Analysis of marine heatwaves over the Bay of Bengal during 1982-2021.

Anomalous increase in sea surface temperature and its impact on natural ecosystems greatly interests the research community. Here we investigate the causes, impacts, and trends of marine heat wave (MHW) events in the Bay of Bengal (BoB) from 1982 to 2021. A total of 107 MHW events have been isolated (> 90th percentile threshold) in this Indian Ocean region, and their variation in intensity, duration, and frequency has been investigated. Our research unveils that an average of three MHW events/year accompanied by a linearly increasing trend of 1.11 MHW events/decade has been observed over the study region. It was also found that the most intense event was observed in 2016, which continued for 69 days, and had a maximum intensity of 5.29 °C and a mean intensity of 2.03 °C (above climatology mean). Moreover, it was observed that the net heat flux, along with anticyclonic eddies, was the primary cause of MHW events. Anticyclonic eddies associated with positive sea surface height anomaly were observed (> 0.20 m) in the vicinity of the most intense MHW event. Additionally, climate change and climate modes like El Niño and Indian Ocean Dipole show a high positive influence on the MHW events. Furthermore, we have examined the MHW event recurrence patterns in various regions of the BoB. From the monthly analysis, it was found that August and November had the most occurrences of MHWs, while April and May had the most extreme MHW events.

Analysis of heat stress and heat wave in the four metropolitan cities of India in recent period.

Cities are becoming hotter day-by-day because heat is trapped near the earth's surface due to a decrease in green cover, rapid urbanization, energy-intensity activities, and concrete structures. The four major metropolitan cities of India, i.e. Kolkata, Chennai, Delhi and Mumbai, have experienced heat waves and heat stress frequently during the summer season. This study analyses heat wave and heat stress patterns in these cities using 30 years of data from 1990 to 2019 during the summer season. We used daily maximum temperature, relative humidity, wind speed and solar radiation datasets for the above mentioned period in this study. To understand the episode of a heat wave, we have used the 95th percentile method. Furthermore, we have also used Humidity Index (HD) to evaluate the degree of discomfort and the Universal Thermal Climate Index (UTCI) to categorize the level of heat stress. The analysis indicates that the number of heat wave events in the Delhi region is 26.31%, 31.58% and 63.16% higher than Kolkata, Chennai, and Mumbai regions respectively. It is also seen that the risks of extreme heat stress and dangerous-heat stroke events in the Chennai region during heat wave periods are higher than that experienced in other metropolitan cities because of high temperature with higher values of relative humidity. The risk of extreme heat stress is less in Delhi because of lower relative humidity compared to other metropolitan cities although temperature is higher in this region. However, the risk of extreme heat stress is lower in Mumbai region because of relatively lower temperature than Chennai during summer season. The likelihood of experiencing great discomfort during heat wave periods in Kolkata city is higher than that experienced in other metropolitan cities in India, however, during non-heat wave periods the probability of extreme discomfort is higher in Chennai.

Quantification of nitrogen transformation and leaching response to agronomic management for maize crop under rainfed and irrigated condition.

Nitrogen (N) plays an important role in agriculture crop production but the increasing application of nitrogen increases the possibilities of groundwater contamination through nitrate leaching. Nitrate leaching is the inevitable part of agriculture production which occurs during nitrogen fertilization. Hence, the quantification of nitrogen fertilizer is required to reduce nitrate leaching. In this study, nitrogen transformation and transport such as ammonium (NH4+) and nitrate (NO3-) at different soil depths and maize crop growth stages were measured during field experiments for two sowing dates (timely and delay) and four N fertilization levels under irrigated (year 2013 and 2014) and rainfed (year 2012 and 2014) conditions for maize crop. NH4+, NO3- and total nitrogen concentrations were measured using spectrophotometer at 410 nm and Kjeldahl method at varying soil depths and maize crop growth stages. Thereafter, nitrogen balance approach was used to estimate the NO3- leaching. Results indicated that NO3- leaching in irrigated condition was higher 109% in N75, 179% in N100, and 292% in N125 level respectively in comparison to the N0 level in timely sowing date, while in delayed sowing date, leaching was higher 54% in N75, 123% in N100, and 184% in N125 level respectively in comparison to N0 level. In rainfed, the NO3- leaching was higher 30% in N60, 59% in N80, and 99% in N100 level respectively in comparison to N0 level for the timely sowing date, while in delayed sowing, leaching was higher 23% in N60, 44% in N80, and 78% in N100 level respectively in comparison to N0 level. The results indicate that leaching losses were less in timely sowing dates for both rainfed and irrigated maize. The study further reveals that sowing dates combination with N levels could be an effective management strategy to reduce NO3- leaching by minimizing the N fertilization.

Surface chlorophyll anomalies associated with Indian Ocean Dipole and El Niño Southern Oscillation in North Indian Ocean: a case study of 2006-2007 event.

North Indian Ocean witnesses varied dynamical response due to independent climate modes such as Indian Ocean Dipole (IOD)/El Niño Southern Oscillations (ENSO) and their co-occurrences. These modes have a significant impact on ocean productivity, which in turn shows feedback for the strengthening of these patterns. Keeping this in view, the present work attempts to analyze the biological activity during the combined influence of positive IOD with El Niño during 2006-2007 event. To divulge the biological variability along with the dynamical response, the study includes intra-annual variability surface chlorophyll anomaly with D20 anomaly using satellite observations. Here, the individual role of IOD and ENSO on both surface chlorophyll and D20 is segregated through partial regression analysis for a period of 25 years (1993-2017). By the regression method, it can be seen varied chlorophyll response for the 2006-2007 event with the IOD forcing leads to the major spatial and temporal variability with positive anomalies in Eastern Equatorial Indian Ocean (EEIO) (generally oligotrophic), Northwestern Bay of Bengal (NWBoB), and Northwestern Arabian Sea (NAS2) where production begins in fall intermonsoon and peaks up during November. On the other hand, negative anomalies are observed around the southern tip of India (SBoB) and the Northern Arabian Sea (NAS1). While ENSO depicts the high surface chlorophyll variability in the Western Indian Ocean (WIO1, WIO2) with negative anomalies of surface chlorophyll. This study observed an asymmetric response of chlorophyll variability over the North Indian Ocean during the 1997-1998 and 2006-2007 events with a major influence of IOD mode compared with the El Niño. Therefore, understanding the chlorophyll anomalies during different climate modes will help us to better understand the interannual variability and improve the predictability of chlorophyll productivity regions.

Anthropogenic forcing exacerbating the urban heat islands in India.

Urban heat island (UHI) phenomena is among the major consequences of the alteration of earth's surface due to human activities. The relatively warmer temperatures in urban areas compared to suburban areas (i.e. UHI) has potential health hazards, such as mortality due to high temperatures and heat waves. In addition, UHI situation demands more energy (e.g. fans and air-conditioners) that would trigger greenhouse gas emissions. Studies on UHI intensity help to assess its impact on urban population, city planning, and urban health planning. This is particularly important for a country like India, where 32% people (~7% of total world population), live in urban areas. We conducted a detailed study on surface UHI intensity (SUHII), which is the difference between urban and surrounding rural land surface temperatures, across all seasons in 44 major cities of India, which shows that mean daytime SUHII is positive (up to 2 °C) for most cities, as analysed from satellite temperature measurements for the period 2000-2017, in contrast to previous studies. However, although statistically insignificant, most cities show a positive trend in SUHII for monsoon and post-monsoon periods, but negative for winter and summer seasons. The increasing night-time SUHII in all seasons for most cities suggest increasing trend in temperature in cities due to the impact of the rapid urbanisation, and thus, suggesting the influence of anthropogenic forcing on SUHII. This is also supported by the analysis of aerosols, night lights, precipitation and vegetation in the study regions. Therefore, this study shall aid planning and management of urban areas by giving insights about the effects of nature and intensity of development, land cover and land use mix and the structure of cities on SUHII.

Spatio-Temporal Variation and Futuristic Emission Scenario of Ambient Nitrogen Dioxide over an Urban Area of Eastern India Using GIS and Coupled AERMOD-WRF Model.

The present study focuses on the spatio-temporal variation of nitrogen dioxide (NO2) during June 2013 to May 2015 and its futuristic emission scenario over an urban area (Durgapur) of eastern India. The concentration of ambient NO2 shows seasonal as well as site specific characteristics. The site with high vehicular density (Muchipara) shows highest NO2 concentration followed by industrial site (DVC- DTPS Colony) and the residential site (B Zone), respectively. The seasonal variation of ambient NO2 over the study area is portrayed by means of Geographical Information System based Digital Elevation Model. Out of the total urban area under consideration (114.982 km2), the concentration of NO2 exceeded the National Ambient Air Quality Standard (NAAQS) permissible limit over an area of 5.000 km2, 0.786 km2 and 0.653 km2 in post monsoon, winter and pre monsoon, respectively. Wind rose diagrams, correlation and regression analyses show that meteorology plays a crucial role in dilution and dispersion of NO2 near the earth's surface. Principal component analysis identifies vehicular source as the major source of NO2 in all the seasons over the urban region. Coupled AMS/EPA Regulatory Model (AERMOD)-Weather Research and Forecasting (WRF) model is used for predicting the concentration of NO2. Comparison of the observed and simulated data shows that the model overestimates the concentration of NO2 in all the seasons (except winter). The results show that coupled AERMOD-WRF model can overcome the unavailability of hourly surface as well as upper air meteorological data required for predicting the pollutant concentration, but improvement of emission inventory along with better understanding of the sinks and sources of ambient NO2 is essential for capturing the more realistic scenario.