Review of Lv et al.

Simon Zwieback

doi:10.5194/tc-2021-369-rc1

Abstract

Knowing the Freeze-Thaw (FT) state of the land surface is essential for many aspects of weather forecasting, climate, hydrology, and agriculture. Near-surface air temperature and land surface temperature are usually used in meteorology to infer the FT-state. However, the uncertainty is large because both temperatures can hardly be distinguished from remote sensing. Microwave L-band emission contains rather direct information about the FT-state because of its impact on the soil dielectric constant, which determines microwave emissivity and the optical depth profile. However, current L band-based FT algorithms need reference values to distinguish between frozen and thawed soil, which are often not known sufficiently well. We present a new FT-state detection algorithm based on the daily variation of the H-polarized brightness temperature of the SMAP L3c FT global product for the northern hemisphere, which is available from 2015 to 2021. The exploitation of the daily variation signal allows for a more reliable state detection, particularly during the transitions periods, when the near-surface soil layer may freeze and thaw on sub-daily time scales. The new algorithm requires no reference values; its results agree with the SMAP FT state product by up to 98 % in summer and up to 75 % in winter. Compared to the FT state inferred indirectly from the 2-m air temperature of the ERA5-land reanalysis, the new FT algorithm has a similar performance as the SMAP FT product. The most significant differences occur over the midlatitudes, including the Tibetan plateau and its downstream area. Here, daytime surface heating may lead to daily FT transitions, which are not considered by the SMAP FT state product but are correctly identified by the new algorithm. The new FT algorithm suggests a 15 days earlier start of the frozen-soil period than the ERA5-land’s 2-m air temperature estimate. This study is expected to extend L-band microwave remote sensing data for improved FT detection.

Highlights

Spatial patterns and the timing of freeze-thaw (FT) state transitions over land are highly variable; they strongly impact land35 atmosphere interactions and weather, climate and hydrological, ecological, and biogeochemical processes (Walvoord and Kurylyk, 2016; Schuur et al, 2015; Zeng et al, 2019; Yu et al, 2020b)
20 We present a new FT-state detection algorithm based on the daily variation of the H-polarized brightness temperature of the SMAP L3c FT global product for the northern hemisphere, which is available from 2015 to 2021
Daytime surface heating may lead to daily FT transitions, which are not considered by the SMAP FT state product but are correctly identified by the new algorithm

Summary

Introduction

Spatial patterns and the timing of freeze-thaw (FT) state transitions over land are highly variable; they strongly impact land atmosphere interactions and weather, climate and hydrological, ecological, and biogeochemical processes (Walvoord and Kurylyk, 2016; Schuur et al, 2015; Zeng et al, 2019; Yu et al, 2020b). FT state transition leads to differences in hydrological and thermal conductivities/diffusivities, the albedo for solar and emissivity for terrestrial radiation, and latent/sensible heat fluxes (Hu et al, 2017; Gao et al, 2016; Zhao et al, 2017). Ecosystem responses to seasonal FT-state changes are rapid via significant changes in evapotranspiration, soil respiration, plant photosynthetic activity, liquid water availability, vegetation net primary production, and net ecosystem CO2 exchange (NEE) with the atmosphere(Kimball et al, 1997; Li et al, 2014; Cramer et al, 1999; Matzner and Borken, 2008; Wang et al, 2016).

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