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ABSTRACT:In this study, the performance of the weather research and forecasting (WRF) ARW regional model was evaluated for simulating the regional scale precipitation during Indian summer monsoon (ISM) at 30 km resolution over seven different homogeneous rainfall zones falling under different climatic (perhumid, humid, dry/moist subhumid, dry/moist semiarid, arid) regions of India. Seasonal scale simulations were made for ten summers (JJAS months) over 2000-2009 using the boundary conditions derived from the National Centers for Environmental Prediction (NCEP) reanalysis data. Sensitivity experiments were conducted with three convection schemes (Kain-Fritsch, KF; Betts-Millor-Janjic, BMJ; GrellDevenyi, GD). Simulated regional climate was evaluated by comparison of precipitation with 0.5°India Meteorological Department (IMD) gridded rainfall data over land, Tropical Rainfall Measuring Mission (TRMM) rainfall data over the ocean and atmospheric circulation fields with 1°NCEP global final analysis (FNL). Although all the simulations showed spatio-temporal rainfall patterns, BMJ had least bias towards dryness whereas KF had moist bias and GD had higher dry bias. BMJ could simulate low, moderate and high rainfall reasonably well with relatively higher correlations and threat scores, lower bias and mean absolute errors in most zones as compared to better simulation of heavy precipitation events with KF and low rainfall days alone with GD scheme. The better performance of BMJ scheme is evident owing to better simulation of surface pressure, temperature, and geopotential, lower and upper atmospheric flow fields. Simulations revealed a relatively less intensive heat, weaker low-level westerly winds, weaker north-south geopotential gradients, weaker subtropical easterlies in the El Niño years than in the La Niña years, which indicate the model is able to simulate the interannual variations in monsoon characteristics.

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TNT is one of the most commonly used nitro aromatic explosives for landmines of military and terrorist activities. As a result, there is an urgent need for rapid and reliable methods for the detection of trace amount of TNT for screening in airport, analyzing forensic samples and environmental analysis. Driven by the need to detect trace amounts of TNT from environmental samples, this article demonstrates a label-free, highly selective and ultra sensitive para-aminothiophenol (p-ATP) modified gold nanoparticle based dynamic light scattering (DLS) probe for TNT recognition in 100 pico molar (pM) level from ethanol:acetonitile mixture solution. Due to the formation of strong π-donor–acceptor interaction between TNT and p-ATP, para-aminothiophenol attached gold nanoparticles undergo aggregation in the presence of TNT, which changes the DLS intensity tremendously. A detailed mechanism for significant DLS intensity change has been discussed. Our experimental results show that TNT can be detected quickly and accurately without any dye tagging in 100 pM level with excellent discrimination against other nitro compounds.