Anoop Kumar Mishra

Monitoring Convective Clouds Over India and Nearby Regions Using Multi-spectral Satellite Observations

Convective clouds are the sources of severe weather and extreme precipitation events which often produce flooding, landslides and other disasters. The physical characteristics of convective clouds influence the distribution of radiative heating/cooling in the troposphere. They play a crucial role in atmospheric circulation and the hydrological cycle. Present study deals with the detection of convective clouds using multispectral observations at split window channels (near 11 and 12 µm) and water vapour absorption channels (near 6.7 µm) from EUMETSAT (Meteosat 7) data. Results are compared with the observations (reflectivity-based threshold) from Precipitation Radar (PR) on-board Tropical Rainfall Measuring Mission (TRMM). The Results have also been validated against convective clouds derived from rain gauge based precipitation product from the IMD data. Validation results show a correlation coefficient (cc) of 0.79 and Root Mean Square Error (RMSE) of 2.61 (%) against rain gauge based observations of convective clouds.

Quantifying the impact of global warming on precipitation patterns in India

Funding information Ministry of Earth Sciences, Grant/Award Number: MoES/16/27/2014-RDEAS The past few decades have witnessed a change in precipitation patterns around the world. This change includes an increase in heavy precipitation and a decrease in light and moderate precipitation. Global/regional warming has been attributed as one of the major factors causing the observed change in precipitation patterns. Past studies over the Indian region have not focused much on quantification of the impact of warming on changes in precipitation patterns. The present research quantifies the impact of warming on precipitation patterns over the Indian region. For this purpose, rain gauge-based high-resolution gridded precipitation data from the India Meteorological Department (IMD) for 113 years between 1901 and 2013 are used to link the changes in precipitation patterns over India during the South West (SW) monsoon season with warming using a new method that focuses on interannual differences rather than time series. It has been reported that during the SW monsoon period, there is an increase of about 51.85% 19% in the top 10% precipitation for each degree (K) increase in temperature. Decreases of about 15–30%/K in low and moderate precipitation have also been reported per 1 K increase in temperature. The impact of warming is more severe over Western and North Eastern India and during July and August. An increase in heavy rainy days of about 46.53% 14% per 1 K increase in temperature has been reported over the Indian region. Low and moderate rainy days show a decrease of about 24.67% 9.53% for a unit degree increase in temperature. Results reported in this research point out increasing trends in droughts and floods due to increased heavy precipitation and decreased low and moderate precipitation in a warming environment.

On land-use and land-cover changes over Lidder Valley in changing environment

ABSTRACT We have examined the land surface changes in the Lidder Valley of Kashmir in the context of socio-economy, climate and environmental aspect using geoscience technology. It was found that there are large-scale changes in agriculture, horticulture and built-up in the subject area. Records for horticulture, agriculture and built-up were generated from satellite data. A geodatabase of socio-economic data is examined and corelated with the land system changes. Furthermore, environmental driving factors like precipitation, temperature, snowfall and black carbon (BC) data were used to relate with the changes in LU/LC over the study area. This study reports decrease in agricultural area from 189.73 km2 in 1979 to 77.18 km2 in 2011 while the horticulture is increasing by 3 km2 annually from last three decades. With the increase of about 95% in horticulture, the concentration of BC has also increased. BC is showing a significant decadal increase of 10.5 mg/m2 which is mainly attributed to the biomass burning from horticulture waste. Rainfall, as well as snowfall over the study area, is decreasing by an amount of 2.95 and 15 mm per decade, respectively, and also their pattern is changing. These variations over the study area result in water scarcity forcing people to implement horticulture.

Development of a rainfall model to study rainfall over South Africa using satellite microwave remote sensing

Abstract In this study, a rainfall model is developed to study rainfall over South Africa (10° to 40°E, 35° to 20°S) using a set of rainfall signatures derived from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations at 0.25     deg × 0.25     deg spatial grid. Based on measurements at 19-, 21-, and 85-GHz channels of TMI, the scattering index (SI) is derived. Polarization corrected temperature (PCT) is calculated using measurements at the 85-GHz channel. SI, PCT, and their combinations are tested as rain signatures over South Africa. These rain signatures (i.e., PCT and SI and their combinations) are collocated against precipitation radar (PR) onboard TRMM to derive a relationship between rain rate and rain signatures. Rainfall retrieval is attempted using linear as well as nonlinear regressions. The results have been validated using an independent dataset of PR. It is reported that a nonlinear regression outperforms a linear algorithm. Statistical validation with an independent dataset of PR exhibits the correlation coefficients (CCs) of 0.60, 0.64, and 0.66, and root mean square errors (RMSEs) of 5.82, 6.42, and 5.76     mm / h from observations of SI, PCT, and a combination of SI and PCT, respectively, using linear regressions. When nonlinear regression is used, the CC of 0.69, 0.68, and 0.70 and RMSE of 4.75, 4.89, and 4.38     mm / h are observed from the SI, PCT, and the combination of SI and PCT, respectively.