Evaluation of Bayesian Multimodel Estimation in Surface Incident Shortwave Radiation Simulation over High Latitude Areas

Abstract

Surface incident shortwave radiation (SSR) is crucial for understanding the Earth’s climate change issues. Simulations from general circulation models (GCMs) are one of the most practical ways to produce long-term global SSR products. Although previous studies have comprehensively assessed the performance of the GCMs in simulating SSR globally or regionally, studies assessing the performance of these models over high-latitude areas are sparse. This study evaluated and intercompared the SSR simulations of 48 GCMs participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) using quality-controlled SSR surface measurements at 44 radiation sites from three observation networks (GC-NET, BSRN, and GEBA) and the SSR retrievals from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF) data set over high-latitude areas from 2000 to 2005. Furthermore, this study evaluated the performance of the SSR estimations of two multimodel ensemble methods, i.e., the simple model averaging (SMA) and the Bayesian model averaging (BMA) methods. The seasonal performance of the SSR estimations of individual GCMs, the SMA method, and the BMA method were also intercompared. The evaluation results indicated that there were large deficiencies in the performance of the individual GCMs in simulating SSR, and these GCM SSR simulations did not show a tendency to overestimate the SSR over high-latitude areas. Moreover, the ensemble SSR estimations generated by the SMA and BMA methods were superior to all individual GCM SSR simulations over high-latitude areas, and the estimations of the BMA method were the best compared to individual GCM simulations and the SMA method-based estimations. Compared to the CERES EBAF SSR retrievals, the uncertainties of the SSR estimations of the GCMs, the SMA method, and the BMA method are relatively large during summer.

Development of high‐resolution monthly precipitation datasets for geomorphological applications in the Tianshan Mountains from 2000 to 2050

“…In this study, we resampled the five CMIP5 models (Table 1) to the same spatial resolution (2.83° × 2.83°) using a bilinear interpolation algorithm and then averaged the five models based on the simple model averaging method. Similarly, we resampled the 11 CMIP6 models (Table 2) to the same spatial resolution (1.41° × 1.41°) and then also averaged them (Xu et al, 2022; Zhang, Zhang, et al, 2019).…”

Characteristics of the Reanalysis and Satellite-Based Surface Net Radiation Data in the Arctic

“…BSRN, initiated in 1992 through the World Climate Research Programme (WCRP), was designed in 2004 to be a global baseline network of surface radiant energy for the Global Climate Observing System (GCOS). It also contributes to the Global Atmosphere Watch program by providing high-quality data from a variety of climatic zones [47][48][49]. The Swiss Federal Institute of Technology (ETH) sources ETH/Greenland Summit (SMT) data that belongs to the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS) project.…”