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  • 1
    Publication Date: 2019-07-13
    Description: In a recent paper, Leroux et al. compared three satellite soil moisture data sets (SMOS, AMSR-E, and ASCAT) and ECMWF forecast soil moisture data to in situ measurements over four watersheds located in the United States. Their conclusions stated that SMOS soil moisture retrievals represent "an improvement [in RMSE] by a factor of 2-3 compared with the other products" and that the ASCAT soil moisture data are "very noisy and unstable." In this clarification, the analysis of Leroux et al. is repeated using a newer version of the ASCAT data and additional metrics are provided. It is shown that the ASCAT retrievals are skillful, although they show some unexpected behavior during summer for two of the watersheds. It is also noted that the improvement of SMOS by a factor of 2-3 mentioned by Leroux et al. is driven by differences in bias and only applies relative to AMSR-E and the ECWMF data in the now obsolete version investigated by Leroux et al.
    Keywords: Statistics and Probability; Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN10895 , IEEE Transactions on Geoscience and Remote Sensing; 52; 3; 1901-1906
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  • 2
    Publication Date: 2023-12-20
    Description: The representation of the Earth's surface in global monitoring and forecasting applications is moving towards capturing more of the relevant processes, while maintaining elevated computational efficiency and therefore a moderate complexity. These schemes are developed and continuously improved thanks to well instrumented field-sites that can observe coupled processes occurring at the surface–atmosphere interface (e.g., forest, grassland, cropland areas and diverse climate zones). Approaching global kilometer-scale resolutions, in situ observations alone cannot fulfil the modelling needs, and the use of satellite observation becomes essential to guide modelling innovation and to calibrate and validate new parameterization schemes that can support data assimilation applications. In this book, we review some of the recent contributions, highlighting how satellite data are used to inform Earth surface model development (vegetation state and seasonality, soil moisture conditions, surface temperature and turbulent fluxes, land-use change detection, agricultural indicators and irrigation) when moving towards global km-scale resolutions.
    Keywords: Q1-390 ; direct and inverse methods ; absorption coefficient ; emissivity ; land-surface model ; n/a ; variational retrieval ; temporal autocorrelation ; Bayesian bias correction ; hyperspectral ; infrared ; BRDF ; satellite rainfall ; MCD43C1 ; penetration depth ; RTTOV ; earth-observations ; earth system modelling ; representative depth ; land ; Changjiang (Yangtze) estuary ; CDOM ; soil moisture ; surface ; Maqu network ; surface soil moisture ; MODIS ; soil effective temperature ; GOCI ; microwave remote sensing ; rain gauge ; QAA inversion ; broadband emissivity ; radiation ; surface parameters ; satellite data ; East Africa ; bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general
    Language: English
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