000810733 001__ 810733
000810733 005__ 20210129223516.0
000810733 0247_ $$2Handle$$a2128/11993
000810733 0247_ $$2ISSN$$a1866-1793
000810733 020__ $$a978-3-95806-143-9
000810733 037__ $$aFZJ-2016-03325
000810733 041__ $$aEnglish
000810733 1001_ $$0P:(DE-Juel1)144811$$aRötzer, Kathrina$$b0$$eCorresponding author$$gfemale$$ufzj
000810733 245__ $$aStatistical analysis and combination of active and passive microwave remote sensing methods for soil moisture retrieval$$f- 2016-12-31
000810733 260__ $$aJülich$$bForschungszentrum Jülich GmbH Zentralbibliothek, Verlag$$c2016
000810733 300__ $$aXIV, 112 S.
000810733 3367_ $$2DataCite$$aOutput Types/Dissertation
000810733 3367_ $$2ORCID$$aDISSERTATION
000810733 3367_ $$2BibTeX$$aPHDTHESIS
000810733 3367_ $$02$$2EndNote$$aThesis
000810733 3367_ $$0PUB:(DE-HGF)11$$2PUB:(DE-HGF)$$aDissertation / PhD Thesis$$bphd$$mphd$$s1470057321_28380
000810733 3367_ $$2DRIVER$$adoctoralThesis
000810733 4900_ $$aSchriften des Forschungszentrums Jülich Reihe Energie & Umwelt / Energy & Environment$$v321
000810733 502__ $$aUniversität Bonn, Diss., 2016$$bDr.$$cUniversität Bonn$$d2016
000810733 520__ $$aKnowledge about soil moisture and its spatio-temporal dynamics is essential for the improvement of climate and hydrological modeling, including drought and flood monitoring and forecasting, as well as weather forecasting models. In recent years, several soil moisture products from active and passive microwave remote sensing have become available with high temporal resolution and global coverage. However, for the improvement of a soil moisture product and for its proper use in models or other applications, validation and evaluation of its spatial and temporal patterns are of great importance. In chapter 2 the Level 2 Soil Moisture and Ocean Salinity (SMOS) soil moisture product and the Advanced Scatterometer (ASCAT) surface soil moisture product are validated in the Rur and Erft catchments in western Germany for the years 2010 to 2012 against a soil moisture reference created by a hydrological model, which was calibrated by in situ observations. Correlation with the modeled soil moisture reference results in an overall correlation coefficient of 0.28 for the SMOS product and 0.50 for ASCAT. While the correlation of both products with the reference is highly dependent ontopography and vegetation, SMOS is also strongly influenced by radiofrequency interferences in the study area. Both products exhibit dry biases as compared to the reference. The bias of the SMOS product is constant in time, while the ASCAT bias is more variable. For the investigation of spatio temporal soil moisture patterns in the study area, a new validation method based on the temporal stability analysis is developed. Through investigation of mean relative differences of soil moisture for every pixel the temporal persistence of spatial patterns is analyzed. Results indicate a lower temporal persistence for both SMOS and ASCAT soil moisture products as compared to modeled soil moisture. ASCAT soil moisture, converted to absolute values, shows highest consistence of ranks and therefore most similar spatio-temporal patterns with the soil moisture reference, while the correlation of ranks of mean relative differences is low for SMOS and relative ASCAT soil moisture products. Chapter 3 investigates the spatial and temporal behavior of the SMOS and ASCAT soil moisture products and additionally of the ERA Interim product from a weather forecast model reanalysis on global scale. Results show similar temporal patterns of the soil moisture products, but high impact of sensor and retrieval types and therefore higher deviations in absolute soil moisture values. Results are more variable for the spatial patterns of the soil moisture products: While the global patterns are similar, a ranking of mean relative differences reveals that ASCAT and ERA Interim products show most similar spatial soil moisture patterns, while ERA and SMOS products show least similarities. Patterns are generally more similar between the products in regions with low vegetation. [...]
000810733 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0
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000810733 9141_ $$y2016
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