This data set is only available for a restricted user group, please contact us if you want to access these data.
RESTRICTED only accessable in CEN/MPI net or via CliSAP login What does that mean?
A unique 40-year long soil moisture data set, version 4.5, has been generated in the framework of the ESA-CCI Soil Moisture ECV project. For this purpose C-band scatterometer data (ERS-1/2 AMI scatterometer, MetOp Advanced Scatterometer) and multi-frequency radiometer data (SMOS, SMMR, SSM/I, TMI, AMSR-E, Windsat, AMSR2) are used to compute the soil moisture.
For the completely re-processed data set offered here, different (Level 2) soil moisture (SM) data sets are merged together. One strand of data comprises soil moisture retrieved using satellite active microwave data (C-Band scatterometers, see above); the second strand comprises soil moisture retrieved using satellite microwave radiometry. Data products from each strand are merged directly, together with a sophisticated uncertainty characterization (see ATBD). The approach makes best use of already established Level 2 services of ESA, EUMETSAT, NASA, JAXA, etc. for the different satellites and sensors. From the two separate strands of data two additional data products are generated. The most important differences between v4.4 and earlier versions like v4.2 and v3.2 can be found in the Executive Summary. Version v4.5 is identical to v4.4 with respect to the processing used.
For more information regarding retrieval schemes we refer to our web pages of ASCAT soil moisture, AMSR-E soil moisture, SMOS soil moisture as well as to the extensive number of documents created during the ESA-CCI Soil Moisture ECV project (see: http://www.esa-soilmoisture-cci.org/).
We DEFINITELY recommend all interested users to register at the respective ESA web site http://www.esa-soilmoisture-cci.org/ to not miss information about updates of the data set.
We are offering the daily "COMBINED" data set v4.5. Currently data sets "ACTIVE" and "PASSIVE" are only available on request.
Last data set update at ICDC: February 14, 2020.
|Volumetric soil moisture||m³ / m³||0 ... 1|
|Volumetric soil moisture error||m³ / m³||0 ... 1|
|Day/Night flag||--||0,1,2,3 = no data, day, night, day+night|
|Quality flag||--||0 ... 8, 16 ... 23 (0 = best quality)|
|Frequency band flag||--||0 ... 130 (L to Ka-Band, single bands & combinations)|
|Sensor flag||--||0 ... 864 (single sensors & combinations)|
|Time||Days since 1970-01-01 00 UTC|
Period and temporal resolution:
- 1978-11-01 to 2018-12-31
Coverage and spatial resolution
- Spatial resolution: 0.25° x 0.25°, cartesian grid
- Geographic latitude: 89.875°S to 89.875°N
- Geographic longitude: 179.875°W to 179.875°E
- Dimension: 720 rows x 1440 columns
- Altitude: following terrain
Each file of the data set contains an uncertainty estimate and a set of quality flags which basically document the reason why data have been discarded from the data set (see below); in addition each file gives information about the sensors used.
We note, that soil moisture retrieval is limited in regions of pronounced topography, in case of standing water, and in areas of dense vegetation. For snow covered areas and frozen soil a soil moisture retrieval is also not possible.
Substantial gaps occur in the data set. These stem from the fact that the used satellite sensors only view a limited portion of the Earth's surface during their overpasses during one day.
We recommend to take a look at the references and the papers listed under "Data citation" (see below) for more details about data quality, validation, and inter-comparison studies.
Users should be aware of the fact that the product is merged from data from a variety of satellite sensors. Their differences in viewing geometry, sensing characteristics, and orbital coverage as well as different maturity of SM retrieval algorithms may cause inconsistencies in the data set.
Available on request are additional netCDF files containing the distribution of the topographic complexity, wetland fraction, soil porosity, and vegetation optical depth mean as well as a separate land mask.
Vienna University of Technology, Austria
Transmissitivity B.V. / VanderSat B.V. Noordwijk, The Netherlands
email: ecv_sm_contact (at) eodc.eu
Vienna University of Technology
email: richard.kidd (at) geo.tuwien.ac.at
ICDC / CEN / University of Hamburg
email: stefan.kern (at) uni-hamburg.de
We recommend to regularly check http://www.esa-soilmoisture-cci.org for updated information from the ESA-CCI Soil Moisture ECV project.
Algorithm Theoretical Basis Documents:
- Gruber, A., et al., 2019, Evolution of the ESA CCI soil moisture climate data records and their underlying merging methodology. Earth System Science Data, 11, 717-739, http://doi.org/10.5194/essd-11-717-2019.
- Gruber, A., et al., 2017, Triple collocation-based merging of satellite soil moisture retrievals. IEEE Transactions on Geoscience and Remote Sensing, 1-13.
- Dorigo, W. A., et al., 2017, ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, Remote Sensing of Environment. doi.org/10.1016/j.rse.2017.07.001.
- Dorigo, W. A., et al., 2015, Evaluation of the ESA CCI soil moisture product using ground-based observations, Remote Sensing of Environment, 162, 380-395, doi:10.1016/j.rse.2014.07.023.
- Zeng, J., et al., 2015, Evaluation of Remotely Sensed and Reanalysis Soil Moisture Products over the Tibetan Plateau using in situ Observations, Remote Sensing of Environment, 163, 91-110, doi:10.1016/j.rse.2015.03.008.
- Jing, W., et al., 2018, A comparison of ECV and SMOS soil moisture products based on OzNet monitoring network, Remote Sensing, 10(5), 703, doi:10.3390/rs10050703.
Please use the following three references:
- Gruber, A., et al., 2019, Evolution of the ESA CCI soil moisture climate data records and their underlying merging methodology, Earth System Science Data, 11, 717-739, http://doi.org/10.5194/essd-11-717-2019.
- Dorigo, W. A., et al., 2017, ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, Remote Sensing of Environment, 203, 185-215, 2017, doi:10.1016/j.rse.2017.07.001.
- Gruber, A., et al., 2017, Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals, Transactions on Geoscience and Remote Sensing, 55(12), 1-13. doi:10.1109/TGRS.2017.2734070.
Last data access was by ICDC (http://icdc.cen.uni-hamburg.de) from ftp.geo.tuwien.ac.at on February 12 2020.