observational data sets. Science (New York, N.Y.)354(6311), 452–455. http://doi.org/10.1126/science.aaf6369

McNorton, J., Gloor, E., Wilson, C., Hayman, G. D., Gedney, N., Comyn-Platt, E., … Chipperfield, M. P. (2016). Role of regional wetland emissions in atmospheric methane variability. Geophysical Research Letters43(21), 11,433-11,444. http://doi.org/10.1002/2016GL070649

Mei, L., Vountas, M., Gómez-Chova, L., Rozanov, V., Jäger, M., Lotz, W., … Hollmann, R. (2016). A Cloud masking algorithm for the XBAER aerosol retrieval using MERIS data. Remote Sensing of Environment.http://doi.org/10.1016/j.rse.2016.11.016

Meul, S., Dameris, M., Langematz, U., Abalichin, J., Kerschbaumer, A., Kubin, A., & Oberländer-Hayn, S. (2016). Impact of rising greenhouse gas concentrations on future tropical ozone and UV exposure. Geophysical Research Letters43(6), 2919–2927. http://doi.org/10.1002/2016GL067997

Mielonen, T., Hienola, A., Kühn, T., Merikanto, J., Lipponen, A., Bergman, T., … Kokkola, H. (2016). Temperature-dependence of aerosol optical depth over the southeastern US. Atmospheric Chemistry and Physics Discussions0, 1–28. http://doi.org/10.5194/acp-2016-625

Nicolai-Shaw, N., Gudmundsson, L., Hirschi, M., & Seneviratne, S. I. (2016). Long-term predictability of soil moisture dynamics at the global scale: Persistence versus large-scale drivers. Geophysical Research Letters43(16), 8554–8562. http://doi.org/10.1002/2016GL069847

Pandey, S., Houweling, S., Krol, M., Aben, I., Chevallier, F., Dlugokencky, E. J., … Röckmann, T. (2016). Inverse modeling of GOSAT-retrieved ratios of total column CH<sub>4</sub> and CO<sub>2</sub> for 2009 and 2010. Atmospheric Chemistry and Physics16(8), 5043–5062. http://doi.org/10.5194/acp-16-5043-2016

Parker, R. J., Boesch, H., Wooster, M. J., Moore, D. P., Webb, A. J., Gaveau, D., & Murdiyarso, D. (2016). Atmospheric CH<sub>4</sub> and CO<sub>2</sub> enhancements and biomass burning emission ratios derived from satellite observations of the 2015 Indonesian fire plumes. Atmospheric Chemistry and Physics16(15), 10111–10131. http://doi.org/10.5194/acp-16-10111-2016

Passaro, M., Dinardo, S., Quartly, G. D., Snaith, H. M., Benveniste, J., Cipollini, P., & Lucas, B. (2016). Cross-calibrating ALES Envisat and CryoSat-2 Delay–Doppler: A coastal altimetry study in the Indonesian Seas. Advances in Space Research58(3), 289–303. http://doi.org/10.1016/j.asr.2016.04.011

Paul, F., Winsvold, S., Kääb, A., Nagler, T., & Schwaizer, G. (2016). Glacier Remote Sensing Using Sentinel-2. Part II: Mapping Glacier Extents and Surface Facies, and Comparison to Landsat 8. Remote Sensing8(7), 575. http://doi.org/10.3390/rs8070575

Petrakov, D., Shpuntova, A., Aleinikov, A., Kääb, A., Kutuzov, S., Lavrentiev, I., … Usubaliev, R. (2016). Accelerated glacier shrinkage in the Ak-Shyirak massif, Inner Tien Shan, during 2003–2013. Science of The Total Environment562, 364–378. http://doi.org/10.1016/j.scitotenv.2016.03.162

Popp, T., de Leeuw, G., Bingen, C., Brühl, C., Capelle, V., Chedin, A., … Xue, Y. (2016). Development, Production and Evaluation of Aerosol Climate Data Records from European Satellite Observations (Aerosol_cci). Remote Sensing8(5), 421. http://doi.org/10.3390/rs8050421

Prodhomme, C., Batté, L., Massonnet, F., Davini, P., Bellprat, O., Guemas, V., … Doblas-Reyes, F. J. (2016). Benefits of Increasing the Model Resolution for the Seasonal Forecast Quality in EC-Earth. Journal of Climate29(24), 9141–9162. http://doi.org/10.1175/JCLI-D-16-0117.1

Ragettli, S., Bolch, T., & Pellicciotti, F. (2016). Heterogeneous glacier thinning patterns over the last 40 years in Langtang Himal, Nepal. The Cryosphere10(5), 2075–2097. http://doi.org/10.5194/tc-10-2075-2016

Raj, R. P., Johannessen, J. A., Eldevik, T., Nilsen, J. E. Ø., & Halo, I. (2016). Quantifying mesoscale eddies in the Lofoten Basin. Journal of Geophysical Research: Oceans121(7), 4503–4521. http://doi.org/10.1002/2016JC011637

Rastner, P., Joerg, P. C., Huss, M., & Zemp, M. (2016). Historical analysis and visualization of the retreat of Findelengletscher, Switzerland, 1859–2010. Global and Planetary Change145, 67–77. http://doi.org/10.1016/j.gloplacha.2016.07.005

Rees, A. P., Tait, K., Widdicombe, C. E., Quartly, G. D., McEvoy, A. J., & Al-Moosawi, L. (2016). Metabolically active, non-nitrogen fixing, Trichodesmium in UK coastal waters during winter. Journal of Plankton Research38(3), 673–678. http://doi.org/10.1093/plankt/fbv123

Reuter, M., Buchwitz, M., Hilker, M., Heymann, J., Bovensmann, H., Burrows, J. P., … Reichstein, M. (2016). How much CO 2 is taken up by the European terrestrial biosphere? Bulletin of the American Meteorological Society, BAMS-D-15-00310.1. http://doi.org/10.1175/BAMS-D-15-00310.1

Robert, C. É., Bingen, C., Vanhellemont, F., Mateshvili, N., Dekemper, E., Tétard, C., … Zehner, C. (2016). AerGOM, an improved algorithm for stratospheric aerosol extinction retrieval from GOMOS observations – Part 2: Intercomparisons. Atmospheric Measurement Techniques9(9), 4701–4718. http://doi.org/10.5194/amt-9-4701-2016

Robson, B., Hölbling, D., Nuth, C., Stozzi, T., & Dahl, S. (2016). Decadal Scale Changes in Glacier Area in the Hohe Tauern National Park (Austria) Determined by Object-Based Image Analysis. Remote Sensing8(1), 67. http://doi.org/10.3390/rs8010067

Rodríguez-Fernández, N., Kerr, Y., van der Schalie, R., Al-Yaari, A., Wigneron, J.-P., de Jeu, R., … Drusch, M. (2016). Long Term Global Surface Soil Moisture Fields Using an SMOS-Trained Neural Network Applied to AMSR-E Data. Remote Sensing8(11), 959. http://doi.org/10.3390/rs8110959

Roxy, M. K., Modi, A., Murtugudde, R., Valsala, V., Panickal, S., Prasanna Kumar, S., … Lévy, M. (2016). A reduction in marine primary productivity driven by rapid warming over the tropical Indian Ocean. Geophysical Research Letters43(2), 826–833. http://doi.org/10.1002/2015GL066979

Rudenko, S., Dettmering, D., Esselborn, S., Fagiolini, E., & Schöne, T. (2016). Impact of Atmospheric and Oceanic De-aliasing Level-1B (AOD1B) products on precise orbits of altimetry satellites and altimetry results. Geophysical Journal International204(3), 1695–1702. http://doi.org/10.1093/gji/ggv545

Schalie, R. va. der, Kerr, Y. H., Wigneron, J. P., Rodríguez-Fernández, N. J., Al-Yaari, A., & Jeu, R. A. M. d. (2016). Global SMOS Soil Moisture Retrievals from The Land Parameter Retrieval Model. International Journal of Applied Earth Observation and Geoinformation45, 125–134. http://doi.org/10.1016/j.jag.2015.08.005

Schellenberger, T., Van Wychen, W., Copland, L., Kääb, A., & Gray, L. (2016). An Inter-Comparison of Techniques for Determining Velocities of Maritime Arctic Glaciers, Svalbard, Using Radarsat-2 Wide Fine Mode Data. Remote Sensing8(9), 785. http://doi.org/10.3390/rs8090785

Schwegmann, S., Rinne, E., Ricker, R., Hendricks, S., & Helm, V. (2016). About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice. Cryosphere10(4), 1415–1425. http://doi.org/10.5194/tc-10-1415-2016

Shutler, J. D., Quartly, G. D., Donlon, C. J., Sathyendranath, S., Platt, T., Chapron, B., … Høyer, J. L. (2016). Progress in satellite remote sensing for studying physical processes at the ocean surface and its borders with the atmosphere and sea-ice.

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Staneva, J., Wahle, K., Koch, W., Behrens, A., Fenoglio-Marc, L., & Stanev, E. V. (2016). Coastal flooding: impact of waves on storm surge during extremes. A case study for the German Bight. Natural Hazards and Earth System Sciences Discussions16(July), 1–37. http://doi.org/10.5194/nhess-2016-227

Su, C. H., Ryu, D., Dorigo, W., Zwieback, S., Gruber, A., Albergel, C., … Wagner, W. (2016). Homogeneity of a global multisatellite soil moisture climate data record. Geophysical Research Letters43(21), 11,245-11,252. http://doi.org/10.1002/2016GL070458

Treichler, D., & Kääb, A. (2016). ICESat laser altimetry over small mountain glaciers. The Cryosphere10(5), 2129–2146. http://doi.org/10.5194/tc-10-2129-2016

Turner, A. J., Jacob, D. J., Benmergui, J., Wofsy, S. C., Maasakkers, J. D., Butz, A., … Biraud, S. C. (2016). A large increase in U.S. methane emissions over the past decade inferred from satellite data and surface observations. Geophysical Research Letters43(5), 2218–2224. http://doi.org/10.1002/2016GL067987

Vanhellemont, F., Mateshvili, N., Blanot, L., Robert, C. É., Bingen, C., Sofieva, V., … Zehner, C. (2016). AerGOM, an improved algorithm for stratospheric aerosol extinction retrieval from GOMOS observations – Part 1: Algorithm description. Atmospheric Measurement Techniques9(9), 4687–4700. http://doi.org/10.5194/amt-9-4687-2016

von Schuckmann, K., Palmer, M. D., Trenberth, K. E., Cazenave, A., Chambers, D., Champollion, N., … Wild, M. (2016). An imperative to monitor Earth’s energy imbalance. Nature Climate Change6(2), 138–144. http://doi.org/10.1038/nclimate2876

Warren, M. A., Quartly, G. D., Shutler, J. D., Miller, P. I., & Yoshikawa, Y. (2016). Estimation of ocean surface currents from maximum cross correlation applied to GOCI geostationary satellite remote sensing data over the Tsushima (Korea) Straits. Journal of Geophysical Research: Oceans121(9), 6993–7009. http://doi.org/10.1002/2016JC011814

Webb, A. J., Bösch, H., Parker, R. J., Gatti, L. V, Gloor, E., Palmer, P. I., … Wilson, C. (2016). CH 4 concentrations over the Amazon from GOSAT consistent with in situ vertical profile data. Journal of Geophysical Research: Atmospheres121(18), 11006–11020. http://doi.org/10.1002/2016JD025263

Wespes, C., Hurtmans, D., Emmons, L. K., Safieddine, S., Clerbaux, C., Edwards, D. P., & Coheur, P.-F. (2016). Ozone variability in the troposphere and the stratosphere from the first 6 years of IASI observations (2008–2013). Atmospheric Chemistry and Physics16(9), 5721–5743. http://doi.org/10.5194/acp-16-5721-2016

Winsvold, S. H., Kaab, A., & Nuth, C. (2016). Regional Glacier Mapping Using Optical Satellite Data Time Series. IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPP(99), 1–14. http://doi.org/10.1109/JSTARS.2016.2527063

Yue, C., Ciais, P., Zhu, D., Wang, T., Peng, S. S., & Piao, S. L. (2016). How have past fire disturbances contributed to the current carbon balance of boreal ecosystems? Biogeosciences13(3), 675–690. http://doi.org/10.5194/bg-13-675-2016

Zawadzki, L., & Ablain, M. (2016). Accuracy of the mean sea level continuous record with future altimetric missions: Jason-3 vs. Sentinel-3a. Ocean Science12(1), 9–18. http://doi.org/10.5194/os-12-9-2016

Zhou, M., Dils, B., Wang, P., Detmers, R., Yoshida, Y., O'Dell, C. W., … De Mazière, M. (2016). Validation of TANSO-FTS/GOSAT XCO<sub>2</sub> and XCH<sub>4</sub> glint mode retrievals using TCCON data from near-ocean sites. Atmospheric Measurement Techniques9(3), 1415–1430. http://doi.org/10.5194/amt-9-1415-2016

Editorial board and Scope of the Journal. (2016). International Journal of Applied Earth Observation and Geoinformation45, IFC. http://doi.org/10.1016/S0303-2434(15)00167-1

2015
 

Ablain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., … Benveniste, J. (2015). Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project. Ocean Science11(1), 67–82. http://doi.org/10.5194/os-11-67-2015

Alexe, M., Bergamaschi, P., Segers, A., Detmers, R., Butz, A., Hasekamp, O., … Kort, E. A. (2015). Inverse modelling of CH4emissions for 2010–2011 using different satellite retrieval products from GOSAT and SCIAMACHY. Atmospheric Chemistry and Physics15(1), 113–133. http://doi.org/10.5194/acp-15-113-2015

Allison, I., Colgan, W., King M., P. F. (2015). Ice sheets, glaciers and sea level. In W. Haeberli & C. Whiteman (Eds.), Snow and Ice-Related Hazards, Risks, and Disasters (1st ed., pp. 714–748). Amsterdam, Netherlands: Elsevier. Retrieved from http://store.elsevier.com/Snow-and-Ice-Related-Hazards-Risks-and-Disaste...

Alonso-Canas, I., & Chuvieco, E. (2015). Global burned area mapping from ENVISAT-MERIS and MODIS active fire data. Remote Sensing of Environment163, 140–152. http://doi.org/10.1016/j.rse.2015.03.011

André, C., Ottlé, C., Royer, A., & Maignan, F. (2015). Land surface temperature retrieval over circumpolar Arctic using SSM/I–SSMIS and MODIS data. Remote Sensing of Environment162, 1–10. http://doi.org/10.1016/j.rse.2015.01.028

Bellprat, O., Macias-Gómez, D., Prodhomme, C., Guemas, V., & Doblas-Reyes, F. (2015). SEASONAL PREDICTION WITH EC-EARTH 3: IMPACT OF RESOLUTION AND INIITALISATION OF SEA ICE AND LAND SURFACE Seasonal prediction with EC-Earth 3: Resolution and Initialisation of land surface and sea ice Series : CFU Technical Memoranda ® Copyright 2011. Retrieved from https://earth.bsc.es/wiki/lib/exe/fetch.php?media=library:external:cfu_t...

Bolch. (2015). Glacier area and mass changes since 1964 in the Ala Archa Valley, Kyrgyz Ala-Too, northern Tien Shan, 129(1), 28–39. Retrieved from http://www.researchgate.net/publication/274887171_Glacier_area_and_mass_...

Brewin, R., Raitsos, D., Dall’Olmo, G., Zarokanellos, N., Jackson, T., Racault, M.-F., … Hoteit, I. (2015, August 1). Regional ocean-colour chlorophyll algorithms for the Red Sea. Remote Sensing of Environment. Elsevier. Retrieved from http://plymsea.ac.uk/6387/

Brewin, R., Sathyendranath, S., Jackson, T., Barlow, R., Brotas, V., Airs, R., & Lamont, T. (2015, October 1). Influence of light in the mixed-layer on the parameters of a three-component model of phytoplankton size class. Remote Sensing of Environment. http://doi.org/10.1016/j.rse.2015.07.004 <http://dx.doi.org/10.1016/j.rse.2015.07.004>

Carbajal Henken, C. K., Doppler, L., Lindstrot, R., Preusker, R., & Fischer, J. (2015). Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. Atmospheric Measurement Techniques8(8), 2623–2655. http://doi.org/10.5194/amt-8-3419-2015

Coldewey-Egbers, M., Loyola, D. G., Koukouli, M., Balis, D., Lambert, J.-C., Verhoelst, T., … Zehner, C. (2015). The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record from the ESA Climate Change Initiative. Atmospheric Measurement Techniques8(9), 3923–3940. http://doi.org/10.5194/amt-8-3923-2015

Couhert, A., Cerri, L., Legeais, J.-F., Ablain, M., Zelensky, N. P., Haines, B. J., … Otten, M. (2015). Towards the 1mm/y stability of the radial orbit error at regional scales. Advances in Space Research55(1), 2–23. http://doi.org/10.1016/j.asr.2014.06.041

d’Ovidio, F., Della Penna, A., Trull, T. W., Nencioli, F., Pujol, M.-I., Rio, M.-H., … Blain, S. (2015). The biogeochemical structuring role of horizontal stirring: Lagrangian perspectives on iron delivery downstream of the Kerguelen Plateau. Biogeosciences12(19), 5567–5581. http://doi.org/10.5194/bg-12-5567-2015

de Leeuw, G., Holzer-Popp, T., Bevan, S., Davies, W. H., Descloitres, J., Grainger, R. G., … Pinnock, S. (2015). Evaluation of seven European aerosol optical depth retrieval algorithms for climate analysis. Remote Sensing of Environment162, 295–315. http://doi.org/10.1016/j.rse.2013.04.023

de Nijs, A. H. A., Parinussa, R. M., de Jeu, R. A. M., Schellekens, J., & Holmes, T. R. H. (2015). A Methodology to Determine Radio-Frequency Interference in AMSR2 Observations. IEEE Transactions on Geoscience and Remote Sensing53(9), 5148–5159. http://doi.org/10.1109/TGRS.2015.2417653

Detmers, R. G., Hasekamp, O., Aben, I., Houweling, S., van Leeuwen, T. T., Butz, A., … Poulter, B. (2015). Anomalous carbon uptake in Australia as seen by GOSAT. Geophysical Research Letters42(19), 8177–8184. http://doi.org/10.1002/2015GL065161

Dieng, H. B., Cazenave, A., von Schuckmann, K., Ablain, M., & Meyssignac, B. (2015). Sea level budget over 2005–2013: missing contributions and data errors. Ocean Science11(5), 789–802. http://doi.org/10.5194/os-11-789-2015

Dieng, H. B., Palanisamy, H., Cazenave, A., Meyssignac, B., & von Schuckmann, K. (2015). The Sea Level Budget Since 2003: Inference on the Deep Ocean Heat Content. Surveys in Geophysics36(2), 209–229. http://doi.org/10.1007/s10712-015-9314-6

Esselborn, S., Schöne, T., & Rudenko, S. (2015). Impact of Time Variable Gravity on Annual Sea Level Variability from Altimetry, 1–8. http://doi.org/10.1007/1345_2015_103

Eyring, V., Righi, M., Evaldsson, M., Lauer, A., Wenzel, S., Jones, C., … Williams, K. D. (2015). ESMValTool (v1.0) – a community diagnostic and performance metrics tool for routine evaluation of Earth System Models in CMIP. Geoscientific Model Development Discussions8(9), 7541–7661. http://doi.org/10.5194/gmdd-8-7541-2015

Famiglietti, J. S., Cazenave, A., Eicker, A., Reager, J. T., Rodell, M., Velicogna, I., … Wood, E. F. (2015). Satellites provide the big picture. Science (New York, N.Y.)349(6249), 684–5. http://doi.org/10.1126/science.aac9238

Feng, L., Palmer, P. I., Parker, R. J., Deutscher, N. M., Feist, D. G., Kivi, R., … Sussmann, R. (2015). Elevated uptake of CO2over Europe inferred from GOSAT XCO2 retrievals: a real phenomenon or an artefact of the analysis? Atmospheric Chemistry and Physics Discussions15(2), 1989–2011. http://doi.org/10.5194/acpd-15-1989-2015

Fenoglio-Marc, L., Dinardo, S., Scharroo, R., Roland, A., Dutour Sikiric, M., Lucas, B., … Weiss, R. (2015). The German Bight: A validation of CryoSat-2 altimeter data in SAR mode. Advances in Space Research55(11), 2641–2656. http://doi.org/10.1016/j.asr.2015.02.014

Fenoglio-Marc, L., Scharroo, R., Annunziato, A., Mendoza, L., Becker, M., & Lillibridge, J. (2015). Cyclone Xaver seen by geodetic observations. Geophysical Research Letters42(22), 9925–9932. http://doi.org/10.1002/2015GL065989

Feofilov, A. G., Stubenrauch, C. J., & Delanoë, J. (2015). Ice water content vertical profiles of high-level clouds: classification and impact on radiative fluxes. Atmospheric Chemistry and Physics15(21), 12327–12344. http://doi.org/10.5194/acp-15-12327-2015

Fernandes, M. J., Lázaro, C., Ablain, M., & Pires, N. (2015). Improved wet path delays for all ESA and reference altimetric missions. Remote Sensing of Environment169, 50–74. http://doi.org/10.1016/j.rse.2015.07.023

Griesfeller, A., Lahoz, W. A., Jeu, R. A. M. d., Dorigo, W., Haugen, L. E., Svendby, T. M., & Wagner, W. (2015). Evaluation of satellite soil moisture products over Norway using ground-based observations. International Journal of Applied Earth Observation and Geoinformation. http://doi.org/10.1016/j.jag.2015.04.016

Gruber, A., Crow, W., Dorigo, W., & Wagner, W. (2015). The potential of 2D Kalman filtering for soil moisture data assimilation. Remote Sensing of Environment171, 137–148. http://doi.org/10.1016/j.rse.2015.10.019

Heymann, J., Reuter, M., Hilker, M., Buchwitz, M., Schneising, O., Bovensmann, H., … Wunch, D. (2015). Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm. Atmospheric Measurement Techniques8(7), 1787–1832. http://doi.org/10.5194/amt-8-2961-2015

Hollstein, A., Fischer, J., Carbajal Henken, C., & Preusker, R. (2015). Bayesian cloud detection for MERIS, AATSR, and their combination. Atmospheric Measurement Techniques8, 1757–1771. http://doi.org/10.5194/amt-8-1757-2015

Holzer, N., Vijay, S., Yao, T., Xu, B., Buchroithner, M., & Bolch, T. (2015). Four decades of glacier variations at Muztagh Ata (eastern Pamir): a multi-sensor study including Hexagon KH-9 and Pléiades data. The Cryosphere9(6), 2071–2088. http://doi.org/10.5194/tc-9-2071-2015

Ivanova, N., Pedersen, L. T., Tonboe, R. T., Kern, S., Heygster, G., Lavergne, T., … Shokr, M. (2015). Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations. The Cryosphere9(5), 1797–1817. http://doi.org/10.5194/tc-9-1797-2015

Ivanova, N., Rampal, P., & Bouillon, S. (2015). Assessment of error in satellite derived lead fraction in Arctic. The Cryosphere Discussions9(6), 6315–6344. http://doi.org/10.5194/tcd-9-6315-2015

Kääb, A., Treichler, D., Nuth, C., & Berthier, E. (2015). Brief Communication: Contending estimates of 2003–2008 glacier mass balance over the Pamir–Karakoram–Himalaya. The Cryosphere9(2), 557–564. http://doi.org/10.5194/tc-9-557-2015

Keller, M., Fuhrer, O., Schmidli, J., Stengel, M., Stöckli, R., & Schär, C. (2015). Evaluation of convection-resolving models using satellite data: The diurnal cycle of summer convection over the Alps. Meteorologische Zeitschrift. http://doi.org/10.1127/metz/2015/0715

Keppens, A., Lambert, J.-C., Granville, J., Miles, G., Siddans, R., van Peet, J. C. A., … Zehner, C. (2015). Round-robin evaluation of nadir ozone profile retrievals: methodology and application to MetOp-A GOME-2. Atmospheric Measurement Techniques8(5), 2093–2120. http://doi.org/10.5194/amt-8-2093-2015

Kern, S., Khvorostovsky, K., Skourup, H., Rinne, E., Parsakhoo, Z. S., Djepa, V., … Sandven, S. (2015). The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise. The Cryosphere9(1), 37–52. http://doi.org/10.5194/tc-9-37-2015

Kim, S., Liu, Y. Y., Johnson, F. M., Parinussa, R. M., & Sharma, A. (2015). A global comparison of alternate AMSR2 soil moisture products: Why do they differ? Remote Sensing of Environment161, 43–62. http://doi.org/10.1016/j.rse.2015.02.002

Klüser, L., Di Biagio, C., Kleiber, P. D., Formenti, P., & Grassian, V. H. (2015). Optical properties of non-spherical desert dust particles in the terrestrial infrared – An asymptotic approximation approach. Journal of Quantitative Spectroscopy and Radiative Transfer. http://doi.org/10.1016/j.jqsrt.2015.11.020

Koukouli, M. E., Lerot, C., Granville, J., Goutail, F., Lambert, J.-C., Pommereau, J.-P., … Zehner, C. (2015). Evaluating a new homogeneous total ozone climate data record from GOME/ERS-2, SCIAMACHY/Envisat and GOME-2/MetOp-A. Journal of Geophysical Research: Atmospheres120(23), n/a-n/a. http://doi.org/10.1002/2015JD023699

Kronenberg, M., Barandun, M., Hoelzle, M., Huss, M., Farinotti, D., Azisov, E., … Kääb, A. (2015). Mass-balance reconstruction for Glacier No. 354, Tien Shan, from 2003 to 2014. Annals of Glaciology. http://doi.org/10.3189/2016AoG71A032

Kulawik, S. S., Wunch, D., O’Dell, C., Frankenberg, C., Reuter, M., Oda, T., … Wolf, J. (2015). Consistent evaluation of GOSAT, SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON. Atmospheric Measurement Techniques Discussions8(6), 6217–6277. http://doi.org/10.5194/amtd-8-6217-2015

Laeng, A., Hubert, D., Verhoelst, T., von Clarmann, T., Dinelli, B. M., Dudhia, A., … Zehner, C. (2015). The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Remote Sensing of Environment. http://doi.org/10.1016/j.rse.2014.12.013

Le Bris, R., & Paul, F. (2015). Glacier-specific elevation changes in parts of western Alaska. Annals of Glaciology56(70), 184–192. http://doi.org/10.3189/2015AoG70A227

Le Cozannet, G., Rohmer, J., Cazenave, A., Idier, D., van de Wal, R., de Winter, R., … Oliveros, C. (2015). Evaluating uncertainties of future marine flooding occurrence as sea-level rises. Environmental Modelling & Software73, 44–56. http://doi.org/10.1016/j.envsoft.2015.07.021

Lindqvist, H., O’Dell, C. W., Basu, S., Boesch, H., Chevallier, F., Deutscher, N., … Yoshida, Y. (2015). Does GOSAT capture the true seasonal cycle of XCO2Atmospheric Chemistry and Physics Discussions15(12), 16461–16503. http://doi.org/10.5194/acpd-15-16461-2015

Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. A. M., Canadell, J. G., McCabe, M. F., Evans, J. P., & Wang, G. (2015). Recent reversal in loss of global terrestrial biomass. Nature Climate Changeadvance on. http://doi.org/10.1038/nclimate2581

Massart, S., Agustí-Panareda, A., Heymann, J., Buchwitz, M., Chevallier, F., Reuter, M., … Kivi, R. (2015). Ability of the 4-D-Var analysis of the GOSAT BESD XCO2 retrievals to characterize atmospheric CO2 at large and synoptic scales. Atmospheric Chemistry and Physics Discussions15(18), 26273–26313. http://doi.org/10.5194/acpd-15-26273-2015

Mei, L., Rozanov, V., Vountas, M., Burrows, J. P., Levy, R. C., & Lotz, W. (2015). Retrieval of aerosol optical properties using MERIS observations: Algorithm and some first results. Remote Sensing of Environment. http://doi.org/10.1016/j.rse.2016.11.015

Melet, A., Meyssignac, B., Melet, A., & Meyssignac, B. (2015). Explaining the Spread in Global Mean Thermosteric Sea Level Rise in CMIP5 Climate Models*. Journal of Climate28(24), 9918–9940. http://doi.org/10.1175/JCLI-D-15-0200.1

Mélin, F., & Vantrepotte, V. (2015). How optically diverse is the coastal ocean? Remote Sensing of Environment160, 235–251. http://doi.org/10.1016/j.rse.2015.01.023

Mélin, F., & Sclep, G. (2015). Band shifting for ocean color multi-spectral reflectance data. Optics Express23(3), 2262–79. http://doi.org/10.1364/OE.23.002262

Miles, G. M., Siddans, R., Kerridge, B. J., Latter, B. G., & Richards, N. A. D. (2015). Tropospheric ozone and ozone profiles retrieved from GOME-2 and their validation. Atmospheric Measurement Techniques8(1), 385–398. http://doi.org/10.5194/amt-8-385-2015

Müller, D., Krasemann, H., Brewin, R. J. W., Brockmann, C., Deschamps, P.-Y., Doerffer, R., … Swinton, J. (2015). The Ocean Colour Climate Change Initiative: II. Spatial and temporal homogeneity of satellite data retrieval due to systematic effects in atmospheric correction processors. Remote Sensing of Environment162, 257–270. http://doi.org/10.1016/j.rse.2015.01.033

Müller, D., Krasemann, H., Brewin, R. J. W., Brockmann, C., Deschamps, P.-Y., Doerffer, R., … Swinton, J. (2015). The Ocean Colour Climate Change Initiative: I. A methodology for assessing atmospheric correction processors based on in-situ measurements. Remote Sensing of Environment162, 242–256. http://doi.org/10.1016/j.rse.2013.11.026

Nagler, T., Rott, H., Hetzenecker, M., Wuite, J., & Potin, P. (2015). The Sentinel-1 Mission: New Opportunities for Ice Sheet Observations. Remote Sensing7(7), 9371–9389. http://doi.org/10.3390/rs70709371

Nicolai-Shaw, N., Hirschi, M., Mittelbach, H., & Seneviratne, S. I. (2015). Spatial representativeness of soil moisture using in-situ, remote sensing and land-reanalysis data. Journal of Geophysical Research: Atmospheres, n/a-n/a. http://doi.org/10.1002/2015JD023305

Noël, S., Bramstedt, K., Hilker, M., Liebing, P., Plieninger, J., Reuter, M., … Burrows, J. P. (2015). Stratospheric CH4 and CO2profiles derived from SCIAMACHY solar occultation measurements. Atmospheric Measurement Techniques Discussions8(11), 11467–11511. http://doi.org/10.5194/amtd-8-11467-2015

Nuth, C., Hagen, J.O., and Kohler, J. (2015). Glaciers in Geoscience Atlas of Svalbard. In W. K. Dallmann (Ed.), Geoscience Atlas of Svalbard. Norsk Polarinstitutt Rapport; 148, Tromsø. Retrieved from https://books.google.nl/books/about/Geoscience_Atlas_of_Svalbard.html?id...

Padilla, M., Stehman, S. V., Ramo, R., Corti, D., Hantson, S., Oliva, P., … Chuvieco, E. (2015). Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation. Remote Sensing of Environment160, 114–121. http://doi.org/10.1016/j.rse.2015.01.005

Palanisamy, H., Cazenave, A., Henry, O., Prandi, P., & Meyssignac, A. B. (2015). Sea-Level Variations Measured by the New Altimetry Mission SARAL/AltiKa and its Validation Based on Spatial Patterns and Temporal Curves Using Jason-2, Tide Gauge Data and an Overview of the Annual Sea Level Budget. Marine Geodesy38(S1), 339–353. http://doi.org/10.1080/01490419.2014.1000469

Palanisamy, H., Meyssignac, B., Cazenave, A., Delcroix, T., al, A. M. et, Ablain M, Cazenave A, V. G. and G. S., … Zhang Y, W. J. M. and B. D. S. (2015). Is anthropogenic sea level fingerprint already detectable in the Pacific Ocean? Environmental Research Letters10(8), 084024. http://doi.org/10.1088/1748-9326/10/8/084024

Palanisamy, H., Cazenave, A., Delcroix, T., & Meyssignac, B. (2015). Spatial trend patterns in the Pacific Ocean sea level during the altimetry era: the contribution of thermocline depth change and internal climate variability. Ocean Dynamics65(3), 341–356. http://doi.org/10.1007/s10236-014-0805-7

Parker, R. J., Boesch, H., Byckling, K., Webb, A. J., Palmer, P. I., Feng, L., … Velazco, V. (2015). Assessing 5 years of GOSAT Proxy XCH4 data and associated uncertainties. Atmospheric Measurement Techniques Discussions8(6), 5937–5972. http://doi.org/10.5194/amtd-8-5937-2015

Paul, F. (2015). Revealing glacier flow and surge dynamics from animated satellite image sequences: examples from the Karakoram. The Cryosphere9(6), 2201–2214. http://doi.org/10.5194/tc-9-2201-2015

Paul, F. (2015). Kap. 4.1 Kartierung von Gletschern mit Satellitendaten und das globale Gletscherinventar. In and H. E.-V. Lozán, J.L., H. Grassl, D. Kasang, D. Notz (Ed.), Warnsignal Klima: Das Eis der Erde (pp. 103–110). Retrieved from http://www.klima-warnsignale.uni-hamburg.de/eis-der-erde/eis-der-erde-bu...

Pekka, K., Larisa, S., Timo, H. V., Gerrit, de L., & Markku, K. (2015). The ADV/ASV AATSR aerosol retrieval algorithm: current status and presentation of a full-mission AOD dataset. http://doi.org/10.6084/m9.figshare.1607394

Poulter, B., MacBean, N., Hartley, A., Khlystova, I., Arino, O., Betts, R., … Peylin, P. (2015). Plant functional type classification for Earth System Models: results from the European Space Agency’s Land Cover Climate Change Initiative. Geoscientific Model Development Discussions8(1), 429–462. http://doi.org/10.5194/gmdd-8-429-2015

Poulter, B., Cadule, P., Cheiney, A., Ciais, P., Hodson, E., Peylin, P., … Zimmermann, N. E. (2015). Sensitivity of global terrestrial carbon cycle dynamics to variability in satellite-observed burned area. Global Biogeochemical Cycles, n/a-n/a. http://doi.org/10.1002/2013GB004655

Povey, A. C., & Grainger, R. G. (2015). Known and unknown unknowns: Uncertainty estimation in satellite remote sensing. Atmospheric Measurement Techniques8(11), 4699–4718. http://doi.org/10.5194/amt-8-4699-2015

Pratola, C., Barrett, B., Gruber, A., & Dwyer, E. (2015). Quality Assessment of the CCI ECV Soil Moisture Product Using ENVISAT ASAR Wide Swath Data over Spain, Ireland and Finland. Remote Sensing7(11), 15388–15423. http://doi.org/10.3390/rs71115388

Racault, M.-F., Raitsos, D. E., Berumen, M. L., Brewin, R. J. W., Platt, T., Sathyendranath, S., & Hoteit, I. (2015). Phytoplankton phenology indices in coral reef ecosystems: Application to ocean-color observations in the Red Sea. Remote Sensing of Environment160, 222–234. http://doi.org/10.1016/j.rse.2015.01.019

Rahpoe, N., Weber, M., Rozanov, A. V., Weigel, K., Bovensmann, H., Burrows, J. P., … Murtagh, D. P. (2015). Relative drifts and biases between six ozone limb satellite measurements from the last decade. Atmospheric Measurement Techniques8(10), 4369–4381. http://doi.org/10.5194/amt-8-4369-2015

Raj, R. P., Chafik, L., Nilsen, J. E. Ø., Eldevik, T., & Halo, I. (2015). The Lofoten Vortex of the Nordic Seas. Deep Sea Research Part I: Oceanographic Research Papers96, 1–14. http://doi.org/10.1016/j.dsr.2014.10.011

Reverdin, G., Morisset, S., Marieé, L., Bourras, D., Sutherland, G., Ward, B., … Lumpkin, R. (2015). Surface Salinity in the North Atlantic Subtropical Gyre During the STRASSE/SPURS Summer 2012 Cruise. Oceanography28(1), 114–123. http://doi.org/10.5670/oceanog.2015.09

Robson, B. A., Nuth, C., Dahl, S. O., Hölbling, D., Strozzi, T., & Nielsen, P. R. (2015). Automated classification of debris-covered glaciers combining optical, SAR and topographic data in an object-based environment. Remote Sensing of Environment170, 372–387. http://doi.org/10.1016/j.rse.2015.10.001

Rodríguez, E., Kolmonen, P., Virtanen, T. H., Sogacheva, L., Sundström, A.-M., & de Leeuw, G. (2015). Indirect estimation of absorption properties for fine aerosol particles using AATSR observations: a case study of wildfires in Russia in 2010. Atmospheric Measurement Techniques8(8), 3075–3085. http://doi.org/10.5194/amt-8-3075-2015

Sá, C., D’Alimonte, D., Brito, A. C., Kajiyama, T., Mendes, C. R., Vitorino, J., … Brotas, V. (2015). Validation of standard and alternative satellite ocean-color chlorophyll products off Western Iberia. Remote Sensing of Environment168, 403–419. http://doi.org/10.1016/j.rse.2015.07.018

Santoro, M., Wegmüller, U., Lamarche, C., Bontemps, S., Defourny, P., & Arino, O. (2015). Strengths and weaknesses of multi-year Envisat ASAR backscatter measurements to map permanent open water bodies at global scale. Remote Sensing of Environment171, 185–201. http://doi.org/10.1016/j.rse.2015.10.031

Schwegmann, S., Rinne, E., Ricker, R., Hendricks, S., & Helm, V. (2015). About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice. The Cryosphere Discussions9(5), 4893–4923. http://doi.org/10.5194/tcd-9-4893-2015

Serret, P., Robinson, C., Aranguren-Gassis, M., García-Martín, E. E., Gist, N., Kitidis, V., … Thomas, R. (2015). Both respiration and photosynthesis determine the scaling of plankton metabolism in the oligotrophic ocean. Nature Communications6, 6961. http://doi.org/10.1038/ncomms7961

Shutler, J. D., Warren, M. A., Miller, P. I., Barciela, R., Mahdon, R., Land, P. E., … Kurekin, A. (2015). Operational monitoring and forecasting of bathing water quality through exploiting satellite Earth observation and models: The AlgaRisk demonstration service. Computers & Geosciences77, 87–96. http://doi.org/10.1016/j.cageo.2015.01.010

Thomalla, S. J., Racault, M.-F., Swart, S., & Monteiro, P. M. S. (2015). High-resolution view of the spring bloom initiation and net community production in the Subantarctic Southern Ocean using glider data. ICES Journal of Marine Science, fsv105-. http://doi.org/10.1093/icesjms/fsv105

Turner, A. J., Jacob, D. J., Wecht, K. J., Maasakkers, J. D., Lundgren, E., Andrews, A. E., … Wunch, D. (2015). Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data. Atmospheric Chemistry and Physics15(12), 7049–7069. http://doi.org/10.5194/acp-15-7049-2015

Valente, A., Sathyendranath, S., Brotas, V., Groom, S., Grant, M., Taberner, M., … Zibordi, G. (2015, November 8). A compilation of global bio-optical in situ data for ocean-colour satellite applications. PANGAEA. http://doi.org/10.1594/PANGAEA.854832

van der Schalie, R., Parinussa, R. M., Renzullo, L. J., van Dijk, A. I. J. M., Su, C.-H., & de Jeu, R. A. M. (2015). SMOS soil moisture retrievals using the land parameter retrieval model: Evaluation over the Murrumbidgee Catchment, southeast Australia. Remote Sensing of Environment163, 70–79. http://doi.org/10.1016/j.rse.2015.03.006

Wang, D., & Kääb, A. (2015). Modeling Glacier Elevation Change from DEM Time Series. Remote Sensing7(8), 10117–10142. http://doi.org/10.3390/rs70810117

Worden, J. R., Turner, A. J., Bloom, A., Kulawik, S. S., Liu, J., Lee, M., … Payne, V. H. (2015). Quantifying lower tropospheric methane concentrations using GOSAT near-IR and TES thermal IR measurements. Atmospheric Measurement Techniques8(8), 3433–3445. http://doi.org/10.5194/amt-8-3433-2015

Xi, H., Hieronymi, M., Röttgers, R., Krasemann, H., & Qiu, Z. (2015). Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra. Remote Sensing7(11), 14781–14805. http://doi.org/10.3390/rs71114781

Xu, W., Miller, P. I., Quartly, G. D., & Pingree, R. D. (2015). Seasonality and interannual variability of the European Slope Current from 20years of altimeter data compared with in situ measurements. Remote Sensing of Environment162, 196–207. http://doi.org/10.1016/j.rse.2015.02.008

Yue, C., Ciais, P., Cadule, P., Thonicke, K., & van Leeuwen, T. T. (2015). Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 2: Carbon emissions and the role of fires in the global carbon balance. Geoscientific Model Development8(5), 1321–1338. http://doi.org/10.5194/gmd-8-1321-2015

Zemp, M., Frey, H., Gärtner-Roer, I., Nussbaumer, S. U., Hoelzle, M., Paul, F., … Vincent, C. (2015). Historically unprecedented global glacier decline in the early 21st century. Journal of Glaciology61(228), 745–762. http://doi.org/10.3189/2015JoG15J017

Zhou, M., Dils, B., Wang, P., Detmers, R. G., Yoshida, Y., O’Dell, C. W., … De Mazière, M. (2015). Validation of TANSO-FTS/GOSAT XCO2 and XCH4 glint mode retrievals using TCCON data from near-ocean sites. Atmospheric Measurement Techniques Discussions8(10), 10897–10935. http://doi.org/10.5194/amtd-8-10897-2015

Zieger, P., Aalto, P. P., Aaltonen, V., Äijälä, M., Backman, J., Hong, J., … Petäjä, T. (2015). Low hygroscopic scattering enhancement of boreal aerosol and the implications for a columnar optical closure study. Atmospheric Chemistry and Physics15(13), 7247–7267. http://doi.org/10.5194/acp-15-7247-2015

Zuo, H., Balmaseda, M. A., & Mogensen, K. (2015). The new eddy-permitting ORAP5 ocean reanalysis: description, evaluation and uncertainties in climate signals. Climate Dynamics, 1–21. http://doi.org/10.1007/s00382-015-2675-1

2014
 

Adams, C., Bourassa, A. E., Sofieva, V., Froidevaux, L., McLinden, C. A., Hubert, D., … Degenstein, D. A. (2014). Assessment of Odin-OSIRIS ozone measurements from 2001 to the present using MLS, GOMOS, and ozonesondes. Atmospheric Measurement Techniques7(1), 49–64. http://doi.org/10.5194/amt-7-49-2014

Aschmann, J., Burrows, J. P., Gebhardt, C., Rozanov, A., Hommel, R., Weber, M., & Thompson, A. M. (2014). On the hiatus in the acceleration of tropical upwelling since the beginning of the 21st century. Atmospheric Chemistry and Physics14(23), 12803–12814. http://doi.org/10.5194/acp-14-12803-2014

Barichivich, J., Briffa, K., Myneni, R., Schrier, G., Dorigo, W., Tucker, C., … Melvin, T. (2014). Temperature and Snow-Mediated Moisture Controls of Summer Photosynthetic Activity in Northern Terrestrial Ecosystems between 1982 and 2011. Remote Sensing6(2), 1390–1431. http://doi.org/10.3390/rs6021390

Barrett, B., Nitze, I., Green, S., & Cawkwell, F. (2014). Assessment of multi-temporal, multi-sensor radar and ancillary spatial data for grasslands monitoring in Ireland using machine learning approaches. Remote Sensing of Environment152, 109–124. http://doi.org/10.1016/j.rse.2014.05.018

Basu, S., Krol, M., Butz, A., Clerbaux, C., Sawa, Y., Machida, T., … Aben, I. (2014). The seasonal variation of the CO 2 flux over Tropical Asia estimated from GOSAT, CONTRAIL, and IASI. Geophysical Research Letters41(5), 1809–1815. http://doi.org/10.1002/2013GL059105

Bojanowski, J., Stöckli, R., Tetzlaff, A., & Kunz, H. (2014). The Impact of Time Difference between Satellite Overpass and Ground Observation on Cloud Cover Performance Statistics. Remote Sensing6(12), 12866–12884. http://doi.org/10.3390/rs61212866

Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., … Levizzani, V. (2014). Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research: Atmospheres119(9), 5128–5141. http://doi.org/10.1002/2014JD021489

Bulgin, C. E., Eastwood, S., Embury, O., Merchant, C. J., & Donlon, C. (2014). The Sea Surface Temperature Climate Change Initiative: Alternative Image Classification Algorithms for Sea-Ice Affected Oceans. Remote Sensing of Environment.

Carbajal Henken, C. K., Lindstrot, R., Preusker, R., & Fischer, J. (2014). FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations. Atmospheric Measurement Techniques7(11), 3873–3890. http://doi.org/10.5194/amt-7-3873-2014

Cazenave, A., Dieng, H.-B., Meyssignac, B., von Schuckmann, K., Decharme, B., & Berthier, E. (2014). The rate of sea-level rise. Nature Climate Changeadvance on. http://doi.org/10.1038/nclimate2159

Chen, T., de Jeu, R. A. M., Liu, Y. Y., van der Werf, G. R., & Dolman, A. J. (2014). Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia. Remote Sensing of Environment140, 330–338. Retrieved from http://www.sciencedirect.com/science/article/pii/S0034425713002800

Chevallier, F., Palmer, P. I., Feng, L., Boesch, H., O’Dell, C. W., & Bousquet, P. (2014). Toward robust and consistent regional CO 2 flux estimates from in situ and spaceborne measurements of atmospheric CO 2. Geophysical Research Letters41(3), 1065–1070. http://doi.org/10.1002/2013GL058772

Chiou, E. W., Bhartia, P. K., McPeters, R. D., Loyola, D. G., Coldewey-Egbers, M., Fioletov, V. E., … Frith, S. M. (2014). Comparison of profile total ozone from SBUV (v8.6) with GOME-type and ground-based total ozone for a 16-year period (1996 to 2011). Atmospheric Measurement Techniques7(6), 1681–1692. http://doi.org/10.5194/amt-7-1681-2014

Ciavatta, S., Torres, R., Martinez-Vicente, V., Smyth, T., Dall’Olmo, G., Polimene, L., & Allen, J. I. (2014). Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling. Progress in Oceanography. http://doi.org/10.1016/j.pocean.2014.06.002

Coldewey-Egbers, M., Loyola R., D. G., Braesicke, P., Dameris, M., van Roozendael, M., Lerot, C., & Zimmer, W. (2014). A new health check of the ozone layer at global and regional scales. Geophysical Research Letters, n/a-n/a. http://doi.org/10.1002/2014GL060212

Cressot, C., Chevallier, F., Bousquet, P., Crevoisier, C., Dlugokencky, E. J., Fortems-Cheiney, A., … Langenfelds, R. L. (2014). On the consistency between global and regional methane emissions inferred from SCIAMACHY, TANSO-FTS, IASI and surface measurements. Atmospheric Chemistry and Physics14(2), 577–592. http://doi.org/10.5194/acp-14-577-2014

de Jeu, R. A. M., Holmes, T. R. H., Parinussa, R. M., & Owe, M. (2014). A spatially coherent global soil moisture product with improved temporal resolution. Journal of Hydrology. http://doi.org/10.1016/j.jhydrol.2014.02.015

Dils, B., Buchwitz, M., Reuter, M., Schneising, O., Boesch, H., Parker, R., … Wunch, D. (2014). The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO2 and CH4 retrieval algorithm products with measurements from the TCCON. Atmospheric Measurement Techniques7(6), 1723–1744. http://doi.org/10.5194/amt-7-1723-2014

Diodato, N., Brocca, L., Bellocchi, G., Fiorillo, F., & Guadagno, F. M. (2014). Complexity-reduction modelling for assessing the macro-scale patterns of historical soil moisture in the Euro-Mediterranean region. Hydrological Processes28(11), 3752–3760. http://doi.org/10.1002/hyp.9925

Dorigo, W., Chung, D., Parinussa, R.M., Reimer, C., Hahn, S., Liu, Y.Y., Wagner, W., De Jeu, R.A.M., Paulik, C., Wang, G. (2014). Soil Moisture in: “State of the Climate in 2013.” Bull. Amer. Meteor95(7), S25–S26. Retrieved from http://journals.ametsoc.org/doi/pdf/10.1175/2014BAMSStateoftheClimate.1

Dorigo, W. A., Gruber, A., De Jeu, R. A. M., Wagner, W., Stacke, T., Loew, A., … Kidd, R. (2014). Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sensing of Environment. http://doi.org/10.1016/j.rse.2014.07.023

Ebojie, F., von Savigny, C., Ladstätter-Weißenmayer, A., Rozanov, A., Weber, M., Eichmann, K.-U., … Burrows, J. P. (2014). Tropospheric column amount of ozone retrieved from SCIAMACHY limb–nadir-matching observations. Atmospheric Measurement Techniques7(7), 2073–2096. http://doi.org/10.5194/amt-7-2073-2014

Eckert, E., von Clarmann, T., Kiefer, M., Stiller, G. P., Lossow, S., Glatthor, N., … Bernath, P. F. (2014). Drift-corrected trends and periodic variations in MIPAS IMK/IAA ozone measurements. Atmospheric Chemistry and Physics14(5), 2571–2589. http://doi.org/10.5194/acp-14-2571-2014

Feng, X., Tsimplis, M. N., Quartly, G. D., & Yelland, M. J. (2014). Wave height analysis from 10 years of observations in the Norwegian Sea. Continental Shelf Research72, 47–56. http://doi.org/10.1016/j.csr.2013.10.013

Feng, X., Tsimplis, M. N., Yelland, M. J., & Quartly, G. D. (2014). Changes in significant and maximum wave heights in the Norwegian Sea. Global and Planetary Change113, 68–76. http://doi.org/10.1016/j.gloplacha.2013.12.010

Fraser, A., Palmer, P. I., Feng, L., Bösch, H., Parker, R., Dlugokencky, E. J., … Langenfelds, R. L. (2014). Estimating regional fluxes of CO2 and CH4 using space-borne observations of XCH4 : XCO2. Atmospheric Chemistry and Physics14, 12883–12895. http://doi.org/10.5194/acp-14-12883-2014

Frey, H., Machguth, H., Huss, M., Huggel, C., Bajracharya, S., Bolch, T., … Stoffel, M. (2014). Estimating the volume of glaciers in the Himalayan–Karakoram region using different methods. The Cryosphere8(6), 2313–2333. http://doi.org/10.5194/tc-8-2313-2014

Gebhardt, C., Rozanov, A., Hommel, R., Weber, M., Bovensmann, H., Burrows, J. P., … Thompson, A. M. (2014). Stratospheric ozone trends and variability as seen by SCIAMACHY from 2002 to 2012. Atmospheric Chemistry and Physics14(2), 831–846. http://doi.org/10.5194/acp-14-831-2014

Hirschi, M., Mueller, B., Dorigo, W., & Seneviratne, S. I. (2014). Using remotely sensed soil moisture for land–atmosphere coupling diagnostics: The role of surface vs. root-zone soil moisture variability. Remote Sensing of Environment154, 246–252. http://doi.org/10.1016/j.rse.2014.08.030

Holmes, T. R. H., Crow, W. T., & de Jeu, R. A. M. (2014). Leveraging Microwave Polarization Information for the Calibration of a Land Data Assimilation System. Geophysical Research Letters, n/a-n/a. http://doi.org/10.1002/2014GL061991

Johannessen, J. A., Raj, R. P., Nilsen, J. E. Ø., Pripp, T., Knudsen, P., Counillon, F., … Koldunov, N. (2014). Toward Improved Estimation of the Dynamic Topography and Ocean Circulation in the High Latitude and Arctic Ocean: The Importance of GOCE. Surveys in Geophysics35(3), 661–679. http://doi.org/10.1007/s10712-013-9270-y

Kargel, J.S., Leonard, G.J., Bishop, M.P., Kääb, A., Raup, B. H. (Eds. . (2014). Global Land Ice Measurements from Space. (B. H. (Eds. . Kargel, J.S., Leonard, G.J., Bishop, M.P., Kääb, A., Raup, Ed.). Springer Praxis Books. Retrieved from http://www.springer.com/new+&+forthcoming+titles+(default)/book/978-3-540-79817-0

Karlsson, K.-G., & Johansson, E. (2014). Multi-Sensor Calibration Studies of AVHRR-Heritage Channel Radiances Using the Simultaneous Nadir Observation Approach. Remote Sensing6(3), 1845–1862. http://doi.org/10.3390/rs6031845

Laeng, A., Grabowski, U., von Clarmann, T., Stiller, G., Glatthor, N., Höpfner, M., … Zawodny, J. (2014). Validation of MIPAS IMK/IAA V5R_O3_224 ozone profiles. Atmospheric Measurement Techniques7(11), 3971–3987. http://doi.org/10.5194/amt-7-3971-2014

Lahoz, W. A., & Schneider, P. (2014). Data assimilation: making sense of Earth Observation. Frontiers in Environmental Science2. http://doi.org/10.3389/fenvs.2014.00016

Legeais, J.-F., Ablain, M., & Thao, S. (2014). Evaluation of wet troposphere path delays from atmospheric reanalyses and radiometers and their impact on the altimeter sea level. Ocean Science10(6), 893–905. http://doi.org/10.5194/os-10-893-2014

MacCallum, S. N., Merchant, C. J., Corlett, G. K., Embury, O., Petrenko, B., Cox, C., & Donlon, C. (2014). The Sea Surface Temperature Climate Change Initiative: Protocol and Outcome for Selecting Sea Surface Temperature Retrieval Methods. Remote Sensing of Environment.

Marzeion, B., Cogley, J. G., Richter, K., & Parkes, D. (2014). Attribution of global glacier mass loss to anthropogenic and natural causes. Science345(6199), 919–921. http://doi.org/10.1126/science.1254702

Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., … Donlon, C. (2014). Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal1(2), 179–191. http://doi.org/10.1002/gdj3.20

Mouillot, F., Schultz, M. G., Yue, C., Cadule, P., Tansey, K., Ciais, P., & Chuvieco, E. (2014). Ten years of global burned area products from spaceborne remote sensing—A review: Analysis of user needs and recommendations for future developments. International Journal of Applied Earth Observation and Geoinformation26, 64–79. Retrieved from http://www.sciencedirect.com/science/article/pii/S0303243413000639

Neckel, N., Kropáček, J., Bolch, T., & Hochschild, V. (2014). Glacier mass changes on the Tibetan Plateau 2003–2009 derived from ICESat laser altimetry measurements. Environmental Research Letters9(1), 014009. http://doi.org/10.1088/1748-9326/9/1/014009

Padilla, M., Stehman, S. V., Warrens, M. J., Alonso-Canas, I., Corti, D., Hantson, S., … Chuvieco, E, M. J. (2014). Comparing the Accuracy of Global Burned Area Products: Statistical Methods and Illustrative Results. Remote Sensing of Environment.

Padilla, M., Stehman, S. V., & Chuvieco, E. (2014). Validation of the 2008 MODIS-MCD45 global burned area product using stratified random sampling. Remote Sensing of Environment144, 187–196. http://doi.org/10.1016/j.rse.2014.01.008

Padilla, M., Stehman, S., Litago, J., & Chuvieco, E. (2014). Assessing the Temporal Stability of the Accuracy of a Time Series of Burned Area Products. Remote Sensing6(3), 2050–2068. http://doi.org/10.3390/rs6032050

Palanisamy, H., Cazenave, A., Meyssignac, B., Soudarin, L., Wöppelmann, G., & Becker, M. (2014). Regional sea level variability, total relative sea level rise and its impacts on islands and coastal zones of Indian Ocean over the last sixty years. Global and Planetary Change116, 54–67. http://doi.org/10.1016/j.gloplacha.2014.02.001

Parinussa, R. M., Wang, G., Holmes, T. R. H., Liu, Y. Y., Dolman, A. J., de Jeu, R. A. M., … Shi, J. (2014). Global surface soil moisture from the Microwave Radiation Imager onboard the Fengyun-3B satellite. International Journal of Remote Sensing35(19), 7007–7029. http://doi.org/10.1080/01431161.2014.960622

Parinussa, R. M., Holmes, T. R. H., Wanders, N., Dorigo, W. A., & de Jeu, R. A. M. (2014). A Preliminary Study Towards Consistent Soil Moisture from AMSR2. Journal of Hydrometeorology, 141201123810004. http://doi.org/10.1175/JHM-D-13-0200.1

Passaro, M., Cipollini, P., Vignudelli, S., Quartly, G. D., & Snaith, H. M. (2014). ALES: A multi-mission adaptive subwaveform retracker for coastal and open ocean altimetry. Remote Sensing of Environment145, 173–189. http://doi.org/10.1016/j.rse.2014.02.008

Paul, F., & Mölg, N. (2014). Hasty retreat of glaciers in northern Patagonia from 1985 to 2011. Journal of Glaciology. Retrieved from http://www.zora.uzh.ch/101919/1/2014 PaulF_j14j104 .pdf

Pellicciotti, F., Stephan, C., Miles, E., Herreid, S., Immerzeel, W., & Bolch, T. (2014). Mass-balance changes of the debris-covered glaciers in the Langtang Himal, Nepal, between 1974 and 1999. http://doi.org/10.3189/2015JoG13J237

Pfeffer, W., Arendt, A., Bliss, A., & Bolch, T. (2014). The Randolph Glacier Inventory: a globally complete inventory of glaciers. Journal of Glaciology60, 537–552. http://doi.org/10.3189/2014JoG13J176

Quartly, G. D. (2014). Metocean Comparisons of Jason-2 and AltiKa—A Method to Develop a New Wind Speed Algorithm. Marine Geodesy. Retrieved from http://www.tandfonline.com/doi/abs/10.1080/01490419.2014.988834

Quartly, G. D., & Passaro, M. (2014). Initial Examination of AltiKa’s Individual Echoes. Marine Geodesy38(sup1), 73–85. http://doi.org/10.1080/01490419.2014.984882

Reuter, M., Buchwitz, M., Hilboll, A., Richter, A., Schneising, O., Hilker, M., … Burrows, J. P. (2014). Decreasing emissions of NOx relative to CO2 in East Asia inferred from satellite observations. Nature Geoscienceadvance on(11), 792–795. http://doi.org/10.1038/ngeo2257

Reuter, M., Buchwitz, M., Hilker, M., Heymann, J., Schneising, O., Pillai, D., … Sawa, Y. (2014). Satellite-inferred European carbon sink larger than expected. Atmospheric Chemistry and Physics14(24), 13739–13753. http://doi.org/10.5194/acp-14-13739-2014

Rudenko, S., Dettmering, D., Esselborn, S., Schöne, T., Förste, C., Lemoine, J.-M., … Neumayer, K.-H. (2014). Influence of time variable geopotential models on precise orbits of altimetry satellites, global and regional mean sea level trends. Advances in Space Research54(1), 92–118. http://doi.org/10.1016/j.asr.2014.03.010

Saux Picart, S., Sathyendranath, S., Dowell, M., Moore, T., & Platt, T. (2014). Remote sensing of assimilation number for marine phytoplankton. Remote Sensing of Environment146, 87–96. http://doi.org/10.1016/j.rse.2013.10.032

Schneising, O., Reuter, M., Buchwitz, M., Heymann, J., Bovensmann, H., & Burrows, J. P. (2014). Terrestrial carbon sink observed from space: variation of growth rates and seasonal cycle amplitudes in response to interannual surface temperature variability. Atmospheric Chemistry and Physics14, 133–141. http://doi.org/10.5194/acp-14-133-2014

Schneising, O., Burrows, J. P., Dickerson, R. R., Buchwitz, M., Reuter, M., & Bovensmann, H. (2014). Remote sensing of fugitive methane emissions from oil and gas production in North American tight geologic formations. Earth’s Future2(10), 548–558. http://doi.org/10.1002/2014EF000265

Sevault, F., Somot, S., Alias, A., Dubois, C., Lebeaupin-Brossier, C., Nabat, P., … Decharme, B. (2014). A fully coupled Mediterranean regional climate system model: design and evaluation of the ocean component for the 1980–2012 period. Tellus A: Dynamic Meteorology and Oceanography66(1), 23967. http://doi.org/10.3402/tellusa.v66.23967

Sioris, C. E., McLinden, C. A., Fioletov, V. E., Adams, C., Zawodny, J. M., Bourassa, A. E., … Degenstein, D. A. (2014). Trend and variability in ozone in the tropical lower stratosphere over 2.5 solar cycles observed by SAGE II and OSIRIS. Atmospheric Chemistry and Physics14(7), 3479–3496. http://doi.org/10.5194/acp-14-3479-2014

Sofieva, V. F., Tamminen, J., Kyrölä, E., Mielonen, T., Veefkind, P., Hassler, B., & Bodeker, G. E. (2014). A novel tropopause-related climatology of ozone profiles. Atmospheric Chemistry and Physics14(1), 283–299. http://doi.org/10.5194/acp-14-283-2014

Stengel, M., Mieruch, S., Jerg, M., Karlsson, K.-G., Scheirer, R., Maddux, B., … Hollmann, R. (2014). The Clouds Climate Change Initiative: The assessment of state of the art cloud property retrieval systems applied to AVHRR heritage measurements. Remote Sensing of Environment.

Szczypta, C., Calvet, J.-C., Maignan, F., Dorigo, W., Baret, F., & Ciais, P. (2014). Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts. Geoscientific Model Development7(3), 931–946. http://doi.org/10.5194/gmd-7-931-2014

Tramblay, Y., Amoussou, E., Dorigo, W., & Mahé, G. (2014). Flood risk under future climate in data sparse regions: Linking extreme value models and flood generating processes. Journal of Hydrology519, 549–558. http://doi.org/10.1016/j.jhydrol.2014.07.052

Valks, P., Hao, N., Gimeno Garcia, S., Loyola, D., Dameris, M., Jöckel, P., & Delcloo, A. (2014). Tropical tropospheric ozone column retrieval for GOME-2. Atmospheric Measurement Techniques7(8), 2513–2530. http://doi.org/10.5194/amt-7-2513-2014

van Peet, J. C. A., van der A, R. J., Tuinder, O. N. E., Wolfram, E., Salvador, J., Levelt, P. F., & Kelder, H. M. (2014). Ozone ProfilE Retrieval Algorithm (OPERA) for nadir-looking satellite instruments in the UV–VIS. Atmospheric Measurement Techniques7(3), 859–876. http://doi.org/10.5194/amt-7-859-2014

Wecht, K. J., Jacob, D. J., Sulprizio, M. P., Santoni, G. W., Wofsy, S. C., Parker, R., … Worden, J. (2014). Spatially resolving methane emissions in California: constraints from the CalNex aircraft campaign and from present (GOSAT, TES) and future (TROPOMI, geostationary) satellite observations. Atmospheric Chemistry and Physics14, 8173–8184. http://doi.org/10.5194/acp-14-8173-2014

Yue, C., Ciais, P., Cadule, P., Thonicke, K., Archibald, S., Poulter, B., … Viovy, N. (2014). Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 1: simulating historical global burned area and fire regimes. Geoscientific Model Development7(6), 2747–2767. http://doi.org/10.5194/gmd-7-2747-2014

Zygmuntowska, M., Rampal, P., Ivanova, N., & Smedsrud, L. H. (2014). Uncertainties in Arctic sea ice thickness and volume: new estimates and implications for trends. The Cryosphere8(2), 705–720. http://doi.org/10.5194/tc-8-705-2014

Atmospheric science: Detecting rainfall from the bottom up. (2014, May 14). Nature509(7500), 262–263. http://doi.org/10.1038/509262e

2013

Adams, C., Bourassa, A. E., Bathgate, A. F., McLinden, C. A., Lloyd, N. D., Roth, C. Z., … Degenstein, D. A. (2013). Characterization of Odin-OSIRIS ozone profiles with the SAGE II dataset. Atmospheric Measurement Techniques6(5), 1447–1459. http://doi.org/10.5194/amt-6-1447-2013

Albergel, C., Dorigo, W., Balsamo, G., Muñoz-Sabater, J., de Rosnay, P., Isaksen, L., … Wagner, W. (2013). Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses. Remote Sensing of Environment138, 77–89. Retrieved from http://www.sciencedirect.com/science/article/pii/S0034425713002216

Albergel, C., Dorigo, W., Reichle, R. H., Balsamo, G., de Rosnay, P., Muñoz-Sabater, J., … Wagner, W. (2013). Skill and Global Trend Analysis of Soil Moisture from Reanalyses and Microwave Remote Sensing. Journal of Hydrometeorology14(4), 1259–1277. http://doi.org/10.1175/JHM-D-12-0161.1

Basu, S., Guerlet, S., Butz, A., Houweling, S., Hasekamp, O., Aben, I., … Worthy, D. (2013). Global CO2 fluxes estimated from GOSAT retrievals of total column CO2Atmospheric Chemistry and Physics13(17), 8695–8717. http://doi.org/10.5194/acp-13-8695-2013

Bauer-Marschallinger, B., Dorigo, W. A., Wagner, W., & van Dijk, A. I. J. M. (2013). How Oceanic Oscillation Drives Soil Moisture Variations over Mainland Australia: An Analysis of 32 Years of Satellite Observations. Journal of Climate, 130730135426008. http://doi.org/10.1175/JCLI-D-13-00149.1

Bhambri, R., Bolch, T., Kawishwar, P., Dobhal, D. P., Srivastava, D., & Pratap, B. (2013). Heterogeneity in glacier response in the upper Shyok valley, northeast Karakoram. The Cryosphere7(5), 1385–1398. http://doi.org/10.5194/tc-7-1385-2013

Bolch, T., Sandberg Sørensen, L., Simonsen, S. B., Mölg, N., Machguth, H., Rastner, P., & Paul, F. (2013). Mass loss of Greenland’s glaciers and ice caps 2003-2008 revealed from ICESat laser altimetry data. Geophysical Research Letters40(5), 875–881. http://doi.org/10.1002/grl.50270

Brewin, R. J. W., Raitsos, D. E., Pradhan, Y., & Hoteit, I. (2013). Comparison of chlorophyll in the Red Sea derived from MODIS-Aqua and in vivo fluorescence. Remote Sensing of Environment136, 218–224. Retrieved from http://www.sciencedirect.com/science/article/pii/S003442571300151X

Brewin, R. J. W., Sathyendranath, S., Müller, D., Brockmann, C., Deschamps, P.-Y., Devred, E., … White, G. N. (2013). The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms. Remote Sensing of Environment. Retrieved from http://www.sciencedirect.com/science/article/pii/S0034425713003519

Brotas, V., Brewin, R. J. W., Sá, C., Brito, A. C., Silva, A., Mendes, C. R., … Sathyendranath, S. (2013). Deriving phytoplankton size classes from satellite data: Validation along a trophic gradient in the eastern Atlantic Ocean. Remote Sensing of Environment134, 66–77. Retrieved from http://www.sciencedirect.com/science/article/pii/S0034425713000540

Buchwitz, M., Reuter, M., Schneising, O., Boesch, H., Guerlet, S., Dils, B., … Yoshida, Y. (2013). The Greenhouse Gas Climate Change Initiative (GHG-CCI): Comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets. Remote Sensing of Environment. Retrieved from http://www.sciencedirect.com/science/article/pii/S0034425713003520

Chevallier, F., & O’Dell, C. W. (2013). Error statistics of Bayesian CO 2 flux inversion schemes as seen from GOSAT. Geophysical Research Letters40(6), 1252–1256. http://doi.org/10.1002/grl.50228

Crevoisier, C., Nobileau, D., Armante, R., Crépeau, L., Machida, T., Sawa, Y., … Chédin, A. (2013). The 2007–2011 evolution of tropical methane in the mid-troposphere as seen from space by MetOp-A/IASI. Atmospheric Chemistry and Physics13(8), 4279–4289. http://doi.org/10.5194/acp-13-4279-2013

Dameris, M., & Jöckel, P. (2013). Numerical Modeling of Climate-Chemistry Connections: Recent Developments and Future Challenges. Atmosphere4(2), 132–156. http://doi.org/10.3390/atmos4020132

De Jeu, R. M. (2013). Global Climate, Hydrological Cycle Soil Mositure in “State of the Climate in 2012.” Bull. Amer. Meteor94(8), S121–S123.

Fraser, A., Palmer, P. I., Feng, L., Boesch, H., Cogan, A., Parker, R., … Weiss, R. F. (2013). Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements. Atmospheric Chemistry and Physics13(11), 5697–5713. http://doi.org/10.5194/acp-13-5697-2013

Gamba, P., & Lisini, G. (2013). Fast and Efficient Urban Extent Extraction Using ASAR Wide Swath Mode Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing6(5), 2184–2195. http://doi.org/10.1109/JSTARS.2012.2235410

Gardelle, J., Berthier, E., Arnaud, Y., & Kääb, A. (2013). Region-wide glacier mass balances over the Pamir-Karakoram-Himalaya during 1999–2011. The Cryosphere7(4), 1263–1286. http://doi.org/10.5194/tc-7-1263-2013

Gardner, A. S., Moholdt, G., Cogley, J. G., Wouters, B., Arendt, A. A., Wahr, J., … Paul, F. (2013). A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009. Science (New York, N.Y.)340(6134), 852–7. http://doi.org/10.1126/science.1234532

Griesfeller,  Alexandra, Lahoz,  William A., Svendby,  Tove M., Haugen,  Lars E., Wagner,  Wolfgang, Dorigo,  Wouter, … de Jeu,  Richard A. M. (2013). Evaluation of SMOS and ASCAT soil moisture products over Norway using ground-based in situ observations. EGU General Assembly 2013. Retrieved from http://adsabs.harvard.edu/abs/2013EGUGA..15.3897G

Guerlet, S., Basu, S., Butz, A., Krol, M., Hahne, P., Houweling, S., … Aben, I. (2013). Reduced carbon uptake during the 2010 Northern Hemisphere summer from GOSAT. Geophysical Research Letters40(10), 2378–2383. http://doi.org/10.1002/grl.50402

Guerlet, S., Butz, A., Schepers, D., Basu, S., Hasekamp, O. P., Kuze, A., … Aben, I. (2013). Impact of aerosol and thin cirrus on retrieving and validating XCO 2 from GOSAT shortwave infrared measurements. Journal of Geophysical Research: Atmospheres118(10), 4887–4905. http://doi.org/10.1002/jgrd.50332

Hantson, S., Padilla, M., Corti, D., & Chuvieco, E. (2013). Strengths and weaknesses of MODIS hotspots to characterize global fire occurrence. Remote Sensing of Environment131, 152–159. Retrieved from http://www.sciencedirect.com/science/article/pii/S0034425712004610

Henry, O., Ablain, M., Meyssignac, B., Cazenave, A., Masters, D., Nerem, S., & Garric, G. (2013). Effect of the processing methodology on satellite altimetry-based global mean sea level rise over the Jason-1 operating period. Journal of Geodesy88(4), 351–361. http://doi.org/10.1007/s00190-013-0687-3

Hollmann, R., Merchant, C. J., Saunders, R., Downy, C., Buchwitz, M., Cazenave, A., … Wagner, W. (2013). The ESA Climate Change Initiative: satellite data records for essential climate variables. Bulletin of the American Meteorological Society, 130313072241002. http://doi.org/10.1175/BAMS-D-11-00254.1

Holzer-Popp, T., de Leeuw, G., Griesfeller, J., Martynenko, D., Klüser, L., Bevan, S., … Pinnock, S. (2013). Aerosol retrieval experiments in the ESA Aerosol_cci project. Atmospheric Measurement Techniques6(8), 1919–1957. http://doi.org/10.5194/amt-6-1919-2013

Kolmonen, P., Sundström, A.-M., Sogacheva, L., Rodriguez, E., Virtanen, T., & de Leeuw, G. (2013). Uncertainty characterization of AOD for the AATSR dual and single view retrieval algorithms. Atmospheric Measurement Techniques Discussions6(2), 4039–4075. http://doi.org/10.5194/amtd-6-4039-2013

Kyrölä, E., Laine, M., Sofieva, V., Tamminen, J., Päivärinta, S.-M., Tukiainen, S., … Thomason, L. (2013). Combined SAGE II–GOMOS ozone profile data set for 1984–2011 and trend analysis of the vertical distribution of ozone. Atmospheric Chemistry and Physics13(21), 10645–10658. http://doi.org/10.5194/acp-13-10645-2013

Lahoz, W. A., & De Lannoy, G. J. M. (2013). Closing the Gaps in Our Knowledge of the Hydrological Cycle over Land: Conceptual Problems. Surveys in Geophysics, 1–38. http://doi.org/10.1007/s10712-013-9221-7

Lean, K., Saunders, R. W., Lean, K., & Saunders, R. W. (2013). Validation of the ATSR Reprocessing for Climate (ARC) Dataset Using Data from Drifting Buoys and a Three-Way Error Analysis. Journal of Climate26(13), 4758–4772. http://doi.org/10.1175/JCLI-D-12-00206.1

Lerot, C., Van Roozendael, M., Spurr, R., Loyola, D., Coldewey-Egbers, M., Kochenova, S., … Zehner, C. (2013). Homogenized total ozone data records from the European sensors GOME/ERS-2, SCIAMACHY/Envisat and GOME-2/MetOp-A. Journal of Geophysical Research: Atmospheres, n/a-n/a. http://doi.org/10.1002/2013JD020831

Levinsen, J. F., Khvorostovsky, K., Ticconi, F., Shepherd, A., Forsberg, R., Sørensen, L. S., … Kleinherenbrink, M. (2013). ESA’s Ice Sheets CCI: validation and inter-comparison of surface elevation changes derived from laser and radar altimetry over Jakobshavn Isbræ, Greenland – Round Robin results. The Cryosphere Discussions7(6), 5433–5460. http://doi.org/10.5194/tcd-7-5433-2013

Li, Y., Xue, Y., de Leeuw, G., Li, C., Yang, L., Hou, T., & Marir, F. (2013). Retrieval of aerosol optical depth and surface reflectance over land from NOAA AVHRR data. Remote Sensing of Environment133, 1–20. http://doi.org/10.1016/j.rse.2013.01.020

Loew, A., Stacke, T., Dorigo, W., de Jeu, R., & Hagemann, S. (2013). Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies. Hydrology and Earth System Sciences17(9), 3523–3542. http://doi.org/10.5194/hess-17-3523-2013

Loew, A. (2013). Terrestrial satellite records for climate studies: how long is long enough? A test case for the Sahel. Theoretical and Applied Climatology, 1–14. http://doi.org/10.1007/s00704-013-0880-6

Meirink, J. F., Roebeling, R. A., & Stammes, P. (2013). Inter-calibration of polar imager solar channels using SEVIRI. Atmospheric Measurement Techniques6(9), 2495–2508. http://doi.org/10.5194/amt-6-2495-2013

Melin, F., Zibordi, G., & Holben, B. N. (2013). Assessment of the Aerosol Products From the SeaWiFS and MODIS Ocean-Color Missions. IEEE Geoscience and Remote Sensing Letters10(5), 1185–1189. http://doi.org/10.1109/LGRS.2012.2235408

Miralles, D. G., van den Berg, M. J., Gash, J. H., Parinussa, R. M., de Jeu, R. A. M., Beck, H. E., … Johannes Dolman, A. (2013). El Niño–La Niña cycle and recent trends in continental evaporation. Nature Climate Changeadvance on. http://doi.org/10.1038/nclimate2068

Monteil, G., Houweling, S., Butz, A., Guerlet, S., Schepers, D., Hasekamp, O., … Röckmann, T. (2013). Comparison of CH 4 inversions based on 15 months of GOSAT and SCIAMACHY observations. Journal of Geophysical Research: Atmospheres118(20), 11,807-11,823. http://doi.org/10.1002/2013JD019760

Muñoz, A. A., Barichivich, J., Christie, D. A., Dorigo, W., Sauchyn, D., González-Reyes, Á., … González, M. E. (2013). Patterns and drivers of Araucaria araucana forest growth along a biophysical gradient in the northern Patagonian Andes: Linking tree rings with satellite observations of soil moisture. Austral Ecology, n/a-n/a. http://doi.org/10.1111/aec.12054

Nuth, C., Kohler, J., König, M., von Deschwanden, A., Hagen, J. O., Kääb, A., … Pettersson, R. (2013). Decadal changes from a multi-temporal glacier inventory of Svalbard. The Cryosphere7(5), 1603–1621. http://doi.org/10.5194/tc-7-1603-2013

Ottlé, C., Lescure, J., Maignan, F., Poulter, B., Wang, T., & Delbart, N. (2013). Use of various remote sensing land cover products for plant functional type mapping over Siberia. Earth System Science Data5(2), 331–348. http://doi.org/10.5194/essd-5-331-2013

Parinussa, R. (2013). Uncertainty characterisation in remotely sensed soil moisture. VU University Amsterdam). Retrieved from http://dare.ubvu.vu.nl/bitstream/handle/1871/41480/dissertation.pdf?sequ...

Parinussa, R. M., Yilmaz, M. T., Anderson, M. C., Hain, C. R., & de Jeu, R. A. M. (2013). An intercomparison of remotely sensed soil moisture products at various spatial scales over the Iberian Peninsula. Hydrological Processes, n/a-n/a. http://doi.org/10.1002/hyp.9975

Paul, F., Barrand, N., Baumann, S., Berthier, E., Bolch, T., Casey, K., … Winsvold, S. (2013). On the accuracy of glacier outlines derived from remote-sensing data. Annals of Glaciology. http://doi.org/10.3189/2013AoG63A296 <http://dx.doi.org/10.3189/2013AoG63A296>

Paul, F., Bolch, T., Kääb, A., Nagler, T., Nuth, C., Scharrer, K., … Van Niel, T. (2013). The Glaciers Climate Change Initiative: Algorithms for creating glacier area, elevation change and velocity products. Remote Sensing of Environment. Retrieved from http://www.sciencedirect.com/science/article/pii/S0034425713003532

Pieczonka, T., Bolch, T., Junfeng, W., & Shiyin, L. (2013). Heterogeneous mass loss of glaciers in the Aksu-Tarim Catchment (Central Tien Shan) revealed by 1976 KH-9 Hexagon and 2009 SPOT-5 stereo imagery. Remote Sensing of Environment130, 233–244. Retrieved from http://www.sciencedirect.com/science/article/pii/S003442571200452X

Rahpoe, N., von Savigny, C., Weber, M., Rozanov, A. V., Bovensmann, H., & Burrows, J. P. (2013). Error budget analysis of SCIAMACHY limb ozone profile retrievals using the SCIATRAN model. Atmospheric Measurement Techniques6(10), 2825–2837. http://doi.org/10.5194/amt-6-2825-2013

Raitsos, D. E., Pradhan, Y., Brewin, R. J. W., Stenchikov, G., & Hoteit, I. (2013). Remote sensing the phytoplankton seasonal succession of the Red Sea. PloS One8(6), e64909. http://doi.org/10.1371/journal.pone.0064909

Rastner, P., Bolch, T., Notarnicola, C., & Paul, F. (2013). A Comparison of Pixel- and Object-Based Glacier Classification With Optical Satellite Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPP(99), 1–10. http://doi.org/10.1109/JSTARS.2013.2274668

Reuter, M., Bösch, H., Bovensmann, H., Bril, A., Buchwitz, M., Butz, A., … Yoshida, Y. (2013). A joint effort to deliver satellite retrieved atmospheric CO2 concentrations for surface flux inversions: the ensemble median algorithm EMMA. Atmospheric Chemistry and Physics13(4), 1771–1780. http://doi.org/10.5194/acp-13-1771-2013

Richards, N. A. D., Arnold, S. R., Chipperfield, M. P., Miles, G., Rap, A., Siddans, R., … Hollaway, M. J. (2013). The Mediterranean summertime ozone maximum: global emission sensitivities and radiative impacts. Atmospheric Chemistry and Physics13(5), 2331–2345. http://doi.org/10.5194/acp-13-2331-2013

Ross, A. N., Wooster, M. J., Boesch, H., & Parker, R. (2013). First satellite measurements of carbon dioxide and methane emission ratios in wildfire plumes. Geophysical Research Letters40(15), 4098–4102. http://doi.org/10.1002/grl.50733

Santoro, M., & Wegmuller, U. (2013). Multi-temporal Synthetic Aperture Radar Metrics Applied to Map Open Water Bodies. IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPP(99), 1–14. http://doi.org/10.1109/JSTARS.2013.2289301

Schneising, O., Heymann, J., Buchwitz, M., Reuter, M., Bovensmann, H., & Burrows, J. P. (2013). Anthropogenic carbon dioxide source areas observed from space: assessment of regional enhancements and trends. Atmospheric Chemistry and Physics13(5), 2445–2454. http://doi.org/10.5194/acp-13-2445-2013

Sofieva, V. F., Rahpoe, N., Tamminen, J., Kyrölä, E., Kalakoski, N., Weber, M., … Zehner, C. (2013). Harmonized dataset of ozone profiles from satellite limb and occultation measurements. Earth System Science Data5(2), 349–363. http://doi.org/10.5194/essd-5-349-2013

Sonkaew, T., von Savigny, C., Eichmann, K.-U., Weber, M., Rozanov, A., Bovensmann, H., … Grooß, J.-U. (2013). Chemical ozone losses in Arctic and Antarctic polar winter/spring season derived from SCIAMACHY limb measurements 2002–2009. Atmospheric Chemistry and Physics13(4), 1809–1835. http://doi.org/10.5194/acp-13-1809-2013

Spurr, R., Natraj, V., Lerot, C., Van Roozendael, M., & Loyola, D. (2013). Linearization of the Principal Component Analysis method for radiative transfer acceleration: Application to retrieval algorithms and sensitivity studies. Journal of Quantitative Spectroscopy and Radiative Transfer125, 1–17. Retrieved from http://www.sciencedirect.com/science/article/pii/S0022407313001362

Sussmann, R., Ostler, A., Forster, F., Rettinger, M., Deutscher, N. M., Griffith, D. W. T., … Patra, P. K. (2013). First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change. Atmospheric Measurement Techniques6(2), 397–418. http://doi.org/10.5194/amt-6-397-2013

2012

Ablain, M., Philipps, S., Urvoy, M., Tran, N., & Picot, N. (2012). Detection of Long-Term Instabilities on Altimeter Backscatter Coefficient Thanks to Wind Speed Data Comparisons from Altimeters and Models. Marine Geodesy35(sup1), 258–275. http://doi.org/10.1080/01490419.2012.718675

Bolch, T., Kulkarni, A., Kääb, A., Huggel, C., Paul, F., Cogley, J. G., … Stoffel, M. (2012). The state and fate of Himalayan glaciers. Science (New York, N.Y.)336(6079), 310–4. http://doi.org/10.1126/science.1215828

Bontemps, S., Herold, M., Kooistra, L., van Groenestijn, A., Hartley, A., Arino, O., … Defourny, P. (2012). Revisiting land cover observation to address the needs of the climate modeling community. Biogeosciences9(6), 2145–2157. http://doi.org/10.5194/bg-9-2145-2012

Braesicke, P., See Hai, O., & Abu Samah, A. (2012). Properties of strong off-shore Borneo vortices: a composite analysis of flow pattern and composition as captured by ERA-Interim. Atmospheric Science Letters13(2), 128–132. http://doi.org/10.1002/asl.372

Brewin, R. J. W., Dall’Olmo, G., Sathyendranath, S., & Hardman-Mountford, N. J. (2012). Particle backscattering as a function of chlorophyll and phytoplankton size structure in the open-ocean. Optics Express20(16), 17632–52. http://doi.org/10.1364/OE.20.017632

Cai, D., Dameris, M., Garny, H., & Runde, T. (2012). Implications of all season Arctic sea-ice anomalies on the stratosphere. Atmospheric Chemistry and Physics12(24), 11819–11831. http://doi.org/10.5194/acp-12-11819-2012

Cazenave, A., Henry, O., Munier, S., Delcroix, T., Gordon, A. L., Meyssignac, B., … Becker, M. (2012). Estimating ENSO Influence on the Global Mean Sea Level, 1993–2010. Marine Geodesy35(sup1), 82–97. http://doi.org/10.1080/01490419.2012.718209

Dameris, M., & Loyola, D. (2012). Recent and Future Evolution of the Stratospheric Ozone Layer. In U. Schumann (Ed.), Atmospheric Physics. Research Topics in Aerospace (pp. 747–761). Berlin, Heidelberg: Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-642-30183-4

de Jeu, R. A. M., Dorigo, W. A., Parinussa, R. M., Wagner, W., & Chung, D. (2012). Soil Moisture in: “State of the Climate in 2011.” Bull. Amer. Meteor. Soc., 93(7), S30-34. Retrieved from http://www.ncdc.noaa.gov/bams-state-of-the-climate/2011.php

Debella-Gilo, M., & Kääb, A. (2012). Locally adaptive template sizes for matching repeat images of Earth surface mass movements. ISPRS Journal of Photogrammetry and Remote Sensing69, 10–28. Retrieved from http://www.sciencedirect.com/science/article/pii/S092427161200038X

Debella-Gilo, M., & Kääb, A. (2012). Measurement of Surface Displacement and Deformation of Mass Movements Using Least Squares Matching of Repeat High Resolution Satellite and Aerial Images. Remote Sensing4(12), 43–67. http://doi.org/10.3390/rs4010043

Dorigo, W., de Jeu, R., Chung, D., Parinussa, R., Liu, Y., Wagner, W., & Fernández-Prieto, D. (2012). Evaluating global trends (1988-2010) in harmonized multi-satellite surface soil moisture. Geophysical Research Letters39(18), n/a-n/a. http://doi.org/10.1029/2012GL052988

Ford, D. A., Edwards, K. P., Lea, D., Barciela, R. M., Martin, M. J., & Demaria, J. (2012). Assimilating GlobColour ocean colour data into a pre-operational physical-biogeochemical model. Ocean Science8(5), 751–771. http://doi.org/10.5194/os-8-751-2012

Garcia-Soto, C., Vazquez-Cuervo, J., Clemente-Colón, P., Hernandez, F., Brewin, R. J. W., Hirata, T., … Barlow, R. (2012). The influence of the Indian Ocean Dipole on interannual variations in phytoplankton size structure as revealed by Earth Observation. Deep Sea Research Part II: Topical Studies in Oceanography77, 117–127. Retrieved from http://www.sciencedirect.com/science/article/pii/S0967064512000574

Heid, T., & Kääb, A. (2012). Repeat optical satellite images reveal widespread and long term decrease in land-terminating glacier speeds. The Cryosphere6(2), 467–478. http://doi.org/10.5194/tc-6-467-2012

Heid, T., & Kääb, A. (2012). Evaluation of existing image matching methods for deriving glacier surface displacements globally from optical satellite imagery. Remote Sensing of Environment118, 339–355. Retrieved from http://www.sciencedirect.com/science/article/pii/S0034425711004214

Heymann, J., Bovensmann, H., Buchwitz, M., Burrows, J. P., Deutscher, N. M., Notholt, J., … Warneke, T. (2012). SCIAMACHY WFM-DOAS XCO2: reduction of scattering related errors. Atmospheric Measurement Techniques,5(10), 2375–2390. http://doi.org/10.5194/amt-5-2375-2012

Heymann, J., Schneising, O., Reuter, M., Buchwitz, M., Rozanov, V. V., Velazco, V. A., … Burrows, J. P. (2012). SCIAMACHY WFM-DOAS XCO2: comparison with CarbonTracker XCO2 focusing on aerosols and thin clouds. Atmospheric Measurement Techniques5(8), 1935–1952. http://doi.org/10.5194/amt-5-1935-2012

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