South Asian emissions of fossil fuel SO2 and black carbon increased Ϸ6-fold since 1930, resulting in large atmospheric concentrations of black carbon and other aerosols. This period also witnessed strong negative trends of surface solar radiation, surface evaporation, and summer monsoon rainfall. These changes over India were accompanied by an increase in atmospheric stability and a decrease in sea surface temperature gradients in the Northern Indian Ocean. We conducted an ensemble of coupled oceanatmosphere simulations from 1930 to 2000 to understand the role of atmospheric brown clouds in the observed trends. The simulations adopt the aerosol radiative forcing from the Indian Ocean experiment observations and also account for global increases in greenhouse gases and sulfate aerosols. The simulated decreases in surface solar radiation, changes in surface and atmospheric temperatures over land and sea, and decreases in monsoon rainfall are similar to the observed trends. We also show that greenhouse gases and sulfates, by themselves, do not account for the magnitude or even the sign in many instances, of the observed trends. Thus, our simulations suggest that absorbing aerosols in atmospheric brown clouds may have played a major role in the observed regional climate and hydrological cycle changes and have masked as much as 50% of the surface warming due to the global increase in greenhouse gases. The simulations also raise the possibility that, if current trends in emissions continue, the subcontinent may experience a doubling of the drought frequency in the coming decades.aerosols ͉ black carbon ͉ regional climate change

Predicting streamflows in snow-fed watersheds in the Western United States is important for water allocation. Since many of these watersheds are heavily regulated through canal networks and reservoirs, predicting expected natural flows and therefore water availability under limited data is always a challenge. This study investigates the applicability of the flow duration curve (FDC) method for predicting natural flows in gauged and ungauged snow-fed watersheds. Point snow observations, air temperature, precipitation, and snow water equivalent, are used to simulate snowmelt process with SNOW-17 model and extended to streamflow generation by a FDC method with modified current precipitation index. For regulated (ungauged) watersheds, a parametric regional FDC method is applied to reconstruct natural flow. For comparison, a simplified Tank Model is used as well. The proximity regionalization method is used to generate streamflow using the Tank Model in ungauged watersheds. The results show that the FDC method can produce acceptable natural flow estimates in both gauged and ungauged watersheds under data limited conditions. The performance of the FDC method is better in watersheds with relatively low evapotranspiration (ET). Multiple donor data sets including current precipitation index are recommended to reduce uncertainty of the regional FDC method for ungauged watersheds. In spite of its simplicity, the FDC method can perform better than the Tank Model under minimal data availability