The East Asian Summer Monsoon Response to Global Warming in a High Resolution Coupled Model: Mean and Extremes

Abstract

Current climate models still have considerable biases in the simulation of the East Asian summer monsoon (EASM), which in turn reduces their reliability of monsoon projections under global warming. We hypothesize that a higher-resolution coupled climate model with atmospheric and oceanic components at horizontal resolutions of 0.25° and 0.1°, respectively, will better capture regional details and extremes of the EASM. Present-day (PD), 2 × CO2 and 4 × CO2 simulations are conducted with the Community Earth System Model (CESM1.2.2) to evaluate PD simulation performance and quantify future changes. Indeed, our PD simulation well reproduces the climatological seasonal mean and intra-seasonal northward advancement of the monsoon rainband, as well as climate extremes. Compared with the PD simulation, the perturbed CO2 experiments show an intensified EASM response to CO2-induced warming. We find that the precipitation increases of the Meiyu-Baiu-Changma band are caused by comparable contributions from the dynamical and thermodynamical components in 2 × CO2, while they are more driven by the thermodynamical component in 4 × CO2 due to stronger upper atmospheric stability. The regional changes in the probability distribution of the temperature show that extreme temperatures warm faster than the most often temperatures, increasing the skewness. Fitting extreme precipitation values with a generalized Pareto distribution model reveals that they increase significantly in 4 × CO2. Changes of temperature extremes scale with the CO2 concentrations over the monsoon domain but not for precipitation extreme changes. The 99th percentile of precipitation over the monsoon region increases at a super Clausius-Clapeyron rate, ~ 8% K–1, which is mainly caused by increased moisture transport through anomalous southerly winds.

Extreme Weather and Climate Events: Dynamics, Predictability and Ensemble Simulations

“…Wang et al (2023) describe the microphysical structures of an extreme rainfall event in China. On larger scales Liu et al (2023) describe changes to precipitation extremes and the East Asian monsoon in high-resolution global warming simulations and demonstrate the advantage of high-resolution modeling by reducing biases. Cadiou et al (2023) attempt to attribute a rain bomb.…”

“…Extreme weather and climate events have significant impacts on society and the economy (Lee et al 2022;Oh et al 2022;Ranalkar et al 2022;Shelton et al 2022;Zhao et al 2022). These events are also projected to become more intense and frequent in a globally warmer world Liu et al 2023). Together with many socio-economic changes, this means that the associated risks are changing and likely are increasing.…”

Impact of greenhouse warming on mesoscale eddy characteristics in high-resolution climate simulations

“…The CESM 1.2.2 ultra-high-resolution climate simulation project, known as CESM-UHR, aims to advance our understanding of multi-scale interactions and processes associated with extreme weather and climate in the context of greenhouse warming (Chu et al 2020, Huang et al 2021, Wengel et al 2021, Kad et al 2023, Liu et al 2023, Moon et al 2023 Three century-long experiments were conducted using CESM-UHR to assess the impact of anthropogenic greenhouse warming on surface mesoscale eddy characteristics. Figure S1a shows a diagram of the CESM-UHR climate experiments used in this study.…”

Impact of Asian aerosols on the summer monsoon strongly modulated by regional precipitation biases

“…Yet, despite considerable efforts, simulating the monsoon remains a long-standing challenge for climate models as some biases have persisted for decades, such as the deficient rainfall over central India and excess wetting over eastern China (Sperber et al, 2013;Liu et al, 2021). The existence of these large and widespread biases not only decreases the confidence in the modelled monsoon and associated physical mechanisms (Yang et al, 2019;Jiang et al, 2020;Rajendran et al, 2022;Liu et al, 2022) but also represents a major cause of the large inter-model spread in historical monsoon evolution (Zhou et al, 2019;Guilbert et al, 2023). Moreover, these biases are likely to hinder reliable monsoon projections with critical implications for water management and planning across Asia and subsequent impacts on agriculture and economy (Zhou et al, 2019;Cao et al, 2020;Wang et al, 2020;Pillai et al, 2021).…”