Premium
A joint analysis of modeled soil moisture fields and satellite observations
Author(s) -
Jiménez Carlos,
Clark Douglas B.,
Kolassa Jana,
Aires Filipe,
Prigent Catherine
Publication year - 2013
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/jgrd.50430
Subject(s) - satellite , water content , environmental science , biome , moisture , mean squared error , joint (building) , soil science , meteorology , atmospheric sciences , remote sensing , mathematics , statistics , geology , geography , ecosystem , geotechnical engineering , engineering , ecology , biology , aerospace engineering , architectural engineering
A methodology to conduct a joint analysis of modeled soil moisture fields from the Joint UK Land Environment Simulator (JULES) and a data set of multiwavelength observations is presented. It consists of building a statistical model capturing the relationships between the land surface model estimates and the satellite observations, and then using the satellite observations (mapped into soil moisture predictions by the statistical model) to evaluate the fields estimated by the land surface model. Two statistical models are tested and predict very similar soil moisture (global correlation and root‐mean‐square deviation (RMSD) of ~ 0.98 and ~ 0.02 m 3 /m 3 ). A characterization of prediction uncertainty shows errors ranging between 0.01 and 0.10 m 3 /m 3 , depending on biome and season. The satellite prediction and JULES soil moisture agree relatively well (global correlation and RMSD of ~ 0.92 and ~ 0.05 m 3 /m 3 ), but for some regions and periods, clear differences exist. Conducted tests modifying either the predicted soil moisture or the JULES estimates show that this methodology can effectively change soil moisture toward more correct values. It can then be expected that some of the differences are the result of the satellite information modifying the modeled soil moisture fields toward more realistic values. However, proving this is difficult given the present uncertainties in modeled and observed global soil moisture products.