Improved Simulation of Frozen‐Thawing Process in Land Surface Model (CLM4.5)

Abstract

Soil freezing-thawing cycle is a hallmark feature of the land surface over cold regions. Variations in soil moisture and temperature during frozen-thawing (FT) process are important for water and energy exchange between land and atmosphere. Results of regional simulations by Community Land Model version 4.5 (CLM4.5) over the Tibetan Plateau show that error of daily soil temperature is within 3°C and error of daily soil moisture is with 0.10 mm 3 /mm 3 in FT process, averaged at 10 sites of whole Tibetan Plateau. Single-point simulations show that model biases partly attribute to uncertainties of initial condition and soil category data; excluding impacts of model setting, large biases of soil moisture still exist during soil thawing, and CLM4.5 fails to simulate the diurnal cycle of soil moisture in this period. Modifications of the FT parameterizations in CLM4.5 are proposed, which include (1) use of virtual temperature (T v ) instead of constant freezing point to determine occurring of phase change, (2) introduction of phase change efficiency (ε) to optimize variation rate of soil temperature and moisture in FT process, and (3) consideration of inferred impacts of phase change on soil heat conduction. Single-point and global simulations show that compared to original parameterizations in CLM4.5, these modifications can reproduce the features of daily and diurnal variations in soil moisture and make simulation in FT process closer to the observations.

Large Uncertainties in Runoff Estimations of GLDAS Versions 2.0 and 2.1 in China

“…However, GLDAS2.1 underestimates runoff even though it overestimates rainfall in the Lancang river, Lower and Upper Songhua river, Middle and Lower Yangtze river, and Upper Yellow river, and it overestimates runoff even though it underestimates rainfall a little in the Middle Yellow river. These uncertainties may be caused by both the rainfall uncertainty and Noah model uncertainty (including model structures and parameterization; Swenson et al, ; Chen et al, ; Yang et al, ). Niu et al () pointed out that Noah model may result in large uncertainty in surface hydrological processes (including the vegetation photosynthesis and transpiration processes, and groundwater simulation).…”

“…Relative bias (RB %) of runoff and rainfall.10.1029/2019EA000829Earth and Space Science uncertainties may be caused by both the rainfall uncertainty and Noah model uncertainty (including model structures and parameterization;Swenson et al, 2012;Chen et al, 2013;Yang et al, 2018) Niu et al (2011). pointed out that Noah model may result in large uncertainty in surface hydrological processes (including the vegetation photosynthesis and transpiration processes, and groundwater simulation).…”

Improved ELMv1-ECA Simulations of Zero-Curtain Periods and Cold-season CH<sub>4</sub> and CO<sub>2</sub> Emissions at Alaskan Arctic Tundra Sites

“…When the liquid water available to be frozen becomes small enough, the released latent heat is not sufficient to compensate for the required energy deficit ( ), and then the freezing process stops. Consequently, the model freezes soil water quickly, resulting in an underestimated duration of the soil water phase-change processes and the zero-curtain periods, and also cold-biased winter temperatures (Nicolsky et al, 2007;Yang et al, 2018a).…”

“…These modification factors are explained below. The phase-change efficiency, introduced by Le Moigne et al (2012) and adopted by Masson et al (2013) and Yang et al (2018a), introduces the dependency of available liquid water on the phase-change rate (Le Moigne et al, 2012). The phase-change efficiency for freezing, , (see (Eq.…”

“…As in Nicolsky et al (2007) and Yang et al (2018a), the occurrence of a phase-change process is then determined by the temperature of the freezing point depression (i.e., an virtual temperature, see (Eq. A8)) instead of .…”