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 - Zhang, Shaojing; Xu, Feng; Xue, Yufeng; Xu, Daosheng; Leung, Jeremy Cheuk-Hin; Han, Liguo; Yang, Jinyi; Zheng, Meiying; Li, Yongchi; Huang, Fei; Zhang, Banglin (Frontiers in Earth Science, 2023)
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.