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.
Highlights
Surface incident shortwave radiation (SSR) is an important parameter in many atmospheric, oceanic, and land process models [1], and a critical ingredient in energy exchanges between the Earth’s surface and the atmosphere [2]
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 ensemble SSR estimations generated by the SMA and BMA methods were superior to all individual general circulation models (GCMs) 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
Summary
Surface incident shortwave radiation (SSR) is an important parameter in many atmospheric, oceanic, and land process models [1], and a critical ingredient in energy exchanges between the Earth’s surface and the atmosphere [2]. The root mean squared errors (RMSEs) of the annual average SSR ranged from 18.3 W m−2 to 35.2 W m−2 among the GCMs with respect to the 760 GEBA sites These studies indicated that large uncertainties in the simulated SSR exist among the GCMs, and GCMs exhibit systematic bias, i.e., the simulated SSR values are usually greater than the observed values. It was found that the differences in physical basis, parameterization schemes, and coupling schemes were the major reason for various uncertainties in climate change [12]
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