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Article

L-Band Soil Moisture Retrievals Using Microwave Based Temperature and Filtering. Towards Model-Independent Climate Data Records

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Water & Climate, VanderSat B.V., 2011VK Haarlem, The Netherlands
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CESBIO (Université Toulouse 3, CNES, CNRS, INRAE, IRD), 31400 Toulouse, France
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CLIMERS, TU Wien, Department of Geodesy and Geoinformation, 1040 Vienna, Austria
*
Author to whom correspondence should be addressed.
Academic Editor: John J. Qu
Remote Sens. 2021, 13(13), 2480; https://doi.org/10.3390/rs13132480
Received: 21 May 2021 / Revised: 17 June 2021 / Accepted: 22 June 2021 / Published: 25 June 2021
(This article belongs to the Special Issue SMOS and SMAP Anniversaries)
The CCI Soil Moisture dataset (CCI SM) is the most extensive climate data record of satellite soil moisture to date. To maximize its function as a climate benchmark, both long-term consistency and (model-) independence are high priorities. Two unique L-band missions integrated into the CCI SM are SMOS and SMAP. However, they lack the high-frequency microwave sensors needed to determine the effective temperature and snow/frozen flagging, and therefore use input from (varying) land surface models. In this study, the impact of replacing this model input by temperature and filtering based on passive microwave observations is evaluated. This is derived from an inter-calibrated dataset (ICTB) based on six passive microwave sensors. Generally, this leads to an expected increase in revisit time, which goes up by about 0.5 days (~15% loss). Only the boreal regions have an increased coverage due to more accurate freeze/thaw detection. The boreal regions become wetter with an increased dynamic range, while the tropics are dryer with decreased dynamics. Other regions show only small differences. The skill was evaluated against ERA5-Land and in situ observations. The average correlation against ERA5-Land increased by 0.05 for SMAP ascending/descending and SMOS ascending, whereas SMOS descending decreased by 0.01. For in situ sensors, the difference is less pronounced, with only a significant change in correlation of 0.04 for SM SMOS ascending. The results indicate that the use of microwave-based input for temperature and filtering is a viable and preferred alternative to the use of land surface models in soil moisture climate data records from passive microwave sensors. View Full-Text
Keywords: soil moisture; effective temperature; SMAP; SMOS; LPRM; passive microwave radiometry soil moisture; effective temperature; SMAP; SMOS; LPRM; passive microwave radiometry
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MDPI and ACS Style

van der Schalie, R.; van der Vliet, M.; Rodríguez-Fernández, N.; Dorigo, W.A.; Scanlon, T.; Preimesberger, W.; Madelon, R.; de Jeu, R.A.M. L-Band Soil Moisture Retrievals Using Microwave Based Temperature and Filtering. Towards Model-Independent Climate Data Records. Remote Sens. 2021, 13, 2480. https://doi.org/10.3390/rs13132480

AMA Style

van der Schalie R, van der Vliet M, Rodríguez-Fernández N, Dorigo WA, Scanlon T, Preimesberger W, Madelon R, de Jeu RAM. L-Band Soil Moisture Retrievals Using Microwave Based Temperature and Filtering. Towards Model-Independent Climate Data Records. Remote Sensing. 2021; 13(13):2480. https://doi.org/10.3390/rs13132480

Chicago/Turabian Style

van der Schalie, Robin, Mendy van der Vliet, Nemesio Rodríguez-Fernández, Wouter A. Dorigo, Tracy Scanlon, Wolfgang Preimesberger, Rémi Madelon, and Richard A.M. de Jeu 2021. "L-Band Soil Moisture Retrievals Using Microwave Based Temperature and Filtering. Towards Model-Independent Climate Data Records" Remote Sensing 13, no. 13: 2480. https://doi.org/10.3390/rs13132480

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