Top‐of‐Atmosphere Radiation Budget and Cloud Radiative Effects Over the Tibetan Plateau and Adjacent Monsoon Regions From CMIP6 Simulations

Abstract

This study investigates the top‐of‐atmosphere (TOA) radiation budget (RT) and cloud radiative effects (CREs) over the Tibetan Plateau (TP) and adjacent Asian monsoon regions including Eastern China (EC) and South Asia (SA) using the Coupled Model Intercomparison Project 6 (CMIP6) simulations. Considerable simulation biases occur but specific causes differ in these regions. Most models underestimate the intensity of annual mean RT and cloud radiative cooling effect over the TP, and the RT during the cold‐warm transition period is hard to capture. The biases in surface temperature and cloud fractions substantially contribute to cloud‐radiation biases over the western and eastern TP, respectively. Over EC, the intensity of RT and cloud radiative cooling effect is seriously underestimated especially in the springtime when the model spread is large, and their biases are closely related to less low‐middle cloud fractions and weaker ascending motion. Over SA, simulation biases mainly arise from longwave radiative components associated with less high cloud fraction and weaker convection, with the large model spread in the summertime. The annual cycles of RT and CREs over EC and SA can be well reproduced by most models, while the summertime peak of the net CRE over the TP occurs later than the observation. The RT and its simulation bias strongly depend on the cloud radiative cooling effect over EC and SA. Our results demonstrate that contemporary climate models still have obvious difficulties in representing various complex cloud‐radiation processes in Asian monsoon regions.

Evaluation of Simulated Cloud Diurnal Variation in CMIP6 Climate Models

“…To date, models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6; Eyring et al, 2016) are representative of the state-of-the-art climate models in the world. While many studies have been devoted to examining the simulated daily mean cloud properties and associated radiative effects in various regimes (e.g., Li et al, 2021;Miao et al, 2021;Smith et al, 2020;Vignesh et al, 2020;Wei et al, 2021;Zhao et al, 2021), none is focused on cloud diurnal cycle to our best knowledge. Given the above considerations, the present study adopted our previous approach (Chen & Wang, 2016b) which proposed using the ratio of "effective-daytime cloud fraction" (the cloud fraction weighting averaged with solar diurnal cycle) to the conventional daily mean cloud fraction, to evaluate the CDV simulation in CMIP6 models.…”

Understanding Surface Air Temperature Cold Bias Over China in CMIP6 Models

“…Furthermore, better simulation of SAT in South China and the mountainous regions also benefits from more reliable cloud fraction and surface albedo, respectively. The sources of cloud simulation biases in South China can be further investigated by the reanalyzed meteorological and satellite‐retrieved data in order to improve the associated physical processes in models (J. Li, Sun, et al., 2021), and the surface albedo biases related to snow‐albedo parameterization can be improved by detailed canopy‐snow processes and thus accurately described land cover parameters (Qu & Hall, 2007; L. Wang et al., 2016).…”

An Integrated Research Plan for the Tibetan Plateau Land–Air Coupled System and Its Impacts on the Global Climate

“…In addition, the precipitation bias on the southern slope of the TP has been further reduced by approximately 30% (Bao and Li 2020;He et al 2019a). The probability distribution characteristics of extreme hourly precipitation in slope areas and the diurnal cycles of precipitation in the Asian monsoon region are simulated better in FGOALS-f3-H than most CMIP6 models (He et al 2019c;Li et al 2021b;Chen et al 2022). Intercomparison Project (HighResMIP) (He et al 2020;Bao et al 2020).…”