Aerosols can alter atmospheric stability through radiative forcing, thereby changing mean and daily extreme precipitation on regional scales. However, it is unclear how extreme sub-daily precipitation responds to aerosol radiative effects. In this study, we use the regional climate model (RCM) Consortium for Small-scale Modeling (COSMO) to perform convection-permitting climate simulations at a kilometer-scale (0.04 degrees/similar to 4.4 km) resolution for the period 2001-2010. By evaluating against the observed hourly precipitation-gauge data, the COSMO model with explicit deep convection can effectively reproduce sub-daily and daily extreme precipitation events, as well as diurnal cycles of summer mean precipitation and wet hour frequency. Moreover, aerosol sensitivity simulations are conducted with sulfate and black carbon aerosol perturbations to assess the direct and semi-direct aerosol effects on extreme sub-daily precipitation in the COSMO model. The destabilizing effects associated with decreased sulfate aerosols intensify extreme sub-daily precipitation, while increased sulfate aerosols tend to induce an opposite change. In contrast, the response of extreme sub-daily precipitation to black carbon aerosol perturbations exhibits a nonlinear behavior and potentially relies on geographical location. Overall, the scaling rates of extreme precipitation intensities decrease and approach the Clausius-Clapeyron rate from hourly to daily time scales, and the responses to sulfate and black carbon aerosols vary with precipitation durations. This study improves the understanding of aerosol radiative effects on sub-daily extreme precipitation events in RCMs.

Aerosol mixtures, which are still unclear in current knowledge, may cause large uncertainties in aerosol climate effect assessments. To better understand this research gap, a well-developed online coupled regional climate-chemistry model is employed here to investigate the influences of different aerosol mixing states on the direct interactions between aerosols and the East Asian summer monsoon (EASM). The results show that anthropogenic aerosols have high-level loadings with heterogeneous spatial distributions in East Asia. Black carbon aerosol loading accounts for more than 13% of the totals in this region in summer. Thus, different aerosol mixing states cause very different aerosol single scattering albedos, with a variation of 0.27 in East Asia in summer. Consequently, the sign of the aerosol instantaneous direct radiative forcing at the top of the atmosphere is changed, varying from - 0.95 to + 1.50 W/m(2) with increasing internal mixing aerosols. The influence of aerosol mixtures on regional climate responses seems to be weaker. The EASM circulation can be enhanced due to the warming effect of anthropogenic aerosols in the lower atmosphere, which further induces considerable aerosol accumulation associated with dynamic field anomaly, decrease in rainfall and so on, despite aerosol mixtures. However, this interaction between aerosols and the EASM will become more obvious if the aerosols are more mixed internally. Additionally, the differences in aerosol-induced EASM anomalies during the strongest and weakest monsoon index years are highly determined by the aerosol mixing states. The results here may further help us better address the environmental and climate change issues in East Asia.

Aerosol-cloud interactions, also known as aerosol indirect effect (AIE), substantially impact rainfall frequency and intensity. Here, we analyze NEX-GDDP, a multimodel ensemble of high-resolution (0.25 degrees) historical simulations and future projections statistically downscaled from 21 CMIP5 models, to quantify the importance of AIE on extreme climate indices, specifically consecutive dry days (CDD), consecutive wet days (CWD), and simple daily intensity index (SDII). The 21 NEX-GDDP CMIP5 models are classified into models with reliable (REM) and unreliable (UREM) monsoon climate simulated over India based on their simulations of the climate indices. The REM group is further decomposed based on whether the models represent only the direct (REMADE) or the direct and indirect (REMALL) aerosol effects. Compared to REMADE, including all aerosol effects significantly improves the model skills in simulating the observed historical trends of all three climate indices over India. Specifically, AIE enhances dry days and reduces wet days in India in the historical period, consistent with the observed changes. However, by the middle and end of the 21st century, there is a relative decrease in dry days and an increase in wet days and precipitation intensity. Moreover, the REMALL simulated future CWD and CDD changes are mostly opposite to those in REMADE, indicating the substantial role of AIE in the future projection of dry and wet climates. These findings underscore the crucial role of AIE in future projections of the Indian hydroclimate and motivate efforts to accurately represent AIE in climate models. We investigate the impacts of aerosol on India's wet and dry climate. High-resolution downscaled CMIP5 models were used to calculate extreme indices like CDD (consecutive dry days), CWD (consecutive wet days), SDII (precipitation intensity). From the group of 22 models, 12 reliable models were chosen based on their fidelity to the observations. Amongst the reliable models, certain models incorporate only aerosol-radiation interaction (REMADE), while others have both aerosol-radiation and aerosol-cloud interaction (REMALL). We found that the simulated trends in the REMAll were similar to the observed trends. In the current period (1975-2005), the aerosol-cloud interactions led to the reduction in rainfall (both frequency and intensity wise) and enhanced the dry days, however in the future projections, the reduction in aerosol emissions leads to a wetter climate (increase in wet days and rainfall intensity) over India.

This study quantifies the impacts of climate change on the mine life cycle (development, operation and closure phases) of 30 mines located in the northern regions of Canada. To this end, climate projections based on a five -member transient climate change simulation ensemble, performed using a state-of-the art regional climate model, spanning the 1991-2050 period, corresponding to the Representative Concentration Pathway 8.5 emis-sion scenario are used. A reanalysis-driven simulation for the 1991-2010 period compared against available observations confirm suitability of the model for application in climate change simulations. Assessment of projected changes to mine-relevant climate variables that are important from structural integrity and operation perspectives reveal potential vulnerabilities and opportunities. Active layer thickness increases in the 0.3-2 m range in permafrost regions, coupled with increases in flood probability, as reflected in snow-melt rate increases in the 0.14-6.77% range and increases in the 100-year return levels of daily maximum rainfall in the 5-50% range, suggest potential impacts on the structural integrity of mine infrastructure, such as slope instability and foundation settlement of tailings dams, and supporting infrastructure such as ice/all-season roads. Increases in soil moisture, projected in the 0-11% range, at a few mines, suggest potential impacts on material handling systems, such as increases in the traction factor of the muck-haul and tire rolling resistance, that can lead to low productivity. Projected increases to wind speeds in the 5-10% range for the northernmost regions suggest po-tential impacts on the tailings management facility in terms of increases in tailings resuspension. Overall, this study identified northernmost and northeastern mines to be more vulnerable, with air/soil temperature, pre-cipitation and wind speed being the most influential climate variables. This systematic study, for the first time, has identified potential vulnerabilities of northern Canadian mines, which can inform future high-resolution climate modelling and detailed at-site climate-mine interaction studies that is required for climate-change adaptation related decision-making.

Infrastructure and transportation systems on which northern communities rely are exposed to a variety of climatic hazards over a broad range of scales. Efforts to adapt these systems to the rapidly warming Arctic climate require high-quality climate projections. Here, a state-of-the-art regional climate model is used to perform simulations at 4-km resolution over the eastern and central Canadian Arctic. These include, for the first time over this region, high-resolution climate projections extending to the year 2040. Validation shows that the model adequately simulates base climate variables, as well as variables hazardous to northern engineering and transportation systems, such as degrading permafrost, extreme rainfall, and extreme wind gust. Added value is found over coarser resolution simulations. A novel approach integrating climate model output and machine learning is used for deriving fog-an important, but complex hazard. Hotspots of change to climatic hazards over the next two decades (2021-2040) are identified. These include increases to short-duration rainfall intensity extremes exceeding 50%, suggesting Super-Clausius-Clapeyron scaling. Increases to extreme wind gust pressure are projected to reach 25% over some regions, while widespread increases in active layer thickness and ground temperature are expected. Overall fog frequency is projected to increase by around 10% over most of the study region by 2040, due to increasing frequency of high humidity conditions. Given that these changes are projected to be already underway, urgent action is required to successfully adapt northern transportation and engineering systems located in regions where the magnitude of hazards is projected to increase.

Dynamical downscaling generally performs poorly on the Tibetan Plateau (TP), due to the region's complex topography and several aspects of model physics, especially convection and land surface processes. This study investigated the effects of the cumulus parameterization scheme (CPS) and land-surface hydrology scheme (LSHS) on TP climate simulation during the wet season using the RegCM4 regional climate model. To address these issues and seek an optimal simulation, we conducted four experiments at a 20 km resolution using various combinations of two CPSs (Grell and MIT-Emanuel), two LSHSs (the default TOPMODEL [TOP], and Variable Infiltration Capacity [VIC]). The simulations in terms of 2-m air temperature, precipitation (including large-scale precipitation [LSP] and convective precipitation [CP]), surface energy-water balance, as well as atmospheric moisture flux transport and vertical motion were compared with surface and satellite-based observations as well as the ERA5 reanalysis dataset for the period 2006-2016. The results revealed that the model using the Grell and TOP schemes better reproduced air temperature but with a warm bias, part of which could be significantly decreased by the MIT scheme. All schemes simulated a reasonable spatial distribution of precipitation, with the best performance in the experiment using the MIT and VIC schemes. Excessive precipitation was produced by the Grell scheme, mainly due to overestimated LSP, while the MIT scheme largely reduced the overestimation, and the simulated contribution of CP to total precipitation was in close agreement with the ERA5 data. The RegCM4 model satisfactorily captured diurnal cycles of precipitation amount and frequency, although there remained some differences in phase and magnitude, which were mainly caused by the CPSs. Relative to the Grell scheme, the MIT scheme yielded a weaker surface heating by reducing net radiation fluxes and the Bowen ratio. Consequently, anomalous moisture flux transport was substantially reduced over the southeastern TP, leading to a decrease in precipitation. The VIC scheme could also help decrease the wet bias by reducing surface heating. Further analysis indicated that the high CP in the MIT simulations could be attributed to destabilization in the low and mid-troposphere, while the VIC scheme tended to inhibit shallow convection, thereby decreasing CP. This study's results also suggest that CPS interacts with LSHS to affect the simulated climate over the TP.

Warm season moist diurnal convection can be particularly sensitive to changes in land surface characteristics such as snow cover and soil moisture. Over regions of mountainous terrain, climate change is expected to reduce snow cover along the low-elevation seasonal snowpack margin. These snow reductions alter surface albedo and soil moisture content, leading to changes in surface fluxes and alterations in mesoscale orographic circulations that act to transport moisture and provide ascent. A set of convection-permitting regional climate simulations centered on the Rocky Mountains of Colorado are conducted from April through July across a period of 12 years (2002-2013). These include a reanalysis forced control run (CTR), a pseudo global warming run (PGW), and an additional altered land surface run (DSURF) used to isolate the effects of the snow albedo and soil moisture changes on orographic convection. Over the mountains, daytime hourly precipitation accumulation (0900-1800 MST) decreased in PGW by an average of 4.2% while precipitation in DSURF increased by 12.5%. On days with weak synoptic forcing, the PGW response more closely follow the DSURF response with daytime hourly increases averaging 29.7% for PGW and 28.7% for DSURF. For PGW, hourly daytime precipitation intensity increases of up to 82% overcome reductions in precipitation frequency to produce higher accumulations. DSURF shows smaller increases in intensity of up to 23% and broad increases in daytime frequency indicating that surface changes act to moderate reductions in the frequency of convective precipitation. Reduced snow cover contributes to this convective response by increasing convective instability and boundary layer moisture and decreasing lifting condensation level over the high terrain. Alterations in orographic thermal circulations contribute to this response by converging moisture over the high terrain and enhancing mesoscale ascent.

The climate change is significantly changing the hydro-thermal state of active layer at Qinghai-Tibet Plateau (QTP), which endangers permafrost environment. The degradation of permafrost would damage the linear engineering in cold regions; furthermore, the alternation of soil hydro-thermal state in the area of rugged terrain would lead to geo-hazards and then threaten the safety of local people. Global warming is widely accepted as a big threat to the ecological environment of arctic, subarctic and alpine regions, while the changing trend of precipitation around the world is still in dispute. Furthermore, the role of precipitation accompanied with global warming is unknown. Hence, in this study, the localized monitoring data from Beiluhe permafrost monitoring station at QTP, including atmospheric and soil hydro-thermal data, were utilized for further processing and comparative analysis. Firstly, the changing trend of precipitation here was investigated through the atmospheric data from 2003 to 2013. Thereafter, the hydro-thermal change of active layer was analyzed combined with precipitation events during this period. However, the raining pattern in QTP is characterized with continuity, short duration and small amount, basically referring to thawed season. The hydro-thermal change affected by corresponding raining event could be influenced by temporally nearby event in timescale. To differentiate the effect, the characteristic precipitation event (CPE) was selected through an elaborate algorithm. Subsequently, the hydro-thermal changes of active layer were reanalyzed in response to CPEs. Representative outcomes were chosen for the specific analysis under the influence from CPEs. Hence, under the circumstance of global warming, the effect from precipitation on the hydro-thermal properties of active layer was also obtained, and the possible harmful consequence induced by that was also discussed.

Recent studies examine the potential for large urban fires ignited in a hypothetical nuclear exchange of one hundred 15 kt weapons between India and Pakistan to alter the climate (e.g., Mills et al., 2014, , and Reisner et al., 2018, ). In this study, the global climate forcing and response is predicted by combining two atmospheric models, which together span the micro-scale to global scale processes involved. Individual fire plumes are modeled using the Weather Research and Forecasting (WRF) model, and the climate response is predicted by injecting the WRF-simulated black carbon (BC) emissions into the Energy Exascale Earth System Model (E3SM) atmosphere model Version 1 (EAMv1). Consistent with previous studies, the radiative forcing depends on smoke quantity and injection height, examined here as functions of fuel loading and atmospheric conditions. If the fuel burned is 1 g cm(-2), BC is quickly removed from the troposphere, causing no global mean climate forcing. If the fuel burned is 16 g cm(-2) and 100 such fires occurred simultaneously with characteristics similar to historical large urban firestorms, BC reaches the stratosphere, reducing solar radiation and causing cooling at the Earth's surface. Uncertainties in smoke composition and aerosol representation cause large uncertainties in the magnitude of the radiative forcing and cooling. The approximately 4 yr duration of the radiative forcing is shorter than the 8 to 15 yr that has previously been simulated. Uncertainties point to the need for further development of potential nuclear exchange scenarios, quantification of fuel loading, and improved understanding of fire propagation and aerosol modeling.

The regional climate model RegCM 4.4 at 50km resolution is used to conduct a sensitivity study over South Asia Coordinated Regional climate Downscaling Experiment domain during the period 1998-2002, in order to investigate the best cumulus convective precipitation scheme, planetary boundary layer (PBL) and land-surface scheme. The inferences obtained from 11 sensitivity experiments include the better performance of community land model version 4.5 (CLM 4.5) over biosphere-atmosphere transfer scheme, Tiedtke as cumulus convective precipitation scheme and University of Washington (UW) as PBL scheme. The simulation with these parameterization schemes well captures the monsoon precipitation pattern over India similar to 7mm/day and North Eastern Region of India (NER) similar to 12mm/day, which are comparable to observations with a significant correlation of R-2>0.93. The observed temperatures are also well simulated by the model. Therefore, RegCM 4.4 with these parameterization schemes is further used to simulate the aerosol fields (aerosol optical depth, AOD and black carbon, BC) and aerosol direct radiative forcing (DRF) for the period 2011-2014 over the same domain with special emphasis on NER. The model captures the seasonality in AOD and BC over the Indian Subcontinent and NER. BC hotspots in the Indo-Gangetic Plain and China are well captured by the model. The observed to simulated BC ratio over Dibrugarh (located in NER) is found to be improved. The model underestimation is significant in the dry season when burning over the region is predominant, which has not been considered by the emission inventories properly. Simulated DRF is found to exhibit seasonality qualitatively as well as a North-South latitudinal gradient.