文献类型：期刊文献

英文题名：Heat balance characteristics in the South China Sea and surrounding areas simulated using the TRAMS model-a case study of a summer heavy rain and a winter cold spell

作者：Zhang, Shaojing[1,2,3];Xu, Feng[1,2];Xue, Yufeng[1,2];Xu, Daosheng[3];Leung, Jeremy Cheuk-Hin[3];Han, Liguo[1,2];Yang, Jinyi[1,2];Zheng, Meiying[1,2];Li, Yongchi[1,2];Huang, Fei[4];Zhang, Banglin[3]

机构：[1]Guangdong Ocean Univ, Coll Ocean & Meteorol, Zhanjiang, Peoples R China;[2]Guangdong Ocean Univ, South China Sea Inst Marine Meteorol, Zhanjiang, Peoples R China;[3]Guangzhou Inst Trop & Marine Meteorol, Guangdong Prov Key Lab Reg Numer Weather Predict, Guangzhou, Peoples R China;[4]Zhuhai Meteorol Bur, Zhuhai, Guangdong, Peoples R China

年份：2023

卷号：10

外文期刊名：FRONTIERS IN EARTH SCIENCE

收录：SCI-EXPANDED(收录号：WOS:000949165000001)、、WOS

基金：This study was supported by the Special Project for Research and Development in Key area of Guangdong Province (Grant 2020B0101130021) and the National Key Research and Development Program of China (Grant 2018YFC1506902).

语种：英文

外文关键词：model diagnosis; forecast tendencies; thermal equilibrium; systematic bias; physical parameterization

外文摘要：Introduction: This study is first to apply d iagnostic analysis of the forecast tendencies to evaluate the simulation of equilibrium features in the South China Sea and its surrounding areas using The Tropical Regional Atmosphere (TRAMS) model, and further identify the sources of simulation biases of the model.Methods: On the basis of the quasi equilibrium between dynamic and physical processes, the deviation of net forecast tendencies, which reflects the overall equilibrium of the model, serves as a good indicator of the model simulations bias. The sources of the forecast error can be further inferred by decomposing the net forecast tendencies into the dynamic and each physical process.Results: Focusing on moisture and temperature tendencies, the results show that the TRAMS model generally captures the thermal equilibrium characteristics and the contributions of each physical process, which are markedly different between summer and winter and are affected by the Northwest Pacific Subtropical High (WPSH) and deep trough of East Asia respectively. Furthermore, the underestimation of vapour consumption by cloud microphysical parameterisation and the overestimation of sea surface heat flux by boundary layer parameterisation near the surface contribute the most to systematic model bias. The temperature bias from 900 to 300 hPa during winter mainly originates from the responses of radiation, cumulus convection, and cloud microphysical parameterisations because water vapour absorbs long wave radiation, heating the atmosphere, and clouds reduce short wave radi ation absorption, cooling it.Discussion: The presented analyses provide a reference for further optimisation and improvement of the model.