A global analysis of water storage variations from remotely sensed soil moisture and daily satellite gravimetry
| Autor: | D. Blank, A. Eicker, L. Jensen, A. Güntner |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Hydrology and Earth System Sciences, Vol 27, Pp 2413-2435 (2023) |
| Druh dokumentu: | article |
| ISSN: | 1027-5606 1607-7938 |
| DOI: | 10.5194/hess-27-2413-2023 |
| Popis: | Water storage changes in the soil can be observed on a global scale with different types of satellite remote sensing. While active or passive microwave sensors are limited to the upper few centimeters of the soil, satellite gravimetry can detect changes in the terrestrial water storage (TWS) in an integrative way, but it cannot distinguish between storage variations in different compartments or soil depths. Jointly analyzing both data types promises novel insights into the dynamics of subsurface water storage and of related hydrological processes. In this study, we investigate the global relationship of (1) several satellite soil moisture products and (2) non-standard daily TWS data from the Gravity Recovery and Climate Experiment/Follow-On (GRACE/GRACE-FO) satellite gravimetry missions on different timescales. The six soil moisture products analyzed in this study differ in the post-processing and the considered soil depth. Level 3 surface soil moisture data sets of the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) missions are compared to post-processed Level 4 data products (surface and root zone soil moisture) and the European Space Agency Climate Change Initiative (ESA CCI) multi-satellite product. On a common global 1∘ grid, we decompose all TWS and soil moisture data into seasonal to sub-monthly signal components and compare their spatial patterns and temporal variability. We find larger correlations between TWS and soil moisture for soil moisture products with deeper integration depths (root zone vs. surface layer) and for Level 4 data products. Even for high-pass filtered sub-monthly variations, significant correlations of up to 0.6 can be found in regions with a large, high-frequency storage variability. A time shift analysis of TWS versus soil moisture data reveals the differences in water storage dynamics with integration depth. |
| Databáze: | Directory of Open Access Journals |
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