Browsing by Author "J.V. Singh"

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Evaluation of CORDEX- South Asia regional climate models for heat wave simulations over India
(Elsevier Ltd, 2021) Saumya Singh; R.K. Mall; J. Dadich; S. Verma; J.V. Singh; A. Gupta
The episodes of heat wave events have strengthened in recent decades causing great concern for human health, agriculture and natural ecosystem. In the present study, Regional Climate Models (RCMs) namely, CCAM and RegCM, from Coordinated Regional Climate Downscaling Experiments (CORDEX) for South Asia (SA) are evaluated for simulating heat waves (March–June) for a long-term period (1971 to 2005) over India in comparison with observations from India Meteorological Department (IMD). The statistical analysis (correlation, RMSE, MAE, ECDF) results reveal differences in RCMs in simulating spatial pattern and trends of maximum temperature before bias correction. Variance scaling bias correction is found to remove bias and improve model simulations in capturing temperature variability. An increase in correlation in daily observations from 0.24 to 0.70 and reduction in RMSE from 8.08 °C to 2.02 °C and MAE from 3.87 °C to 2.43 °C after bias correction is observed between model and observation. LMDZ4 and GFDL-ESM2M are found to perform best in simulating interannual variability of seasonal mean maximum temperature with an underestimation of −7.74% and −15.41% which improved significantly to around −1.51% and − 0.78%, respectively after bias correction over India. LMDZ4 and GFDL-ESM2M are also best-performing models in significantly reproducing the heat wave frequency and spatial variability in closer proximity with observations over India amongst all models after bias correction. Over NW and western regions, the LMDZ4 and GFDL-ESM2M ensemble models successfully capture the increasing trend of 0.2 events/year and 0.4 events/year accordance to IMD and IITM criteria, respectively. However, the ACCESS1.0, CNRM-CM5 and CCSM4 ensemble experiments overestimated heat waves by ±40 events in most sub-divisions in India. Over the central Indian regions, the ACCESS 1.0 and CNRM-CM5 model output show a negative trend of −0.2 events/year and large spatial variability possibly due to model associated uncertainties. Overall the results show an improvement in capturing maximum temperature and heat waves across the regions of Indian sub-continent in the bias-corrected downscaled CORDEX-SA ensemble RCMs than without bias-corrected output. The study suggests a way forward to assess RCMs performance and uncertainty in extreme weather analysis in future projections. © 2020 Elsevier B.V.
High concentration of acidic species in rainwater at Varanasi in the Indo-Gangetic Plains, India
(Kluwer Academic Publishers, 2015) D.S. Bisht; S. Tiwari; A.K. Srivastava; J.V. Singh; B.P. Singh; M.K. Srivastava
The Indo-Gangetic Plains (IGP), straddling the northeastern parts of India near the foothills of the Himalayas, are one of the most densely populated and polluted regions on the globe, with consequent large anthropogenic emissions. In particular, the use of traditional biofuels in the rural areas along the plains leads to strong emissions of various pollutants. Due to this importance, a comprehensive study on the chemical characteristics of rainwater was carried out during southwest summer monsoon season of 2009 at two different locations over Varanasi, India, located in the middle of IGP region in the eastern part of Uttar Pradesh. The rainwater samples were analyzed for major chemical constituents along with pH and its electric conductivity. The pH values ranged from 5.18 to 7.08 with a mean of 5.82 ± 0.45 suggest the alkaline nature of rainwater over Varanasi. During the study period, ~14 % rainwater samples were found to be acidic when the winds blew from south–southeast direction. The weighted mean pH and electric conductivity were found higher (5.92 ± 0.45) and (24.59 µS/cm) at Maldahiya site than Banaras Hindu University (5.89 ± 0.46) and (17.16 µS/cm) due to dominance of soil-derived particles. The equivalent concentration of ionic species is of the order: Ca2+ > SO4 2− > NO3 − > Cl− > Mg2+ > Na+ > HCO3 − > NH4 + > K+ > F− > H+. The weighted mean concentration of dominant ions in rainwater over Varanasi was Ca2+ (67.1 ± 56 µeq/l), SO4 2− (37 ± 23 µeq/l) and NO3 − (27.1 ± 28 µeq/l). Significant correlation (r = 0.81; P < 0.001) between the sum of major cations (NH4 + + Ca2+ + Mg2+) and the sum of acidic species (SO4 2− + NO3 −) corroborates that these alkaline species may act as a neutralizing agent for the acidity of rainwater. The source contribution of SO4 2− in rainwater was estimated and was ~95 % by man-made activities, which is mainly derived from burning of fossil/biofuels over this region. The source of nitrate (11 %) emissions was mainly from automobiles and biomass burning. Statistical analysis such as principle component analysis was performed to find out possible sources of measured ions. First factor accounted for ~54 % variance suggested that most of the ions were from natural sources especially soil dust and sea; however, factor 2 accounted only for ~12 % variance suggests their sources from burning of fossil fuel and biomass. The third factor also indicates the mixed sources into the atmosphere. © 2014, Springer Science+Business Media Dordrecht.