Existing studies have shown that observed surface incident solar radiation (R s ) over China may have important inhomogeneity issues. This study provides metadata and reference data to homogenize observed R s , from which the decadal variability of R s over China can be accurately derived. From 1958 to 1990, diffuse solar radiation (R sdif ) and direct solar radiation (R sdir ) were measured separately, and R s was calculated as their sum. The pyranometers used to measure R sdif had a strong sensitivity drift problem, which introduced a spurious decreasing trend into the observed R sdif and R s data, whereas the observed R sdir did not suffer from this sensitivity drift problem. From 1990 to 1993, instruments and measurement methods were replaced and measuring stations were restructured in China, which introduced an abrupt increase in the observed R s . Intercomparisons between observation-based and model-based R s performed in this research show that sunshine duration (SunDu)-derived R s is of high quality and can be used as reference data to homogenize observed R s data. The homogenized and adjusted data of observed R s combines the advantages of observed R s in quantifying hourly to monthly variability and SunDu-derived R s in depicting decadal variability and trend. R s averaged over 105 stations in China decreased at À2.9 W m À2 per decade from 1961 to 1990 and remained stable afterward. This decadal variability is confirmed by the observed R sdir and diurnal temperature ranges, and can be reproduced by high-quality Earth System Models. However, neither satellite retrievals nor reanalyses can accurately reproduce such decadal variability over China.

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Ground-based observations of surface incident solar radiation (R s ) have been used to evaluate simulations of global climate models. Existing studies have shown that biases in simulated clouds have a significant spatial pattern, which may be transferred to the simulated R s . Therefore, the evaluation results of R s simulations may depend on the locations of the ground-based observations. In this study, R s simulations of 48 models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) were first evaluated with ground-based observations from different networks (446 stations in total) from 2000 to 2005. The global mean biases of the CMIP5 R s simulations were found to vary from 4.8 to 11.9 W m À2 when R s observations from different networks were used as reference data. To reduce the location impact on the evaluation results, CMIP5 simulated R s was then evaluated with the latest satellite R s retrieval at 1°× 1°spatial resolution by the Clouds and the Earth's Radiant Energy System, Energy Balanced and Filled (CERES EBAF). It was found that the CMIP5 simulated multimodel mean R s has a small bias of 2.

Land surface temperature Ts provides essential supplementary information to surface air temperature, the most widely used metric in global warming studies. A lack of reliable observational Ts data makes assessing model simulations difficult. Here, the authors first examined the simulated Ts of eight current reanalyses based on homogenized Ts data collected at ~2200 weather stations from 1979 to 2003 in China. The results show that the reanalyses are skillful in simulating the interannual variance of Ts in China (r = 0.95) except over the Tibetan Plateau. ERA-Interim and MERRA land versions perform better in this respect than ERA-Interim and MERRA. Observations show that the interannual variance of Ts over the north China plain and south China is mostly influenced by surface incident solar radiation Rs, followed by precipitation frequency, whereas the opposite is true over the northwest China, northeast China, and the Tibetan Plateau. This variable relationship is well captured by ERA-Interim, ERA-Interim land, MERRA, and JRA-55. The homogenized Ts data show a warming of 0.34°C decade−1 from 1979 to 2003 in China, varying between 0.25° and 0.42°C decade−1 for the eight reanalyses. However, the reanalyses substantially underestimate the warming trend of Ts over northwest China, northeast China, and the Tibetan Plateau and significantly overestimate the warming trend of Ts over the north China plain and south China owing to their biases in simulating the Rs and precipitation frequency trends. This study provides a diagnostic method for examining the capability of current atmospheric/land reanalysis data in regional climate change studies.

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