Soil Moisture data (version 03.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets.

The homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2014-12-31 and the Active product covering 1991-08-05 to 2014-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD) or the paper by Wagner 2012, both available in linked documentation. Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in 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