Sensitivity of simulated mesoscale convective systems over East Asia to the treatment of convection in a high-resolution GCM

Abstract

Mesoscale convective systems (MCSs) downstream of the Tibetan Plateau (TP) exhibit unique precipitation features. These MCSs can have damaging impacts and there is a critical need for improving the representation of MCSs in numerical models. However, most global climate models are typically run at resolutions that are too coarse to reasonably resolve MCSs, and it is still unclear how well higher-resolution global models can reproduce the precipitation characteristics of MCSs. In this study, the sensitivity of MCSs simulated by a global high resolution (~ 10 km), atmosphere-only climate model to different treatments of convection (with and without parametrized convection, and a hybrid representation of convection) have been investigated. The results show that explicit convection (i.e., non-parameterized) can better reproduce the observed pattern of MCS precipitation over the East Asian Summer Monsoon region. In general, explicit convection better simulates the diurnal variability of MCSs over the eastern China, and is able to represent the distinctive diurnal variations of MCS precipitation over complex terrain particularly well, such as the eastern TP and the complex terrain of central-northern China. It is shown that explicit convection is better at simulating the timing of initiation and subsequent propagating features of the MCS, resulting in better diurnal variations and further a better spatial pattern of summer mean MCS precipitation. All three experiments simulate MCS rainfall areas which are notably smaller than those in observations, but with much stronger rainfall intensities, implying that these biases in simulated MCS morphological characteristics are not sensitive to the different treatment of convection.

Realistic Precipitation Diurnal Cycle in Global Convection‐Permitting Models by Resolving Mesoscale Convective Systems

“…With grid spacings of a few kilometers, CPMs can explicitly resolve deep convection, offering the potential for more reliable climate simulations (Bauer et al., 2021; Slingo et al., 2022; Stevens et al., 2019). Many studies have found that CPMs have better performance in simulating many aspects of MCSs, such as duration, propagation, and heavy precipitation (e.g., Ban et al., 2014; X. Chen et al., 2021; Feng et al., 2018; Gao et al., 2017; Li et al., 2023; Na et al., 2022; Prein et al., 2017, 2024; Zhang et al., 2021). However, these studies mostly investigated MCSs regionally using simulations from one or two CPMs.…”

“…Many studies have found that CPMs have better performance in simulating many aspects of MCSs, such as duration, propagation, and heavy precipitation (e.g., Ban et al, 2014;X. Chen et al, 2021;Feng et al, 2018;Gao et al, 2017;Li et al, 2023;Na et al, 2022;Prein et al, 2017Prein et al, , 2024Zhang et al, 2021). However, these studies mostly investigated MCSs regionally using simulations from one or two CPMs.…”

Impact of Convection‐Permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties Over East Asia

“…In recent years, convection‐permitting models (CPMs) have flourished due to the dramatic improvements in computer performance, making it possible to explicitly simulate convection on a large scale and over long periods of time. These models have been shown to outperform traditional convection‐parameterized models (CParMs) in accurately simulating the properties of MCSs and their related environments (Li et al., 2022; Prein et al., 2017; Yun et al., 2020). For example, Zhang et al.…”

“…In recent years, convection-permitting models (CPMs) have flourished due to the dramatic improvements in computer performance, making it possible to explicitly simulate convection on a large scale and over long periods of time. These models have been shown to outperform traditional convection-parameterized models (CParMs) in accurately simulating the properties of MCSs and their related environments (Li et al, 2022;Prein et al, 2017;Yun et al, 2020). For example, Zhang et al (2013) investigated the causes of the Beijing extreme rainfall of 21 July 2012, which was triggered by a prolonged MCS event, and concluded that the simulation using CPMs was critical to capture the details of the complex meteorological and hydrological processes.…”