This title appears in the Scientific Report :
2018
Please use the identifier:
http://dx.doi.org/10.1594/PANGAEA.878889 in citations.
Sub-grid soil moisture variability of SMAP, SMOS and ASCAT predicted on basis of soil texture, links to NetCDF files, supplement to: Montzka, Carsten; Rötzer, Kathrina; Bogena, Heye R; Vereecken, Harry (submitted): A new soil moisture downscaling approach for SMAP, SMOS and ASCAT by predicting sub-grid variability. Remote Sensing
Sub-grid soil moisture variability of SMAP, SMOS and ASCAT predicted on basis of soil texture, links to NetCDF files, supplement to: Montzka, Carsten; Rötzer, Kathrina; Bogena, Heye R; Vereecken, Harry (submitted): A new soil moisture downscaling approach for SMAP, SMOS and ASCAT by predicting sub-grid variability. Remote Sensing
Several studies currently strive to improve the spatial resolution of coarse scale high temporal resolution global soil moisture products of the satellite missions SMOS (Soil Moisture and Ocean Salinity), SMAP (Soil Moisture Active and Passive) and ASCAT (Advanced Scatterometer). Soil texture hetero...
Saved in:
Personal Name(s): | Montzka, Carsten |
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Rötzer, Kathrina / Bogena, Heye / Vereecken, Harry | |
Contributing Institute: |
Agrosphäre; IBG-3 |
Imprint: |
PANGAEA - Data Publisher for Earth & Environmental Science
2017
|
DOI: |
10.1594/PANGAEA.878889 |
Document Type: |
Dataset |
Research Program: |
Terrestrial Systems: From Observation to Prediction |
Publikationsportal JuSER |
Several studies currently strive to improve the spatial resolution of coarse scale high temporal resolution global soil moisture products of the satellite missions SMOS (Soil Moisture and Ocean Salinity), SMAP (Soil Moisture Active and Passive) and ASCAT (Advanced Scatterometer). Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability. The approach is based on a method that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. We provide a look-up table map that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set helps identifying adequate regions to validate coarse scale soil moisture products by providing a measure of representativeness of small-scale measurements for the coarse grid cell. Moreover, it contains important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. |