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Generation of the ESA CCI soil moisture product (citation of these papers is compulsory when you use the ESA CCI product)

Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014.

Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436, doi:10.5194/hess-15-425-2011.

Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012) Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321.


Special Issue

International Journal of Applied Earth Observation and Geoinformation. Volume 45, Part B, Pages 107-244 (March 2016) Advances in the Validation and Application of Remotely Sensed Soil Moisture - Part 1 Edited by Wouter A. Dorigo and Richard A.M. de Jeu.

International Journal of Applied Earth Observation and Geoinformation. Volume 48, Pages 1-174 (June 2016) Advances in the Validation and Application of Remotely Sensed Soil Moisture - Part 2 Edited by Wouter A. Dorigo and Richard A.M. de Jeu.


New since 2017

Shrivastava, S., Kar, S.C. & Sharma, A.R. (2017) Intraseasonal Variability of Summer Monsoon Rainfall and Droughts over Central India. Pure Appl. Geophys. doi:10.1007/s00024-017-1498-x

Lauer, A., Eyring, V., Righi, M., Buchwitz, M., Defourny, P., Evaldsson, M., Friedlingstein, P., de Jeu, R., de Leeuw, G., Loew, A., Merchant, C. J., Müller, B., Popp, T., Reuter, M., Sandven, S., Senftleben, D., Stengel, M., van Roozendael, M., Wenzel, S. and Willen, U. (2017) Benchmarking CMIP5 models with a subset of ESA CCI Phase 2 data using the ESMValTool. Remote Sensing of Environment. ISSN 0034-4257. DOI: 10.1016/j.rse.2017.01.007.

Mao, Yun, et al. (2017) Spatio-temporal analysis of drought in a typical plain region based on the soil moisture anomaly percentage index. Science of The Total Environment 576: 752-765. doi:

Lauer, A., Eyring, V., Righi, M., Buchwitz, M., Defourny, P., Evaldsson, M., ... & Merchant, C. J. (2017). Benchmarking CMIP5 models with a subset of ESA CCI Phase 2 data using the ESMValTool. Remote Sensing of Environment. doi:


Validation of the ESA CCI soil moisture product

Albergel, C., Dorigo, W., Balsamo, G., Muñoz-Sabater, J., De Rosnay, P., Isaksen, L., Brocca, L., De Jeu, R. & Wagner, W. (2013a). Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses, Remote Sensing of Environment, 138, 77-89. doi: 10.1016/j.rse.2013.07.009.

Albergel, C., Dorigo, W., Reichle, R.H., Balsamo, G., De Rosnay, P., Muñoz-Sabater, J., Isaksen, L., De Jeu, R. & Wagner, W. (2013b). Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing, Journal of Hydrometeorology. doi: 10.1175/JHM-D-12-0161.1.

Chakravorty, A., Chahar, B. R., Sharma, O. P., & Dhanya, C. T. (2016). A regional scale performance evaluation of SMOS and ESA-CCI soil moisture products over India with simulated soil moisture from MERRA-Land. Remote Sensing of Environment, 186, 514-527.

Ciabatta, L., Massari, C., Brocca, L., Reimer, C., Hann, S., Dorigo, W., & Wagner, W. (2016). Using Python® language for the validation of the CCI soil moisture products via SM2RAIN (No. e2131v1). PeerJ Preprints.

Cui, Y., Long, D., Hong, Y., Zeng, C., Zhou, J., Han, Z., ... & Wan, W. (2016). Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau. Journal of Hydrology.

Kumar, S. V., Peters-Lidard, C. D., Santanello, J. A., Reichle, R. H., Draper, C. S., Koster, R. D., ... & Jasinski, M. F. (2015). Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes. Hydrology and Earth System Sciences, 19(11), 4463. doi: 10.5194/hess-19-4463-2015.

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

Massari, C., Brocca, L., Tarpanelli, A., Ciabatta, L., Camici, S., Moramarco, T., Dorigo, W., & Wagner, W. (2015). Assessing the Potential of CCI Soil Moisture Products for data assimilation in rainfall-runoff modelling: A Case Study for the Niger River. In: Earth Observation for Water Cycle Science 2015. Frascati, Italy. Conference paper.

McNally, A., Shukla, S., Arsenault, K. R., Wang, S., Peters-Lidard, C. D., & Verdin, J. P. (2016). Evaluating ESA CCI soil moisture in East Africa. International Journal of Applied Earth Observation and Geoinformation, 48, 96-109. doi: 10.1016/j.jag.2016.01.001.

Peng, J., Niesel, J., Loew, A., Zhang, S., Wang, J. (2015). Evaluation of Satellite and Reanalysis Soil Moisture Products over Southwest China Using Ground-Based Measurements. Remote Sensing, 7, 15729-15747. doi: 10.3390/rs71115729.

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 Sensing, 2015, Vol. 7(11):15388-15423. doi:10.3390/rs71115388.

Pratola, C., Barrett, B., Gruber, A., Kiely, G & Dwyer, E., (2014). Evaluation of a Global Soil Moisture Product from Finer Spatial Resolution SAR Data and Ground Measurements at Irish Sites. Remote Sensing, 6, 8190-8219. doi:10.3390/rs6098190.

Shen, X., An, R., Quaye‐Ballard, J. A., Zhang, L., & Wang, Z. (2016). Evaluation of the European Space Agency Climate Change Initiative Soil Moisture Product over China Using Variance Reduction Factor. JAWRA Journal of the American Water Resources Association. doi: 10.1111/1752-1688.12478.

Spennemann, P.C., Rivera, J.A., Celeste Saulo, A., & Penalba, O.C. (2015). A comparison of GLDAS soil moisture anomalies against standardized precipitation index and multisatellite estimations over South America. Journal of Hydrometeorology, 16, 158-171. doi:


Analyses and applications using the ESA CCI soil moisture product

Abera, W., Formetta, G., Brocca, L., and Rigon, R. (2016). Water budget modelling of the Upper Blue Nile basin using the JGrass-NewAge model system and satellite data, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-290.

Allam, M. M., Figueroa, A. J., McLaughlin, D. B., Eltahir, E. A. B. (2016). Estimation of evaporation over the upper Blue Nile basin by combining observations from satellites and river flow gauges. Water Resources Research. An AGU Journal, doi: 10.1002/2015WR017251.

Al-Yaari, A., Wigneron, J. P., Kerr, Y., De Jeu, R., Rodriguez-Fernandez, N., Van Der Schalie, R., Al Bitar, A., Mialon, A., Richaume, P., Dolman, A. & Ducharne, A. (2016). Testing regression equations to derive long-term global soil moisture datasets from passive microwave observations. Remote Sensing of Environment, 180, 453-464.

An, R., Zhang, L., Wang, Z., Quaye-Ballard, J. A., You, J., Shen, X., Gao, W., Huang, L., Zhao, Y. & Ke, Z. (2016). Validation of the ESA CCI soil moisture product in China. International Journal of Applied Earth Observation and Geoinformation, 48, 28-36.

Barichivich, J., Briffa, K.R., Myneni, R., Schrier, G., Dorigo, W., Tucker, C.J., Osborn, T.J. & Melvin, T.M. (2014). Temperature and Snow-Mediated Moisture Controls of Summer Photosynthetic Activity in Northern Terrestrial Ecosystems between 1982 and 2011. Remote Sensing, 2014, 6(4), 1390-1431. doi: 10.3390/rs6021390.

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 (Editor), Satellite Soil Moisture Retrievals: Techniques & Applications. doi: 10.1016/B978-0-12-803388-3.00011-5.

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 Environment, 152, 109-124. doi:

Bauer-Marschallinger, B., Dorigo, W., Wagner, W., Van Dijk, A.(2013). How oceanic oscillation drives soil moisture variations over mainland Australia: An analysis of 32 years of satellite observations, Journal of Climate. doi: 10.1175/jcli-d-13-00149.1.

Carrão, H., Russo, S., Sepulcre-Canto, G., & Barbosa, P. (2016). An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data. International Journal of Applied Earth Observation and Geoinformation, 48, 74-84. doi:

Casagrande, E., Mueller, B., Miralles, D. G., Entekhabi, D., & Molini, A. (2015). Wavelet correlations to reveal multiscale coupling in geophysical systems. Journal of Geophysical Research: Atmospheres, 120(15), 7555-7572. doi: 10.1002/2015JD023265.

Chen T, De Jeu, R., Liu, Y., Vd Werf, G. & Dolman, A. (2014). Using satellite based soil moisture to quantify the water driven variability, NDVI: a case study over Mainland Australia.  Remote Sensing of Environment, 140, 330-338. doi:

Chen, T., McVicar, T. R., Wang, G., Chen, X., de Jeu, R. A., Liu, Y. Y., Shen, H., Zhang, F. & Dolman, A. J. (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 Sensing, 8(5), 428. doi:10.3390/rs8050428.

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 Geoinformation, 48, 163-17. doi: 10.1016/j.jag.2015.10.004.

Das, S., & Maity, R. (2015). Potential of Probabilistic Hydrometeorological Approach for Precipitation-Based Soil Moisture Estimation. J. Hydrol. Eng., 20(4), 04014056.

De Jeu, R., Kerr, Y., Wigneron, J. P., Rodriguez-Fernandez, N., Al-Yaari, A., van der Schalie, R., Dolman, H., Drusch, M., Mecklenburg, S. (2015). The Integration of SMOS Soil Moisture in a Consistent Soil Moisture Climate Record, Geographical Research Abstracts, Vol. 17, EGU2015-7286.

De Jeu, R.A.M., Dorigo, W.A., Parinussa, R.M., Wagner, W. & Chung, D. (2012a). Global Climate. Soil Moisture In: State of the Climate in 2011. Bull. Amer. Meteor. Soc., 93 (7), S30-S34. doi:

De Jeu, R.A.M., Dorigo, W.A., Parinussa, R.M., Wagner, W., Liu, Y.Y., Chung, D. & Fernandez-Prieto (2012b). Building a climate record of soil moisture from historical satellite observations In: State of the Climate in 2011. Bull. Amer. Meteor. Soc., 93 (7), S32-S33.

De Jeu, R., Dorigo, W., Wagner, W., & Liu, Y. (2011). Global Climate. Soil Moisture In: State of the Climate in 2010. Bulletin of the American Meteorological Society, 92, S52-S53. DOI:


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 Geoscience and Remote Sensing, IEEE Transactions, vol.53, no.9, p. 5148-5159. doi: 10.1109/TGRS.2015.2417653.

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. Hydrol. Process., 28: 3752–3760., doi: 10.1002/hyp.9925.

Dorigo, W., Chung, D., Gruber, A., Hahn, S., Mistelbauer, T., Parinussa, R.M., Paulik, C., Reimer, C., van der Schalie, R., de Jeu, R.A.M., Wagner, W. (2016): Soil Moisture .In: State of the Climate in 2015. Bull. Amer. Meteor. Soc., 97 (8), S31-32. doi: 10.1016/j.jag.2016.02.007.

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. Bulletin of the American Meteorological Society, 95 (7), S25-S26. doi:

Dorigo, W., Reimer, C., Chung, D., Parinussa, R.M., Melzer, T., Wagner, W., De Jeu, R.A.M. & Kidd., R. (2015). Soil Moisture In: State of the Climate in 2014. Bulletin of the American Meteorological Society, 96 (7), S28-29. doi:

Du, E., Di Vittorio, A., & Collins, W. D. (2016). Evaluation of hydrologic components of community land model 4 and bias identification. International Journal of Applied Earth Observation and Geoinformation, 48, 5-16. doi:

Du, J., Kimball, J. S., & Jones, L. A. (2016). Passive Microwave Remote Sensing of Soil Moisture Based on Dynamic Vegetation Scattering Properties for AMSR-E. IEEE Transactions on Geoscience and Remote Sensing, 54(1), 597-608. doi: 10.1109/TGRS.2015.2462758.

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 Sciences, 20(10), 4191. doi: 10.5194/hess-20-4191-2016.

Enenkel, M., Steiner, C., Mistelbauer, T., Dorigo, W., Wagner, W., See, L., Atzberger, C., Schneider, S., Rogenhofer, E. (2016). A combined satellite-derived Drought Indicator to support Humanitarian Aid Organizations. Remote Sensing, 8(4), 340. doi: 10.3390/rs8040340.

Fang, L., Hain, C. R., Zhan, X., & Anderson, M. C. (2016). An inter-comparison of soil moisture data products from satellite remote sensing and a land surface model. International Journal of Applied Earth Observation and Geoinformation, 48, 37-50. doi: 10.1016/j.jag.2015.10.006.

Feng, H. (2016). Individual contributions of climate and vegetation change to soil moisture trends across multiple spatial scales. Scientific Reports, 6, 32782. doi: 10.1038/srep32782.

Forkel, M., Dorigo, W., G. Lasslop, I. Teubner, & K. Thonicke (2016). Identifying required model structures to predict global fire activity from satellite and climate data. Geoscientific Model Development. doi: 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 Geoinformation, 45, 235-244. doi: 10.1016/j.jag.2015.08.006.

Griesfeller, A., Lahoz, W. A., de Jeu, R. A. M, Dorigo, W., Haugen, L. E., Svendby, T. M., Wagner, W. (2016).Evaluation of satellite soil moisture products over Norway using ground-based observations. International Journal of Applied Earth Observation and Geoinformation, 45, part B, 155 – 164. doi: 10.1016/j.jag.2015.04.016.

Guillod, B.P., Orlowsky, B., Miralles, D., Teuling, A.J., & Seneviratne, S.I. (2015). Reconciling spatial and temporal soil moisture effects on afternoon rainfall. Nature Communications, 6. doi:10.1038/ncomms7443.

Guillod, B.P., Orlowsky, B., Miralles, D., Teuling, A.J., Blanken, P.D., Buchmann, N., Ciais, P., Ek, M., Findell, K.L., Gentine, P., Lintner, B.R., Scott, R.L., Van den Hurk, B., & I. Seneviratne, S. (2014). Land-surface controls on afternoon precipitation diagnosed from observational data: uncertainties and confounding factors. Atmos. Chem. Phys., 14, 8343-8367. doi:10.5194/acp-14-8343-2014.

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 Environment, 154, 246–252. doi:10.1016/j.rse.2014.08.030.

Ichoku, C., Ellison, L. T., Willmot, K. E., Matsui, T., Dezfuli, A. K., Gatebe, C. K., ... & Okonkwo, C. (2016). Biomass burning, land-cover change, and the hydrological cycle in Northern sub-Saharan Africa. Environmental Research Letters, 11(9), 095005. doi: Environ. Res. Lett. doi:10.1088/1748-9326/11/9/095005.

Kim, S., Y. Y. Liu, F. M. Johnson, R. M. Parinussa & A. Sharma (2015). A global comparison of alternate AMSR2 soil moisture products: Why do they differ? Remote Sensing of the Environment 161 (2015): 43-62. doi:

Klingmüller, K., Pozzer, A., Metzger, S., Stenchikov, G.L., & Lelieveld, J. (2016). Aerosol optical depth trend over the Middle East. Atmospheric Chemistry and Physics, 16, 5063-5073. doi:10.5194/acp-16-5063-2016.

Kolassa, J., Aires, F., Polcher, J., Prigent, C., Jimenez, C., & Pereira, J.M. (2013). Soil moisture retrieval from multi-instrument observations: Information content analysis and retrieval methodology. Journal of Geophysical Research: Atmospheres, 118, 4847–4859. doi: 10.1029/2012JD018150.

Lai, X., Wen, J., Cen, S., Huang, X., Tian, H. & Shi, X. (2015): Spatial and Temporal Soil Moisture Variations over China from Simulations and Observations, Research Article. Advances in Meteorology, vol. 2016. Article ID 529825. doi:

Leng, P., Song, X., Duan, S. B., & Li, Z. L. (2016). A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data. International Journal of Applied Earth Observation and Geoinformation, 52, 338-348.

Leng, P., Song, X., Duan, S. B., & Li, Z. L. (2016). Preliminary validation of two temporal parameter-based soil moisture retrieval models using a satellite product and in situ soil moisture measurements over the REMEDHUS network. International Journal of Remote Sensing, 37(24), 5902-5917.

Liu, Y., Pan, Z., Zhuang, Q., Miralles, D.G., Teuling, A.J., Zhang, T., An, P., Dong, Z., Zhang, J., He, D., Wang, L., Pan, X., Bai, W., & Niyogi, D. (2015). Agriculture intensifies soil moisture decline in Northern China. Scientific Reports, 5, 11261. doi: 10.1038/srep11261.

McNally, A., Husak, G.J., Brown, M., Carroll, M., Funk, C., Yatheendradas, S., Arsenault, K., Peters-Lidard, C., & Verdin, J.P. (2015). Calculating Crop Water Requirement Satisfaction in the West Africa Sahel with Remotely Sensed Soil Moisture. Journal of Hydrometeorology, 16, 295-305. doi:

Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C., & de Arellano, J. V. G. (2014). Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nature Geoscience, 7(5), 345-349. doi: 10.1038/ngeo2141.

Miralles, D. G., Van den Berg, M. K., Gash, J. H., Parinussa, R. M., De Jeu, R. A. M., Beck, H., Holmes, T., Jimenez, C., Verhoest, N., Dorigo, W., Teuling, A. J. & Dolman A. J. (2014). El Nino-La Nina cycle and recent trends in continental evaporation, Nature Climate Change, 4, 122-126. doi: 10.1038/nclimate2068.

Muñoz, A. A., Barichivich, J., Christie, D. A., Dorigo, W., González-Reyes, A., González, M. E., Lara, A., Sauchyn, D., Villalba, R. (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. doi: 10.1111/aec.12054.

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 Letters. 43. doi: 10.1002/2016GL069847.

Nicolai-Shaw, N., Hirschi, M., Mittelbach, H. and Seneviratne, S. I. (2015). Spatial representativeness of soil moisture using in-situ, remote sensing and land-reanalysis data, J. Geophys. Res. Atmos., 120, doi: 10.1002/2015JD023305.

Papagiannopoulou, C., Miralles, D.G., Verhoest, N.E.C., Dorigo, W.A., & Waegeman, W. (2016). A non-linear Granger causality framework to investigate climate–vegetation dynamics. Global Model Development, doi: 10.5194/gmd-2016-266.

Parinussa, R. M., De Jeu, R., Wagner, W., Dorigo, W., Fang, F., Teng, W., & Liu, Y. Y. (2013). Soil Moisture. State of the Climate in 2012. Bulletin of the American Meteorological Society, 94 (8), S24-S25. doi:

Parr, D., & Wang, G. (2014). Hydrological changes in the U.S. Northeast using the Connecticut River Basin as a case study: Part 1. Modeling and analysis of the past. Global and Planetary Change, 122, 208-222. doi:

Peng, J., Loew, A., Zhang, S., Wang, J., Niesel, J. (2015). Spatial Downscaling of Satellite Soil Moisture Data Using a Vegetation Temperature Condition Index. IEEE Trans. On Geosc. And Rem. Sens., 10.1109/TGRS.2015.2462074. doi: 10.1109/TGRS.2015.2462074.

Pieczka, I., Pongrácz, R., André, K. S., Kelemen, F. D., & Bartholy, J. (2016). Sensitivity analysis of different parameterization schemes using RegCM4. 3 for the Carpathian region. Theoretical and Applied Climatology, 1-14. doi: 10.1007/s00704-016-1941-4.

Qiu, J., Gao, Q., Wang, S., & Su, Z. (2016). Comparison of temporal trends from multiple soil moisture data sets and precipitation: The implication of irrigation on regional soil moisture trend. International Journal of Applied Earth Observation and Geoinformation, 48, 17-27. doi: 10.1016/j.jag.2015.11.012.

Rahmani, A., Golian, S., Brocca, L. (2016). Multilayer monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products. International Journal of Applied Earth Observation and Geoinformation, 48, 85-95., doi: 10.1016/j.jag.2015.06.009.

Rodríguez-Fernández, N. J., Kerr, Y. H., 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 Sensing, 8(11), 959. doi: 10.3390/rs8110959.

Sakai, T., Iizumi, T., Okada, M., Nishimori, M., Grünwald, T., Prueger, J., ... & Loubet, B. (2016). Varying applicability of four different satellite-derived soil moisture products to global gridded crop model evaluation. International Journal of Applied Earth Observation and Geoinformation, 48, 51-60. doi: 10.1016/j.jag.2015.09.011.

Santi, E., Paloscia, S., Pettinato, S., & Fontanelli, G. (2016). Application of artificial neural networks for the soil moisture retrieval from active and passive microwave spaceborne sensors. International Journal of Applied Earth Observation and Geoinformation, 48, 61-73. doi: 10.1016/j.jag.2015.08.002.

Sathyanadh, A., Karipot, A., Ranalkar, M., & Prabhakaran, T. (2016). Evaluation of Soil Moisture Data Products over Indian Region and Analysis of Spatiotemporal Characteristics with Respect to Monsoon Rainfall. Journal of Hydrology., doi: 10.1016/j.jhydrol.2016.08.040.

Schellekens, J., Dutra, E., Balsamo, G., Dijk, A.v., Weiland, F.S., Minvielle, M., Calvet, J.-C., Decharme, B., Eisner, S., Fink, G., Flörke, M., Peßenteiner, S., Beek, R.v., Polcher, J., Beck, H., Torre, A.M.-d.l., Orth, R., Calton, B., Burke, S., Dorigo, W., & Weedon, G.P. (2016). A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset. Earth Syst. Sci. Data. doi: 10.5194/essd-2016-55.

Shrivastava, S., Kar, S. C., & Sharma, A. R. (2016). Soil moisture variations in remotely sensed and reanalysis datasets during weak monsoon conditions over central India and central Myanmar. Theoretical and Applied Climatology, doi: 10.1007/s00704-016-1792-z.

Shukla, S., McNally, A., Husak, G. & Funk, C. (2014). A seasonal agricultural drought forecast system for food-insecure regions of East Africa. Hydrology and Earth System Sciences, 18, 3907-3921. doi: 10.5194/hess-18-3907.

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 Letters. doi: 10.1002/2016GL070458.

Su, C. H., Zhang, J., Gruber, A., Parinussa, R., Ryu, D., Crow, W. T., & Wagner, W. (2016). Error decomposition of nine passive and active microwave satellite soil moisture data sets over Australia. Remote Sensing of Environment, 182, 128-140.

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 Development, 7, 931 – 946. doi: 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 Hydrology, 519, 549-558. doi:

Traore, A. K., Ciais, P., Vuichard, N., Poulter, B., Viovy, N., Guimberteau, M., Jung, M., Myneni, R. & Fisher, J.B. (2014). Evaluation of the ORCHIDEE ecosystem model over Africa against 25 years of satellite-based water and carbon measurements. Journal of Geophysical Research: Biogeosciences, 119. doi: 10.1002/2014JG002638.

Van der Schrier, G., Barichivich, J., Briffa, K. R., & Jones, P. D. (2013). A scPDSI-based global data set of dry and wet spells for 1901–2009. Journal of Geophysical Research: Atmospheres, 118, 4025-4048. doi: 10.1002/jgrd.50355.

Veal, K., Taylor, C., Gallego-Elvira, B., Ghent, D., Harris, P., & Remedios, J. (2016). Relating trends in land surface-air temperature difference to soil moisture and evapotranspiration. In EGU General Assembly Conference Abstracts. Vol. 18, p. 12606.

Wang, S., Mo, X., Liu, S., Lin, Z., Hu, S. (2016). Validation and trend analysis of ECV soil moisture data on cropland in North China Plain during 1981-2010. Int. Journal of Applied Earth Observation and Geoinformation, 48, 110-121. doi: 10.1016/j.jag.2015.10.010.

Xi, X., and I. N. Sokolik (2015). Dust interannual variability and trend in Central Asia from 2000 to 2014 and their climatic linkages, J. Geophys. Res. Atmos., 120, 12,17512,197, doi: 10.1002/2015JD024092.

Zeng, J., Li, Z., Chen, Q., Bi, H., Qui, J. & Zou, P. (2015). Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations. In: Remote Sensing of Environment. Vol. 163. 91-110. doi:

Zeng, Y., Su, Z., Calvet, J. C., Manninen, T., Swinnen, E.& Schulz, J. (2015). Analysis of current validation practices in Europe for space-based climate data records of essential climate variables. Int. J. of Applied Earth Observation and Geoinformation, 42, 150-161. doi:

Zhang, C., Lu, D., Chen, X., Zhang, Y., Maisupova, B., & Tao, Y. (2016). The spatiotemporal patterns of vegetation coverage and biomass of the temperate deserts in Central Asia and their relationships with climate controls. Remote Sensing of Environment, 175, 271-281. doi: org/10.1016/j.rse.2016.01.002.

Zhou, J., Wen, J., Wang, X., Jia, D., & Chen, J. (2016). Analysis of the Qinghai-Xizang Plateau Monsoon Evolution and Its Linkages with Soil Moisture. Remote Sensing, 8(6), 493. doi:10.3390/rs8060493.


Advances in ESA CCI input products

De Jeu, R., Dorigo, W. (2016). On the importance of satellite observed soil moisture. International Journal of Applied Earth Observation and Geoinformation, 45, part B, 107-109, doi: 10.1016/j.jag.2015.10.007.

De Jeu, R., Holmes, T. R. H., Parinussa, R. M. & Owe, M. (2014). A spatially coherent global soil moisture product with improved temporal resolution. Journal of Hydrology, 516, 284-296. doi:

Dorigo, W. A., R. A.M. de Jeu, D. Chung, R. M. Parinussa, Y. Y. Liu, W. Wagner, and D. Fernandez-Prieto (2012), Evaluating global trends (1988-2010) in harmonized multi-satellite surface soil moisture, Geophys. Res. Lett., VOL. 39, L18405, 7 PP. 2012 doi:10.1029/2012GL052988.

Dorigo, W., Bauer-Marschallinger, B., Depoorter, M., & Miralles, D. (2016). Assessing the impact of the 2015/2016 El Niño event on multi-satellite soil moisture over the Southern Hemisphere. EGU General Assembly 2016, held 17-22 April, 2016 in Vienna Austria, p.15476.

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 Geoinformation, 48.

Dorigo, W.A., Gruber, A., De Jeu, R.A.M., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R.M., Kidd, R. (2015). Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sensing of Environment,. doi: 10.1016/j.rse.2014.07.023.

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 Geoinformation, Volume 45, Part B, March 2016, 200–211. doi: 10.1016/j.jag.2015.09.002.

Holmes, TRH, W Crow & RAM de Jeu (2014). Leveraging Microwave Polarization Information for the Calibration of a Land Data Assimilation System, Geophysical Research Letters, Geophys. Res. Lett., 41. doi:10.1002/2014GL061991.

Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A., Fernández-Prieto, D., ... & Verhoest, N. E. (2016). GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev. Discuss, 1-36. doi: 10.5194/gmd-2016-162.

Parinussa, R. M., G. Wang, T. R. H. Holmes, Y.Y. Liu, A.J. Dolman, R. A. M. de Jeu, T. Jiang, P. Zhang & J. Shi (2014). Global surface soil moisture from the Microwave Radiation Imager onboard the Fengyun-3B satellite, International Journal of Remote Sensing, 35:19, 7007-7029. doi: 10.1080/01431161.2014.960622.

Parinussa, R. M., Holmes, T.R.H., & De Jeu, R. A. M. (2012). Soil moisture retrievals from the windSat spaceborne polarimetric microwave radiometer. IEEE Transactions on Geoscience and Remote Sensing, 50, 2683-2694. doi: 10.1109/TGRS.2011.2174643.

Van der Schalie, R., de Jeu, R., Kerr, Y., Wigneron, J. P., Rodríguez-Fernández, N., Al-Yaari, A., Drusch, M., Mecklenburg, S. & Dolman, H. (2016). Evaluation of three different data fusion approaches that uses satellite soil moisture from different passive microwave sensors to construct one consistent climate record. In EGU General Assembly Conference Abstracts (Vol. 18, p. 8520).

Van der Schalie, R., Kerr, Y.H., Wigneron, J.P., Rodríguez-Fernández, N.J., Al-Yaari, A., de Jeu, R.A.M. (2016). Global SMOS Soil Moisture Retrievals from The Land Parameter Retrieval Model, International Journal of Applied Earth Observation and Geoinformation, Volume 45, Part B, Pages 125–134. doi: org/10.1016/j.jag.2015.08.005.


Other publications funded through CCI soil moisture project

Brocca, L., L. Ciabatta, C. Massari, T. Moramarco, S. Hahn, S. Hasenauer, R. Kidd, W. Dorigo, W. Wagner, & V. Levizzani (2014). Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research: Atmospheres 119 (9), 5128. 5141. doi: 10.1002/2014JD021489. – featured as a Nature Research Highlight: (Volume 509 Number 7500) in the Research Highlights section.

Chen, T. (2014). Terrestrial plant productivity and soil moisture constraints. PhD Dissertation VU University Amsterdam.

Ertl, M., Boresch, A., Kianička, J., Sudakov, A., Tomuta, E. (2015). IDCDACS: IDC’s Distributed Application Control System. Poster in: Geophysical Research Abstracts, EGU General Assembly 2015, Vol. 17, EGU2015-3323-2.

Gruber, A., Crow, W., Dorigo, W., Wagner, W. (2015). The potential of 2D Kalman filtering for soil moisture data assimilation, Remote Sensing of Environment, 171, 137-148. doi:

Ikonen, J., Vehviläinen, J., Rautiainen, K., Smolander, T., Lemmetyinen, J., Bircher, S., and Pulliainen, J. (2016). The Sodankylä in situ soil moisture observation network: an example application of ESA CCI soil moisture product evaluation, Geosci. Instrum. Method. Data Syst., 5, 95-108. doi:10.5194/gi-5-95-2016.

Lahoz W.A. & Schneider P. (2014b). Data assimilation: making sense of Earth Observation. Frontiers in Environmental Science. 2:16. doi: 10.3389/fenvs.2014.00016.

Lahoz, W. A., & G. J. M. De Lannoy (2014a). Closing the Gaps in our Knowledge of the Hydrological Cycle over Land: Conceptual Problems. Surveys in Geophysics. doi: 10.1007/s10712-013-9221-7.

Parinussa, R. M. (2013). Uncertainty characterisation in remotely sensed soil moisture, PhD dissertation VU University Amsterdam.

Parinussa, R. M., Holmes, T. R. H., Wanders, N., Dorigo, W. & RAM de Jeu (2015). A Preliminary study towards consistent soil moisture records from AMSR2, Journal of Hydrometeorology 6.2 (2015): 932-947. doi:

Parinussa, R. M., Yilmaz, M., Anderson, M., Hain, C. & De Jeu, R. (2013). An intercomparison of soil moisture observations at various spatial scales over the Iberian Peninsula, Hydrological Processes. doi: 10.1002/hyp.9975.

Yuan, X., Ma, Z., Pan, M., & Shi, C. (2015). Microwave remote sensing of short-term droughts during crop growing seasons. Geophysical Research Letter, 42. doi:10.1002/2015GL064125.