About
The important role of soil moisture for the environment and climate system is well known. Soil moisture influences hydrological and agricultural processes, runoff generation, drought development and many other processes. It also impacts on the climate system through atmospheric feedback. Soil moisture is a source of water for evapotranspiration over the continents, and is involved in both the water and the energy cycles. Soil moisture was recognized as an Essential Climate Variable (ECV) in 2010.
The Soil Moisture_cci project is part of the ESA Programme on Global Monitoring of Essential Climate Variables (ECV), better known as the Climate Change Initiative (CCI), initiated in 2010 and producing an updated soil moisture product every year. The ESA CCI Soil Moisture product has contributed to hundreds of hydrological and climatological studies worldwide, as well as the annual BAMS "State of the Climate" reports.
The CCI Soil Moisture project produces:
- Annually algorithmically updated global climate data record of soil moisture spanning over 40 years.
- 3 separate soil moisture products derived from active, passive and combined (active + passive).
- 14 public releases to date, each updated with new sensors and extended time series.
The dataset ingests soil moisture datasets derived from the sensors listed in the figures below. In particular, the following datasets are used (at ESA CCI SM v08.1):
- ASCAT-A, -B and -C data are generated through the HSAF soil moisture project which can be accessed on the EUMETSAT HSAF soil moisture website. At v08.1, version H119/120 of the data record is ingested.
- ERS data is processed by the Microwave Remote Sensing Group at TU Wien.
- All passive datasets are processed using the LPRMv7 algorithm, designed and implemented by Planet.
ESA CCI Soil Moisture User feedback survey
Please consider filling in our anonymous survey at this link, requiring only 8-12 minutes to complete.
Your response is invaluable to the ESA CCI Soil Moisture project and we thank you for any time you can dedicate to it.
Data
ESA CCI SM v08.1
The latest version v08.1 includes data to December 31st, 2022. The algorithm has been updated as follows:
- The uncertainty estimates obtained through Triple Collocation Analysis and the consequent merging weights are now generated on a seasonal basis. The product uncertainty is now more representative of seasonal errors in soil moisture retrieval.
- The barren ground flagging strategy has been changed to a majority decision, where at least 50% + 1 of the observing sensors are needed to raise the flag. The flag is kept optional, i.e., the soil moisture data is not masked.
- Temporal break correction, which was provided as a separate experimental product in previous versions, is now included in COMBINED.
- The temporal extent of the products is brought up to the end of 2022.
Further information can be found in the documentation. Licensing conditions follow the principles of openness and transparency wherever applicable. All ECV data products resulting from the project are freely accessible.
Downloading the Data
All (current and past) versions of ESA CCI SM data can be downloaded for free and without registration from the CEDA Archive under "data/daily_files".
Using the Data
For information on how to use the product, please read the Product User Guide (PUG). This is also available in the docs folder of the FTP site (from which the data can be downloaded).
The downloadable data is provided in 2D (longitude, latitude) image files representing one day of the record. A package is available in python for reading the data as daily images and converting these images to time series and reading them.
- The source code for our python package and installation instructions are available here: https://github.com/TUW-GEO/esa_cci_sm
- The package can be installed via pip using "pip install esa_cci_sm"
- The documentation for this package is available here: https://esa-cci-sm.readthedocs.io/en/latest/
Any software that can handle CF conform data should be able to import the raw .nc files (e.g. CDO, NCO, QGIS, ArCGIS, Matlab, R, ...). You can also use the GUI software Panoply to view each file.
Known issues
Below is a summary of the reported issues of the ESA CCI SM products:
ESA CCI SM v08.1
- For the grid cells (see the smecv_grid package) 2147, 2148, 2149 (Eastern China), and 2334, 2335 (east of Yakutiya), the processing failed to include observations from the Fengyun (3-B/C/D) sensors series. This leads to a spatial discontinuity in the soil moisture uncertainty field (see figure below) and a systematic decrease in coverage in the June 2011 - December 2022 period. However, it does not lead to a substantial discontinuity in the soil moisture field thanks to the many sensors operational in the same period (see figure below).
- The sensor values for
ASCATA,ASCATB, andASCATCin thesensorfield are all set to256(contrary to what stated in the netCDF file attributes).
Citing the data
The following citations are compulsory with the use of the dataset:
- Gruber, A., Scanlon, T., van der Scalie, R., Wagner, W., Dorigo, W. (2019), Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth System Science Data, 11, 717-739, https://doi.org/10.5194/essd-11-717-2019.
- Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi, M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y.,Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C., van der Schalie, R., Seneviratne, S. I. Smolander, T., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2017.07.001.
- (compulsory with the use of the COMBINED product) Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W. (2021). Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record, in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896.
Further information
If you are interested in previous product versions, please visit the CEDA Archive or send us a request at:
CCI_SM_CONTACT@EODC.EU
Please consider filling in our anonymous survey at this link, requiring only 8-12 minutes to complete.
Your response is invaluable to the ESA CCI Soil Moisture project and we thank you for any time you can dedicate to it.
Key Documents
The following documents have been published by the Soil Moisture project, referring to the ESA CCI SM v09.1 product:
- Product Validation and Intercomparison Report (PVIR): ESA_CCI_SM_D4.1_v2_PVIR_v9.1_issue_1.0 (DOI: https://doi.org/10.5281/zenodo.13861146)
- Algorithm Theoretical Baseline Document (ATBD): ESA_CCI_SM_RD_D2.4_v1.1_ATBD_v08.1_1.1 (DOI: https://doi.org/10.5281/zenodo.8320868)
- Product User Guide (PUG): ESA_CCI_SM_RD_D4.2_v2_Product_Users_Guide_v09.1_i1.0 (DOI: https://doi.org/10.5281/zenodo.13861012)
- Climate Assessment Report (CAR): ESA_CCI_SM_D5.1_v2_CAR_issue_1.0 (DOI:https://doi.org/10.5281/zenodo.15084332)
The following documents have been published by the Soil Moisture project, referring to the ESA CCI SM v08.1 product:
- Product Validation and Intercomparison Report (PVIR): ESA_CCI_SM_D4.1_v1_PVIR_v8.1_issue_1.0 (DOI: https://doi.org/10.5281/zenodo.8320929)
- Algorithm Theoretical Baseline Document (ATBD): ESA_CCI_SM_RD_D2.4_v1.1_ATBD_v08.1_1.1 (DOI: https://doi.org/10.5281/zenodo.8320868)
- Product User Guide (PUG): ESA_CCI_SM_D3.3.1_v1_PUG_v8.1_issue_1.0 (DOI: https://doi.org/10.5281/zenodo.8320913)
Team
The CCI+ Soil Moisture project consortium consists of the following partners.
- Earth Observation Data Centre (EODC), Austria – project management
- Technische Universität Wien (TUW), Austria – algorithm development/ scientific advancements
- Planet, The Netherlands – passive datasets/ scientific advancements
- Eidgenössische Technische Hochschule Zürich (ETH Zürich), Switzerland – validation and verification
- CESBIO, France – algorithm development
Publications
Here you can find a list of publications relating to the ESA CCI Soil Moisture project. Authors listed in bold are consortium members (current or past). For a full list of articles relating to the ESA CCI SM product, please see the homepages of the compulsory citations.
Generation of the ESA CCI soil moisture product (citation of these papers is compulsory when you use the ESA CCI product)
Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001.
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture Climate Data Records and their underlying merging methodology. Earth System Science Data 11, 717-739, https://doi.org/10.5194/essd-11-717-2019
If using the COMBINED product, the following is also compulsory in addition to the above:
Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W. (2021). Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record, in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896.
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: http://dx.doi.org/10.1016/j.rse.2015.10.019.
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 Sensing. PP. 1-13. https://doi.org/10.1109/TGRS.2017.2734070.
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: http://dx.doi.org/10.1175/JHM-D-13-0200.1.
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.
ESA CCI SM in BAMS State of the Climate
Stradiotti, P., Preimesberger, W., van der Schalie, R., Madelon, R. , Rodriguez-Fernandez, N., Hirschi, M., Gruber, A., Hahn, S., Dorigo, W. A., de Jeu, R. A. M., and Kidd, R. (2023) Soil Moisture [in "State of the Climate in 2022"] Bull. Amer. Meteor. Soc., 104 (9), S65–S66, https://doi.org/10.1175/BAMS-D-23-0090.1.
van der Schalie, R., Preimesberger, W., Stradiotti, P., van der Vliet, M., Mösinger, L., Rodríguez-Fernández, N., Madelon, R., Hahn, S., Hirschi, M., Kidd, R., R. A. M. de Jeu, and Dorigo, W. (2022) Soil Moisture [in "State of the Climate in 2021"] Bull. Amer. Meteor. Soc., 103 (8), S64–S66, doi.org/10.1175/2022BAMSStateoftheClimate.1
van der Schalie, R., Scanlon, T., Preimesberger, W., Pasik, A., van der Vliet, M., Mosinger, L., Rodriguez-Fernandez, N., Madelon, R., Hahn, S., Hirschi, M., Kidd, R., R. A. M. de Jeu, Dorigo, W. (2021) Soil Moisture [in "State of the Climate in 2020"] Bull. Amer. Meteor., 102 (8), S67-S68, doi.org/10.1175/2021BAMSStateoftheClimate
Preimesberger, W., Pasik, A., van der Schalie, R., Scanlon, T., Kidd, R., R. A. M. de Jeu, Dorigo, W. (2020) Soil Moisture [ in "State of the Climate in 2019"]. Bull. Amer. Meteor., 101 (8), S56-S57, doi.org/10.1175/BAMS-D-20-0104.1.
Scanlon, T., van der Schalie, R., Preimesberger, W., Reimer, C., Hahn, S., Gruber, A., Kidd, R., de Jeu, R.A.M. and Dorigo, W. A. (2019), [Global Climate] Soil Moisture [in "State of the Climate in 2018"]. Bulletin of the American Meteorological Society, 100 (9), 38-39. doi:10.1175/BAMS-D-19-0193.1.
Dorigo, W., Scanlon, T., Gruber, A., van der Schalie, R., Reimer, C., Hahn, S., Paulik, C., Wagner, W., De Jeu, R. (2018), [Hydrological cycle] Soil Moisture [in "State of the Climate in 2017"]. Bulletin of the American Meteorological Society, 99 (8), 35-36. doi:10.1175/2018BAMSStateoftheClimate.1
Dorigo, W., Chung, D., Gruber, A., Hahn, S., Mistelbauer, T., Parinussa, R., Reimer, C., van der Schalie, R., De Jeu, R., Wagner, W. (2017), [Hydrological cycle] Soil Moisture [in "State of the Climate in 2016"]. Bulletin of the American Meteorological Society, 98 (8), 30-32. doi:10.1175/2017BAMSStateoftheClimate.1
Dorigo, W.A., 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"]. Bulletin of the American Meteorological Society, 97 (8), S31-32.
Dorigo, W.A., Reimer, C., Chung, D., Parinussa, R.M., Melzer, T., Wagner, W., De Jeu, R.A.M., Kidd, R. (2015). [Hydrological cycle]] Soil Moisture [in: "State of the Climate in 2014"]. Bulletin of the American Meteorological Society, 96 (7), S28-S29. doi: 10.1175/2015BAMSStateoftheClimate.1.
Dorigo, W.A., Chung, D., Parinussa, R.M., Reimer, C., Hahn, S., Liu, Y.Y., Wagner, W., De Jeu, R.A.M., Paulik, C., Wang, G. (2014). [Global Climate] Soil Moisture [in: "State of the Climate in 2013"]. Bulletin of the American Meteorological Society, 95 (7), S25-S26.
Parinussa, R.M., De Jeu, R., Wagner, W., Dorigo, W., Fang, F., Teng, W., & Liu, Y.Y. (2013). [Global Climate] Soil Moisture [in: "State of the Climate in 2012"]. Bulletin of the American Meteorological Society, 94 (8), S24-S25.
De Jeu, R.A.M., Dorigo, W.A., Parinussa, R.M., Wagner, W., Chung, D. (2012): [Global Climate] Soil Moisture [in: State of the Climate in 2011]. Bull. Amer. Meteor. Soc., 93 (7), S30-S34.
De Jeu, R.A.M., Dorigo, W.A., Parinussa, R.M., Wagner, W., Liu, Y.Y., Chung, D., Fernandez-Prieto (2012): [Global Climate] 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]. Bull. Amer. Meteor. Soc., 92 (6), S52-S53. http://dx.doi.org/10.1175/1520-0477-92.6.S1
Special issue relating to ESA CCI SM
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.
Other key papers using ESA CCI SM
Al-Yaari, A., Wigneron, J.-P., Dorigo, W., Colliander, A., Pellarin, T., Hahn, S., Mialon, A., Richaume, P., Fernandez-Moran, R., Fan, L., Kerr, Y. H., De Lannoy, G. (2019) Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements. Remote Sensing of Environment, 224, 289-303. https://doi.org/10.1016/j.rse.2019.02.008
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.
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.
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.
Ciabatta, L., Massari, C., Brocca, L., Reimer, C., Hahn, S., Dorigo, W., & Wagner, W. (2016). Using Python® language for the validation of the CCI soil moisture products via SM2RAIN (No. e2131v1). PeerJ Preprints. doi.org/10.7287/peerj.preprints.2131v3.
Ciabatta, L., Massari, C., Brocca, L., Gruber, A., Reimer, C., Hahn, S., Paulik, C., Dorigo, W., Kidd, R., and Wagner, W. (2018) SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture, Earth Syst. Sci. Data, 10, 267-280, https://doi.org/10.5194/essd-10-267-2018, 2018.
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: http://dx.doi.org/10.1016/j.jhydrol.2014.02.015.
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., Dorigo, W. (2016). http://www.sciencedirect.com/science/article/pii/S0303243415001579. International Journal of Applied Earth Observation and Geoinformation, 45, part B, 107-109, doi: 10.1016/j.jag.2015.10.007.
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.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.
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. doi.org/10.1016/j.jag.2016.02.007.
Dorigo, W., Gruber, A., Van Der Schalie, R., Paulik, C., Scanlon, T., Reimer, C., Kidd, R., de Jeu, R., Wagner, W. (2018) Statistical merging of active and passive microwave observations into long-term soil moisture climate data records. IGARSS 2018 – 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, 2018, 333-336. http://doi.org/10.1109/IGARSS.2018.8519579
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.
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.
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), Geosci. Model Dev., 10, 4443-4476, doi.org/10.5194/gmd-10-4443-2017.
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.
Gruber, A., De Lannoy, G., Crow, W. (2019) A Monte Carlo based adaptive Kalman filtering framework for soil moisture data assimilation. Remote Sensing of Environment 228, 2019, 105-114. https://doi.org/10.1016/j.rse.2019.04.003.
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.
Ikonen, J., Smolander, T., Rautiainen, K., Cohen, J., Lemmetyinen, J., Salminen, M., Pulliainen, J.(2018) Spatially Distributed Evaluation of ESA CCI Soil Moisture Products in a Northern Boreal Forest Environment, Geosciences 2018, 8, 51. DOI: https://doi.org/10.3390/geosciences8020051.
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.
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., 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 Environment, Volume 203, 2017, Pages 216-225, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.06.014.
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, Volume 203,2017,Pages 2-8, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.014.
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.
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.
Sharifi, E., Eitzinger, J., Dorigo, W. (2019) Performance of the State-Of-The-Art Gridded Precipitation Products over Mountainous Terrain: A Regional Study over Austria. Remote Sens. 2019, 11, 2018. https://doi.org/10.3390/rs11172018
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. http://dx.doi.org/10.1016/j.rse.2016.05.008.
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.
Van der Schalie, R.; De Jeu, R.; Parinussa, R.; Rodríguez-Fernández, N.; Kerr, Y.; Al-Yaari, A.; Wigneron, J.-P.; Drusch, M. (2018) The Effect of Three Different Data Fusion Approaches on the Quality of Soil Moisture Retrievals from Multiple Passive Microwave Sensors. Remote Sens. 10, 107. https://doi.org/10.3390/rs10010107
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.
Zaussinger, F., Dorigo, W., Gruber, A., Tarpanelli, A., Filippucci, P., Brocca, L. (2019) Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data. Hydrol. Earth Syst. Sci. 23, 897-923. https://doi.org/10.5194/hess-23-897-2019
Contacts
Key contacts within the soil moisture project.
- ESA Project Coordinator: Dr Clément Albergel, ESA – clement.albergel@esa.int
- Coordinator/Earth Observation Science Team Lead: Prof. Wouter Dorigo, TUW – wouter.dorigo@geo.tuwien.ac.at
- Project Management/Coordinator: Richard Kidd, EODC – richard.kidd@eodc.eu
- Climate Research Group Lead: Dr Martin Hirschi, ETH Zurich – martin.hirschi@env.ethz.ch
- Helpdesk CCI_SM_CONTACT@EODC.EU
