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The Simulation of L-Band Microwave Emission of Frozen Soil during the Thawing Period with the Community Microwave Emission Model (CMEM)

Authors :
Shaoning Lv
Clemens Simmer
Yijian Zeng
Jun Wen
Zhongbo Su
Source :
Journal of Remote Sensing, Vol 2022 (2022)
Publication Year :
2022
Publisher :
American Association for the Advancement of Science (AAAS), 2022.

Abstract

One-third of the Earth’s land surface experiences seasonal freezing and thawing. Freezing-thawing transitions strongly impact land-atmosphere interactions and, thus, also the lower atmosphere above such areas. Observations of two L-band satellites, the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) missions, provide flags that characterize surfaces as either frozen or not frozen. However, both state transitions—freezing and thawing (FT)—are continuous and complex processes in space and time. Especially in the L-band, which has penetration depths of up to tens of centimeters, the brightness temperature (TB) may be generated by a vertically-mixed profile of different FT states, which cannot be described by the current version of the Community Microwave Emission Model (CMEM). To model such complex state transitions, we extended CMEM in Fresnel mode with an FT component by allowing for (1) a varying fraction of an open water surface on top of the soil, and (2) by implementing a temporal FT phase transition delay based on the difference between the soil surface temperature and the soil temperature at 2.5 cm depth. The extended CMEM (CMEM-FT) can capture the TB progression from a completely frozen to a thawed state of the contributing layer as observed by the L-band microwave radiometer ELBARA-III installed at the Maqu station at the northeastern margin of the Tibetan Plateau. The extended model improves the correlation between the observations and CMEM simulations from 0.53/0.45 to 0.85/0.85 and its root-mean-square-error from 32/25 K to 20/15 K for H/V-polarization during thawing conditions. Yet, CMEM-FT does still not simulate the freezing transition sufficiently.

Details

Language :
English
ISSN :
26941589
Volume :
2022
Database :
Directory of Open Access Journals
Journal :
Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.84f41ecfd0dd4a19918f8a1f9baa2208
Document Type :
article
Full Text :
https://doi.org/10.34133/2022/9754341