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Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. In this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m−2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m−2, the overestimation of the global radiation still reaches 160.2 W m−2. This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%. Significance Statement: Numerical weather prediction (NWP) is the "go-to" approach for achieving high-performance day-ahead solar power forecasting. Integrating time-varying aerosol forecasts into NWP models effectively captures aerosol direct radiation effects, thereby enhancing the accuracy of solar irradiance forecasts in heavily polluted regions. This work not only quantifies the aerosol effects on global, beam, and diffuse irradiance but also reveals the physical mechanisms of irradiance-to-power conversion by constructing a model chain. Using the North China Plain as a testbed, the performance of WRF-Solar on solar power forecasting on five severe pollution days is analyzed. This version of WRF-Solar can outperform the European Centre for Medium-Range Weather Forecasts model, confirming the need for generating high spatial–temporal NWP. [ABSTRACT FROM AUTHOR]

Precipitation in China is controlled by a combination of multiple weather systems and is susceptible to their spatiotemporal variability under climate warming. Based on the daily precipitation dataset developed by the China Meteorological Administration and ERA5 6-hourly data from 1979 to 2018, we detected tropical cyclones, extratropical cyclones, and fronts affecting mainland China of an altitude less than 1500 m using objective methods and identified their individually associated precipitation. We quantified climatological characteristics of precipitation associated with these three meteorological causes and their proportion of precipitation totals, and evaluated their relative contribution to change in precipitation. Results show that precipitation associated with tropical cyclones (TCP), extratropical cyclones (ETCP), and fronts (FRTP) accounted for 3.0%, 21.2%, and 20.4% of the total precipitation in China, and constituted the largest percentage in August, June, and January, respectively. The total proportion of these three types of precipitation exceeded 50% in more than 55% of China's regions. The high-value regions of corresponding precipitation were directly related to the locations of frequent occurrences of these weather systems. TCP and FRTP increased over the past four decades, while ETCP decreased. The western part of Northeast China and the middle and upper reaches of the Yangtze River show precipitation decreases, 37.8% of which is contributed by ETCP decreases. Precipitation increased in most regions of China during the dry season, 34.1% of which is contributed by FRTP increases. Among them, Northeast (Northwest) China significantly increased it precipitation by 14.4% decade−1 (21.8% decade−1), 33.6% (51.3%) of which is contributed by FRTP increases. [ABSTRACT FROM AUTHOR]

In this study, the total days, mean duration, and intensity of extreme hot events over southern China during the 1971–2020 warm seasons are analyzed on the basis of daily maximum and minimum temperatures, by comparing the newly proposed independent hot day (IHD), independent warm night (IWN), and compound extreme (CMPD; i.e., the continuous occurrences of hot days and hot nights) with the traditionally defined hot day and warm night. Relationships between the hot extremes and urbanization are explored with 1-km-resolution population density data. Results show obvious differences in the spatial distributions among IHD, IWN, and CMPD over southern China. Positive correlations of 0.43, 0.41, and 0.37 are found between the population density and the total days, mean duration, and mean intensity of CMPD, respectively, which are qualitatively similar to those using the traditional hot days and warm nights. In contrast, negative correlations between the IHD and IWN indices and the population density are found, because those indices are more apparent over rural areas. Moreover, total days, mean duration, and mean intensity of CMPD increase significantly, with trends of approximately 103%, 21%, and 38% decade−1, respectively, during the rapid urbanization period from the mid-1990s to 2020, which are about 4.9, 2.1, and 2.4 times their counterparts from 1970 to the mid-1990s, and less significant and smaller differences between the two eras are found in IHD and IWN. These results will provide a new scientific basis for evaluating climate models of hot extremes in southern China and have important implications for the other urbanized regions as well. [ABSTRACT FROM AUTHOR]