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 ZMAW net or via CliSAP login What does that mean?
This soil moisture data set is based on dual-polarization brightness temperature measurements carried out with the polar orbiting Advanced Microwave Scanning Radiometer aboard EOS (AMSR-E) at frequencies of 6.9 GHz, 10.7 GHz, and 36.5 GHz. A radiative transfer model is used to simulate the brightness temperature based on the soil surface and canopy emissivity and the surface temperature which is derived using the AMSR-E 36.5 GHz data. Simulated brightness temperatures are compared to the measured ones while iteratively changing the variable parameters until convergence is achieved. The parameters are the soil dielectric constant (depends on soil type and moisture) and the canopy optical depth (depends on canopy type, density, and water content). Once convergence between modeled and measured brightness temperature is achieved (difference below 0.25 K) the soil moisture is derived using a soil dielectric mixing model and a global data set of soil physical properties. The derived quantity is the relative volumetric water content and is given in percent. Soil moisture (and its uncertainty) is computed for both frequencies (6.9 GHz and 10.7 GHz) separately.
We offer data for years 2002-2011, i.e. the full AMSR-E measurement period. Data are offered as daily swath composites, separated for descending and ascending overpasses, i.e. there are two files per day available; one contains data from all ascending overpasses of the respective day, the other data from all descending overpasses. In principle the data set offered here via ICDC is a re-formatted (1), inconsistency-corrected (2) version of the LPRM_AMSRE_SOILM3_V002 data set of the VU Amsterdam.
(1) Soil moisture data are now in landscape mode
(2) Inconsistencies w.r.t. scale factors are corrected. In addition the netCDF-files are following the more recent CF conventions now.
Last data set update (re-formatting): August 6, 2015.
|Relative volumetric soil moisture (C-Band, 6.9 GHz)||%|
|Uncertainty of relative volumetric soil moisture (C-Band, 6.9 GHz)||%|
|Canopy optical depth (C-Band, 6.9 GHz)||--|
|Relative volumetric soil moisture (X-Band, 10.7 GHz)||%|
|Uncertainty of relative volumetric soil moisture (X-Band, 10.7 GHz)||%|
|Canopy optical depth (X-Band, 10.7 GHz)||--|
Period and temporal resolution:
- June 19, 2002 to Oct. 03, 2011
Coverage and spatial resolution:
- Global, separately for ascending and descending satellite overpasses
- Spatial resolution: 0.25° x 0.25°, cartesian grid
- Geographic longitude: 179.875°W to 179.875°E
- Geographic latitude: 89.875°S to 89.875°N
- Dimension: 720 rows x 1440 columns
- Altitude: following terrain
This data set contains a quality flags, a retrieval error and canopy optical depth separately for soil moisture data sets of the two used AMSR-E frequency channels (see parameters).
The data set is completed with the retrieved surface temperature (derived from 36.5 GHz brightness temperatures, see references: Holmes et al.)
Due to lacking documentation we cannot give complete information about the quality flag. It is clear, though, that these flag open water, ice/snow/frozen ground, and (too) dense vegetation. For the latter we recommend to consider the canopy optical depths which are also provided along with the data sets.
We note, that the soil moisture retrieval method used here, is of limited use particularly in regions covered by dense vegetation such as rain forests. These areas are therefore often flagged as unreliable data and/or show a large retrieval noise.
We recommend to take a look at the references for more details about data quality, validation, and inter-comparison studies.
Richard De Jeu & Thomas Holmes
Department of Eco-Hydrology, Faculty of Earth and Life Science
Vrjie Universiteit Amsterdam, Amsterdam, The Netherlands
email: richard.de.jeu (at) falw.vu.nl & thomas.holmes (at) falw.vu.nl
ICDC / CEN / University of Hamburg
email: stefan.kern (at) uni-hamburg.de
Land surface temperature:
Inter-comparison / -evaluation / data synergies
Upon using this data please cite as follows:
Owe, M., R. A. M., de Jeu, and T. R. H. Holmes (2008). Multi-Sensor historical Climatology of satellite-derived global land surface moisture, J Geophys. Res., 113, F01002, doi:1029/2007JF000769, distributed in rotated netCDF format by icdc.cen.uni-hamburg.de