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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]

This paper examines variations of the surface air temperature (SAT) over China and the globe in the twentieth century simulated by 19 coupled climate models driven by historical natural and anthropogenic forcings. Most models perform well in simulating both the global and the Northern Hemispheric mean SAT evolutions of the twentieth century. The inclusion of natural forcings improves the simulation, in particular for the first half of the century. The reproducibility of the SAT averaged over China is lower than that of the global and hemispheric averages, but it is still acceptable. The contribution of natural forcings to the SAT over China in the first half of the century is not as robust as that to the global and hemispheric averages. No model could successfully produce the reconstructed warming over China in the 1920s. The prescribed natural and anthropogenic forcings in the coupled climate models mainly produce the warming trends and the decadal- to interdecadal-scale SAT variations with poor performances at shorter time scales. The prominent warming trend in the last half of the century over China and its acceleration in recent decades are weakly simulated. There are discrepancies between the simulated and observed regional features of the SAT trend over China. Few models could produce the summertime cooling over the middle part of eastern China (27°–36°N), while two models acceptably produce the meridional gradients of the wintertime warming trends, with north China experiencing larger warming. Limitations of the current state-of-the-art coupled climate models in simulating spatial patterns of the twentieth-century SAT over China cast a shadow upon their capability toward projecting credible geographical distributions of future climate change through Intergovernmental Panel on Climate Change (IPCC) scenario simulations. [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]

Abstract: In this paper, we introduce the research on atmospheric corrosion in China. We describe the climate characteristics and the classification of atmospheric corrosivity across the whole country. We also describe the rusting evolution under simulated wet/dry cyclic conditions. [Copyright &y& Elsevier]

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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]

Precipitation accumulations, integrated over rainfall events, are investigated using hourly data across continental China during the warm season (May–October) from 1980 to 2015. Physically, the probability of precipitation accumulations drops slowly with event size up to an approximately exponential cutoff scale sL where probability drops much faster. Hence sL can be used as an indicator of high accumulation percentiles (i.e., extreme precipitation accumulations). Overall, the climatology of sL over continental China is about 54 mm. In terms of cutoff changes, the current warming stage (1980–2015) is divided into two periods, 1980–97 and 1998–2015. We find that the cutoff in 1998–2015 increases about 5.6% compared with that of 1980–97, with an average station increase of 4.7%. Regionally, sL increases are observed over East China (10.9% ± 1.5%), Northwest China (9.7% ± 2.5%), South China (9.4% ± 1.4%), southern Southwest China (5.6% ± 1.2%), and Central China (5.3% ± 1.0%), with decreases over North China (−10.3% ± 1.3%), Northeast China (−4.9% ± 1.5%), and northern Southwest China (−3.9% ± 1.8%). The conditional risk ratios for five subregions with increased cutoff sL are all greater than 1.0, indicating an increased risk of large precipitation accumulations in the most recent period. For high precipitation accumulations larger than the 99th percentile of accumulation s99, the risk of extreme precipitation over these regions can increase above 20% except for South China. These increases of extreme accumulations can be largely explained by the extended duration of extreme accumulation events, especially for "extremely extreme" precipitation greater than s99. [ABSTRACT FROM AUTHOR]

A total of 290 tree-ring samples, collected from six sites in the West Qinling Mountains of China, were used to develop six new standard tree-ring chronologies. In addition, 73 proxy records were assembled in collaboration with Chinese and international scholars, from 27 publically available proxy records and 40 tree-ring chronologies that are not available in public datasets. These records were used to reconstruct annual mean temperature variability in the West Qinling Mountains over the past 500 years (AD 1500–1995), using a modified point-by-point regression (hybrid PPR) method. The results demonstrate that the hybrid PPR method successfully integrates the temperature signals from different types of proxies, and that the method preserves a high degree of low-frequency variability. The reconstruction shows greater temperature variability in the West Qinling Mountains than has been found in previous studies. Our temperature reconstruction for this region shows: 1) five distinct cold periods, at approximately AD 1520–1535, AD 1560–1575, AD 1610–1620, AD 1850–1875 and AD 1965–1985, and four warm periods, at approximately AD 1645–1660, AD 1705–1725, AD 1785–1795 and AD 1920–1945; 2) that in this region, the 20th century was not the warmest period of the past 500 years; and 3) that a dominant and persistent oscillation of ca. 64 years is significantly identified in the 1640–1790 period. [ABSTRACT FROM AUTHOR]