Impact and Sensitivity Analysis of Soil Water and Heat Transfer Parameterizations in Community Land Surface Model on the Tibetan Plateau

Journal of Advances in Modeling Earth Systems

Yaqiong Lu¹  Lin Zhao²  Shaoying Wang²  Mingshan Deng²  Xianhong Meng²  Lunyu Shang²  Hao Chen²  Zhaoguo Li²  Zeyong Hu²  Qian Li³ 

[1] Institute of Mountain Hazards and Environment Chinese Academy of Science Chengdu China;Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions Northwest Institute of Eco‐Environment and Resources Chinese Academy of Science Lanzhou China;Lanzhou Central Meteorological Observatory Lanzhou China;

关键词: land surface model;    soil thermal conductivity;    soil moisture;    soil temperature;    Tibetan Plateau;   

DOI  :  10.1029/2021MS002670

来源: DOAJ

【 摘 要 】

Abstract Soil water and heat transfer is especially complicated during the freezing and thawing processes over the high‐altitude cold regions. In this study, four sensitivity tests of soil water and heat transfer parameterizations including replacing soil property data (SP1), soil resistance scheme modification (SP2), soil thermal conductivity scheme (SP3) and virtual temperature scheme (SP4), and four combination experiments (SP1+SP2+SP3/SP5, SP1+SP2+SP4/SP6, SP1+SP3+SP4/SP7, and SP1+SP2+SP3+SP4/SP8) were done using Community Land Model (CLM5.0) to examine its performances for soil water and heat transfer modeling on the Tibetan Plateau (TP) both in single‐point and regional simulations. The observed data from five eddy covariance sites, four soil moisture and temperature networks and 60 sites of soil temperature observations on the TP were used to evaluate the results. Single‐point simulations show that SP2 experiment reduced the wet biases of soil moisture in semiarid area, but enhanced the error of soil temperature. SP6 shows the best performances in simulating soil moisture, and SP3 in soil temperature. Regional simulations show that the SP7 experiment had the best performances for soil water and heat transfer simulation on the TP, and improved the simulation of soil freezing‐thawing processes. Compared to CLM5.0 default simulation, SP7 shows the best performances. For soil moisture, it reduced average Bias by 23%, Root Mean Square Error (RMSE) by 18%, and increased the Correlation Coefficient (Corr) by2%. For soil temperature, it reduced the Bias by 9%, 10%, 23%, and 13% at four soil depths on the TP, respectively.

【 授权许可】

Unknown