Evaluating and improving simulations of diurnal variation in land surface temperature with the Community Land Model for the Tibetan Plateau

PeerJ

article

Xiaogang Ma¹  Jiming Jin¹  Lingjing Zhu³  Jian Liu¹ 

[1] Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F Universtiy, Yangling, Shaanxi Province;College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi Province;South China Sea Institute of Marine Meteorology & College of Ocean and Meteorology, Guangdong Ocean University;Southern Marine Science and Engineering Guangdong Laboratory

关键词: Community land model version 5.0;    Land surface temperature;    Tibetan Plateau;    Sensible heat roughness length;    Soil thermal conductivity;    Soil evaporation resistance;   

DOI  :  10.7717/peerj.11040

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

This study evaluated and improved the ability of the Community Land Model version 5.0 (CLM5.0) in simulating the diurnal land surface temperature (LST) cycle for the whole Tibetan Plateau (TP) by comparing it with Moderate Resolution Imaging Spectroradiometer satellite observations. During daytime, the model underestimated the LST on sparsely vegetated areas in summer, whereas cold biases occurred over the whole TP in winter. The lower simulated daytime LST resulted from weaker heat transfer resistances and greater soil thermal conductivity in the model, which generated a stronger heat flux transferred to the deep soil. During nighttime, CLM5.0 overestimated LST for the whole TP in both two seasons. These warm biases were mainly due to the greater soil thermal inertia, which is also related to greater soil thermal conductivity and wetter surface soil layer in the model. We employed the sensible heat roughness length scheme from Zeng, Wang & Wang (2012), the recommended soil thermal conductivity scheme from Dai et al. (2019), and the modified soil evaporation resistance parameterization, which was appropriate for the TP soil texture, to improve simulated daytime and nighttime LST, evapotranspiration, and surface (0–10 cm) soil moisture. In addition, the model produced lower daytime LST in winter because of overestimation of the snow cover fraction and an inaccurate atmospheric forcing dataset in the northwestern TP. In summary, this study reveals the reasons for biases when simulating LST variation, improves the simulations of turbulent fluxes and LST, and further shows that satellite-based observations can help enhance the land surface model parameterization and unobservable land surface processes on the TP.

【 授权许可】

CC BY