Brown carbon (BrC) has been recognized as an important light-absorbing carbonaceous aerosol, yet understanding of its influence on regional climate and air quality has been lacking, mainly due to the ignorance of regional coupled meteorology-chemistry models. Besides, assumptions about its emissions in previous explorations might cause large uncertainties in estimates. Here, we implemented a BrC module into the WRF-Chem model that considers source-dependent absorption and avoids uncertainties caused by assumptions about emission intensities. To our best knowledge, we made the first effort to consider BrC in a regional coupled model. We then applied the developed model to explore the impacts of BrC absorption on radiative forcing, regional climate, and air quality in East Asia. We found notable increases in aerosol absorption optical depth (AAOD) in areas with high OC concentrations. The most intense forcing of BrC absorption occurs in autumn over Southeast Asia, and values could reach around 4 W m(-2). The intensified atmospheric absorption modified surface energy balance, resulting in subsequent declines in surface temperature, heat flux, boundary layer height, and turbulence exchanging rates. These changes in meteorological variables additionally modified near-surface dispersion and photochemical conditions, leading to changes of PM2.5 and O-3 concentrations. These findings indicate that BrC could exert important influence in specific regions and time periods. A more in-depth understanding could be achieved later with the developed model.

China experiences severe particulate matter (PM) pollution. Although a monitoring network for PM2.5 (diameter < 2.5 mu m) has been set up in more than 100 major Chinese cities, insufficient spatial coverage of observations limits the study of the temporal and spatial characteristics, influencing factors, and component of PM2.5. In this study, we conducted a one year air quality simulation using a regional climate-chemistry model and evaluated the simulation's performance based on in situ observations concerning meteorological elements and PM2.5 concentrations. The simulated results showed that, higher PM2.5 concentrations appeared in northern China and the Sichuan Basin, and the maximal value occurred in winter. Furthermore, Vertical PM2.5 concentrations presented a gradual decreasing trend from the surface, whereas in southern coastal cities the profiles were unsteady with a secondary peak in the lower layer. Meteorological conditions were conducive to both pollutant diffusion and removal in summer, whereas stagnant conditions appeared in winter, characterized by high sea level pressure (SLP), the lowest planetary boundary layer height (PBLH), and 2-m temperature (T2). In provincial capital cities, PM2.5 was positively correlated with residential emissions but negatively correlated with precipitation, 10-m wind speed, T2, PBLH, and industrial emissions. Finally, we utilized the simulation results to investigate the component variations of PM2.5. Results indicated that primary PM2.5 components had significantly higher concentrations in northern China where residential heating is the major source of PM2.5 emissions, whereas they had lower concentrations in southern China. Secondary components played a crucial role in PM2.5 mass in eastern China. This study provided a clear perspective of seasonal variations, horizontal and vertical distributions of PM2.5 and its components and influence factors, which could be used in subsequent studies to investigate the formation mechanism and emission sources of PM2.5.

Alpine areas play a substantial role in supplying the world's water resources. The hydrological cycle in these areas has been experiencing notable alterations owing to climate change. However, the present comprehension of how water yield capacity (WYC) responds to climate change at varying elevations within alpine basins is impeded due to the complex terrain and simplified representation of coupled water-energy processes in traditional hydrological models. Through integrating the Weather Research and Forecasting hydrological modeling system (WRF-Hydro) and Budyko framework, this study quantitatively assessed the influence of climate change on WYC across different elevations in a Tibetan Plateau alpine basin, named Xiying River Basin (XRB). The results indicated the WRF-Hydro adeptly reproduced the streamflow and evapotranspiration (ET) within the XRB. The combination of the WRF-Hydro model allows the Budyko framework, traditionally limited to the watershed scale, to be applicable at the grid scale. We found that the XRB underwent substantial climate change from 1980 to 2015, and there existed an abrupt change in 1997. Climate change caused the WYC reduced by -17.06% during the post-1997 period (1998-2015), compared to the pre-1997 period (1980-1997). Additionally, all elevation bands displayed the WYC reductions, ranging from -3.69% to -24.31%, with diminishing magnitude at higher elevations. This WYC reduction is primarily attributed to an increase of 11.38% in ET. Although ET and precipitation increased with elevation, the former consistently exceeded the latter, resulting in decreasing water deficits and an altitudinal gradient of the WYC reduction. Besides the increasing vapor pressure deficit and decreasing albedo, our findings emphasized the significance of precipitation event timing in influencing WYC. The longer time intervals between precipitation events in the XRB led to more soil moisture loss through ET. These findings shed valuable implications for policymakers, offering guidance for the formulation of sustainable policies for water resource management and ecological conservation.

Tropical cyclone (TC) Amphan is analyzed in terms of the various factors that governed the intensification process associated with it and compared with Fani. Furthermore, the TC radial characteristics and ocean productivity are examined. Notably, both TCs formed in the Bay of Bengal during the pre-monsoon seasons of 2020 and 2019, respectively. For this study, both ocean and atmospheric parameters from various sources including global analyses, satellite observations, and outputs from Model for Prediction Across Scales-Atmosphere (MPAS-A) and Advanced Research Weather Research and Forecasting (WRF-ARW), are considered. The results indicate a gradual decrease in vertical wind shear during Fani. In the case of Amphan, the increase in mid-tropospheric relative humidity values is found to be substantial. The sea surface cooling after the passage of Amphan was higher than in the case of Fani. The higher sea surface temperature in the Amphan case corresponds to the lower aerosol loading (partly because of lockdown measures) than that of Fani in the pre-cyclone phase. And the decrease (increase) in aerosol loading coincides with an increase (decrease) in the direct radiative forcing at the ocean surface. The Madden-Julian Oscillation played a greater role in the cyclogenesis of Fani, but Kelvin waves offered a major support in the case of Amphan. The warmer sea surface, higher tropical cyclone heat potential, and conducive ocean and atmospheric setting together supported the further intensification of Amphan to the supercyclone stage. The difference in chlorophyll concentration showed a significant variation, with higher positive values seen in the case of Amphan implicating greater vertical mixing. The numerical modeling effort indicated superior performance of MPAS-A compared to WRF-ARW in simulating the radial parameters of the TCs.

The lockdowns implemented during the coronavirus disease 2019 (COVID-19) pandemic provide a unique opportunity to investigate the impact of emission sources and meteorological conditions on the trans-boundary transportation of black carbon (BC) aerosols to the Tibetan Plateau (TP). In this study, we conducted an integrative analysis, including in-situ observational data, reanalysis datasets, and numerical simulations, and found a significant reduction in the trans-boundary transport of BC to the TP during the 2020 pre-monsoon season as a result of the lockdowns and restrictive measures. Specifically, we observed a decrease of 0.0211 mu g m- 3 in surface BC concentration over the TP compared to the 2016 pre-monsoon period. Of this reduction, approximately 6.04 % can be attributed to the decrease in emissions during the COVID-19 pandemic, surpassing the 4.47 % decrease caused by changes in meteorological conditions. Additionally, the emission reductions have weakened the transboundary transport of South Asia BC to the TP by 0.0179 mu g m � 2s 1; indicating that the recurring spring atmospheric pollution from South Asia to the TP will be alleviated through the reduction of anthropogenic emissions. Moreover, it is important to note that BC deposition on glaciers contributes significantly to glacier melting due to its enrichment, posing a threat to the water sustainability of the TP. Therefore, urgent measures are needed to reduce emissions from adjacent regions to preserve the TP as the Asian Water Tower.

In this study, in situ observations were conducted for six criteria air pollutants (PM2.5, PM10, SO2, NO2, CO, and O-3) at 23 sites in western China for 1 year. Subsequently, the detailed Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) results for the pollutants were determined. The WRF-Chem model provided a clear perspective on the spatiotemporal distribution of air pollutants. High pollutant concentrations were mainly observed over highly populated mega-city regions, such as Sichuan and Guanzhong basins, whereas low concentration levels were observed over the Tibetan Plateau (TP). The TP also showed an increased concentration of O-3. Seasonally, all six pollutants except O-3 exhibited high concentration values during winter and low values during summer. O-3 concentrations exhibited an opposite seasonal variation in low-altitude regions. Unlike other pollutants that exhibited gradually decreasing concentrations with an increase in altitude, O-3 concentrations revealed an increasing trend. Furthermore, NO2 concentrations gradually increased in the upper atmosphere possibly due to lighting and stratospheric transmission. Atmospheric pollution is closely related to emissions and meteorological variations in western China. Meteorological conditions in the summer are conducive to pollutant dispersion and wet scavenging; however, unfavourable weather conditions (high pressure as well as a low planetary boundary layer height and precipitation level) in the winter can further worsen air pollution. Atmospheric pollutants from various emission sectors generally exhibited varying monthly profiles. In six typical cities, pollutants were positively correlated with multiple emission sources except for industrial emissions. Further sensitivity simulations indicated that eliminating residential emissions resulted in the largest decrease (up to 70%) in PM2.5 and PM10 concentrations. The most significant reductions in the concentrations of SO2 and NO2 were achieved by eliminating industrial and transportation emissions, respectively. The outcomes of this study could be helpful for future studies on pollution formation mechanisms as well as environmental and health risk assessments in western China. (C) 2019 Elsevier Ltd. All rights reserved.

Black carbon (BC) as the main component of pollutants in the Arctic plays an important role on regional climate change. In this study, we applied the regional climate-chemistry model, WRF-Chem, to investigate the spatial distribution, transportation, and impact factors of BC in the Arctic. Compared with reanalysis data and observations, the WRF-Chem performed well in terms of the seasonal variations of meteorological parameters and BC concentrations, indicating the applicability of this model on Arctic BC simulation works. Our results showed that the BC concentrations in the Arctic had an obviously seasonalvariation pattern. Surface BC concentrations peaked during winter and spring seasons, while the minimum occurred during summer and autumn seasons. For the vertical distribution, BC aerosols mainly concentrated in the Arctic lower troposphere, and most of BC distributed near the surface during winter and spring seasons and in the higher altitude during other seasons. The seasonality of BC was associated with the seasonal change of meteorological field. During winter, the significant northward airflow prevailing in northern Eurasia caused the transport of accumulated pollutants from this region into the Arctic. The similar but weakened northward airflow pattern and the anticyclone activity during spring can allow pollutants to be transported to the Arctic lower troposphere. Moreover, the more stable atmosphere during winter and spring seasons made BC accumulated mainly near the surface. During summer and autumn seasons, the less stable boundary layer and the cyclone activity in the Arctic facilitated the diffusion of pollutants into the higher altitude. Meanwhile, the higher relative humidity can promote the wet removal process and lead to the relatively lower BC concentrations near the surface. Compared with the seasonal change of emission, our analysis showed that the seasonal variation of meteorological field was the main contributor for the seasonality of BC in the Arctic. (C) 2019 Elsevier Ltd. All rights reserved.

Heavy precipitation events are increasingly concerned because their significant contribution to annual precipitation in the Northwestern China, which might be related to invasion of summer monsoon moisture. It is interest whether or not the same is Jade Pass as being outside the control of the Asian summer monsoon. In this work, six heavy precipitation events were selected based on the 95 percentiles of the daily precipitation at the 12 weather stations around the Jade Pass from 1970-2000, with consideration of the influences of elevation. The event on June 19th, 2013 was chosen for a detailed examination due to the fact that the day has a large-scale precipitation as revealed by a gridded precipitation dataset over a large region. Using a Weather Research and Forecasting Model (WRF) simulation with high spatiotemporal resolution and in situ isotopic tracing (delta O-18, delta D), under a large-scale heavy precipitation event, this study provides ambitious view at the synoptic scale. A dramatic decrease in the delta O-18, delta D and deuterium (d)-excess of precipitation, very high relative humidity (98%), and reduced air temperature indicate that the precipitation was a result of long-distance-transported monsoon vapor. In addition, the slope of the local water meteoric line (LWML) of the precipitation for this event was very close to that of the global meteoric water line (GWML), indicating the source of moisture was from the ocean. Meanwhile, the WRF simulation confirms that the precipitation at the Jade Pass was not caused by local convection, but by summer monsoon. Both WRF simulation and isotopic tracing support the view that the monsoon moisture could invade Jade Pass at the synoptic scale and impact on precipitation, which need be further investigated.

The formation mechanism of air pollution events in the Sichuan Basin (SB), which is the fourth most heavily polluted area in China, has not been fully revealed. This study investigated the formation mechanism of a severe air pollution event over the SB using synoptic approaches and model simulations. The results can be summarized as follows: (1) Heavy air pollution in the SB was characterized by low visibility, low atmospheric boundary layer (ABL) height, high temperature, high relative humidity, strong temperature inversion layer, subsidence in the troposphere, high water vapor content between 500 and 900 hPa, southerly winds in the low troposphere, and surface winds with low speed and irregular direction. (2) Air quality in the SB was closely related to the weather system at 700 hPa over the basin. When the 700 hPa weather system affecting the SB was a high-pressure system, the subsidence and stable atmospheric stratification increased the air pollutant concentrations near the ground. When the 700 hPa weather system affecting the SB was a low-pressure system and the basin was in front of this low-pressure system, southwesterly warm and moist airflow and adiabatic subsidence warming formed the thick temperature inversion layer over the basin. As a result, the temperature inversion layer trapped air pollutants in the basin and induced the heavy air pollution event. When the 700 hPa weather system over the SB was a low-pressure system and the basin was behind the low-pressure system, the dry and cold airflow from the north invaded southward to the basin and broke the temperature inversion layer. Consequently, air pollutants dispersed vertically, resulting in decreased concentrations near the ground. (3) Air pollutants from December 17, 2017 to January 4, 2018 were mainly from local emissions. (4) The WRF-Chem model not only reproduced the variations in PM2.5 concentrations, the ABL height, and the height-time cross-sections of temperature, water vapor content, and wind over Chengdu during the air pollution event, but also revealed the formation mechanism of this heavy air pollution event. The results of this study reveal the formation mechanism of winter heavy air pollution events over the SB and help develop effective regional air quality management strategies to reduce the likelihood of local air pollution events and minimize the adverse impacts of air pollution.

Investigating the trends in the major climatic variables over the Upper Indus Basin (UIB) region is difficult for many reasons, including highly complex terrain with heterogeneous spatial precipitation patterns and a scarcity of gauge stations. The Weather Research and Forecasting (WRF) model was applied to simulate the spatiotemporal variability of precipitation and temperature over the Indus Basin from 2000 through 2015 with boundary conditions derived from the Climate Forecast System Reanalysis (CFSR) data. The WRF model was configured with three nested domains (d01-d03) with horizontal resolutions increasing inward from 36 km to 12 km to 4 km horizontal resolution, respectively. These simulations were a continuous run with a spin-up year (i.e., 2000) to equilibrate the soil moisture, snow cover, and temperature at the beginning of the simulation. The simulations were then compared with TRMM and station data for the same time period using root mean squared error (RMSE), percentage bias (PBIAS), mean bias error (MBE), and the Pearson correlation coefficient. The results showed that the precipitation and temperature simulations were largely improved from d01 to d03. However, WRF tended to overestimate precipitation and underestimate temperature in all domains. This study presents high-resolution climatological datasets, which could be useful for the study of climate change and hydrological processes in this data-sparse region.