Dataset
ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 03.2
Abstract
The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets.
The v03.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2015-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.
The data set should be cited using all three of the following references:
1. 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
2. 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. 10.1109/TGRS.2017.2734070
3. 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
Details
Previous Info: |
2018-06-29 This dataset forms part of the CCI Soil Moisture v03.2 dataset collection (doi:10.5285/d2eea061026240eb8a2f9cc64a691338. http:/… Show More 2018-06-29 This dataset forms part of the CCI Soil Moisture v03.2 dataset collection (doi:10.5285/d2eea061026240eb8a2f9cc64a691338. http://dx.doi.org/10.5285/d2eea061026240eb8a2f9cc64a691338 ) Show Less |
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Previously used record identifiers: |
No related previous identifiers.
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Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
Data lineage: |
Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project. |
Data Quality: |
as provided by the CCI Soil Moisture team
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File Format: |
Data are in NetCDF format
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Related Documents
Process overview
- var_id: dnflag
- long_name: Day / Night Flag
- var_id: flag
- long_name: Flag
- long_name: Frequency Band Identification
- var_id: freqbandID
- long_name: Observation Timestamp
- var_id: t0
- long_name: Satellite Mode
- var_id: mode
- long_name: Sensor
- var_id: sensor
- var_id: sm
- units: m3 m-3
- long_name: Volumetric Soil Moisture
- var_id: sm_uncertainty
- units: m3 m-3
- long_name: Volumetric Soil Moisture Uncertainty
Co-ordinate Variables
- units: degrees_north
- standard_name: latitude
- var_id: lat
- units: degrees_east
- standard_name: longitude
- var_id: lon
- standard_name: time
- var_id: time
Temporal Range
1978-11-01T00:00:00
2015-12-31T23:59:59
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |