Abstract. The recent release of the International Satellite Cloud
Climatology Project (ISCCP) HXG cloud products and new ERA5 reanalysis data
enabled us to produce a global surface solar radiation (SSR) dataset: a
16-year (2000–2015) high-resolution (3 h, 10 km) global SSR dataset using an
improved physical parameterization scheme. The main inputs were cloud
optical depth from ISCCP-HXG cloud products; the water vapor, surface
pressure and ozone from ERA5 reanalysis data; and albedo and aerosol from
Moderate Resolution Imaging Spectroradiometer (MODIS) products. The
estimated SSR data were evaluated against surface observations measured at 42 stations of the Baseline Surface Radiation Network (BSRN) and 90 radiation
stations of the China Meteorological Administration (CMA). Validation
against the BSRN data indicated that the mean bias error (MBE), root mean
square error (RMSE) and correlation coefficient (R) for the instantaneous SSR
estimates at 10 km scale were −11.5 W m−2, 113.5 W m−2 and 0.92,
respectively. When the estimated instantaneous SSR data were upscaled to 90 km, its error was clearly reduced, with RMSE decreasing to 93.4 W m−2
and R increasing to 0.95. For daily SSR estimates at 90 km scale, the MBE,
RMSE and R at the BSRN were −5.8 W m−2, 33.1 W m−2 and 0.95,
respectively. These error metrics at the CMA radiation stations were 2.1 W m−2, 26.9 W m−2 and 0.95, respectively. Comparisons with other
global satellite radiation products indicated that our SSR estimates were
generally better than those of the ISCCP flux dataset (ISCCP-FD), the global
energy and water cycle experiment surface radiation budget (GEWEX-SRB), and
the Earth's Radiant Energy System (CERES). Our SSR dataset will contribute
to the land-surface process simulations and the photovoltaic applications in
the future. The dataset is available
at https://doi.org/10.11888/Meteoro.tpdc.270112 (Tang, 2019).
High-Resolution Numerical Simulation of Surface Wave Development under the Action of Wind