Effects of modified soil water‐heat physics on RegCM4 simulations of climate over the Tibetan Plateau

Abstract

To optimize the description of land surface processes and improve climate simulations over the Tibetan Plateau (TP), a modified soil water‐heat parameterization scheme (SWHPS) is implemented into the Community Land Model 3.5 (CLM3.5), which is coupled to the regional climate model 4 (RegCM4). This scheme includes Johansen's soil thermal conductivity scheme together with Niu's groundwater module. Two groups of climate simulations are then performed using the original RegCM4 and revised RegCM4 to analyze the effects of the revised SWHPS on regional climate simulations. The effect of the revised RegCM4 on simulated air temperature is relatively small (with mean biases changing by less than 0.1°C over the TP). There are overall improvements in the simulation of winter and summer air temperature but increased errors in the eastern TP. It has a significant effect on simulated precipitation. There is also a clear improvement in simulated annual and winter precipitation, particularly over the northern TP, including the Qilian Mountains and the source region of the Yellow River. There are, however, increased errors in precipitation simulation in parts of the southern TP. The precipitation difference between the two models is caused mainly by their convective precipitation difference, particularly in summer. Overall, the implementation of the new SWHPS into the RegCM4 has a significant effect not only on land surface variables but also on the overlying atmosphere through various physical interactions.

Precipitation over the Tibetan Plateau during recent decades: a review based on observations and simulations

“…Observations (OBS) are the same as Figure . RegCM4_OC and RegCM4_RC indicate RegCM4 coupled with the original CLM3.5 and the revised CLM3.5, respectively (after Wang et al , ). [Colour figure can be viewed at wileyonlinelibrary.com].…”

“…DDMs, which can describe climate variations induced by mesoscale and smaller topography, underlying surface characteristics, and other factors, have become an outstanding tool for comprehending climate characteristics and change, such as precipitation and its response to atmospheric circulation (e.g. Giorgi, 1990;Wang et al, 2004Wang et al, , 2016Gao et al, 2011Gao et al, , 2015bMaussion et al, 2014;Feng and Zhou, 2015). Of the various DDMs that have been applied over the TP region, the Regional Climate Model (RegCM) series (Pal et al, 2007;Giorgi et al, 2012) are the most commonly used.…”

“…For instance, in CLM3.5, the Farouki scheme calculated soil thermal conductivity is generally higher on the TP, groundwater is not well represented (Wang et al, 2015c). Then simulated precipitation by RegCM4 coupled with the modified soil thermal conductivity and groundwater schemes in CLM3.5 is significantly improved over the eastern Qianlian Mountains, the source region of the Yellow River, and the Tanggula Mountains, moreover, simulated annual and summer total precipitation, large-scale and convective precipitation caused by the soil water-heat physics are statistically significant over the most part of the TP (Figure 4; Wang et al, 2016).…”

“…The atmosphere, hydrosphere, cryosphere, and biosphere all interact across this region, and their interactions have drawn considerable attention (e.g. Ma et al, 2008;Yang et al, 2010Yang et al, , 2011Yang et al, , 2014bYao et al, 2012;Wang et al, 2016).…”

Development of a Physically Based Soil Albedo Parameterization for the Tibetan Plateau

“…Several studies indicated that the performance of RCMs can be significantly influenced by the parameterization of the land surface model (LSM), including surface albedo, soil water–heat transfer, snow properties, vegetation fluctuations, and other factors (Davin and Seneviratne, 2012; Gao et al, 2017; Hong et al, 2009; Jin et al, 2010; Rechid et al, 2009; Wang et al, 2016). For the TP, researchers have tested the applicability of many different LSMs during the past decade (Cuo et al, 2015; Gao et al, 2004; Guo and Wang, 2013; Guo et al, 2011; Wang et al, 2016), including the revised Simple Biosphere model (Sellers et al, 1996a), the variable infiltration capacity model (Liang et al, 1994), the simultaneous heat and water model (Flerchinger and Saxton, 1989), Version 4 of the Community Land Model (Oleson et al, 2010), and others. Of all the relevant processes, surface energy partitioning is the most fundamental and has attracted considerable research interests (Gao et al, 2004, 2017; Guo et al, 2011; Wang et al, 2016; Yang et al, 2009).…”