Changes in rainfall affect drinking water, river and surface runoff, soil moisture, groundwater reserve, electricity generation, agriculture production and ultimately the economy of a country. Trends ...in rainfall, therefore, are important for examining the impact of climate change on water resources for its planning and management. Here, as analysed from 119 years of rainfall measurements at 16 different rain gauge stations across northeast India, a significant change in the rainfall pattern is evident after the year 1973, with a decreasing trend in rainfall of about 0.42 ± 0.024 mm dec−1. The wettest place of the world has shifted from Cherrapunji (CHE) to Mawsynram (MAW) (separated by 15 km) in recent decades, consistent with long-term rainfall changes in the region. The annual mean accumulated rainfall was about 12 550 mm at MAW and 11 963 mm at CHE for the period 1989-2010, as deduced from the available measurements at MAW. The changes in the Indian Ocean temperature have a profound effect on the rainfall in the region, and the contribution from the Arabian Sea temperature and moisture is remarkable in this respect, as analysed with a multivariate regression procedure for the period 1973-2019. The changes in land cover are another important aspect of this shift in rainfall pattern, as we find a noticeable reduction in vegetation area in northeast India in the past two decades, implying the human influence on recent climate change.
India is home for more than a billion people and its economy is largely based on agrarian society. Therefore, rainfall received not only decides its livelihood, but also influences its water security ...and economy. This situation warrants continuous surveillance and analysis of Indian rainfall. These kinds of studies would also help forecasters to better tune their models for accurate weather prediction. Here, we introduce a new method for estimating variability and trends in rainfall over different climate regions of India. The method based on multiple linear regression helps to assess contributions of different remote and local climate forcings to seasonal and regional inhomogeneity in rainfall. We show that the Indian Summer Monsoon Rainfall (ISMR) variability is governed by Eastern and Central Pacific El Niño Southern Oscillation, equatorial zonal winds, Atlantic zonal mode and surface temperatures of the Arabian Sea and Bay of Bengal, and the North East Monsoon Rainfall variability is controlled by the sea surface temperature of the North Atlantic and extratropial oceans. Also, our analyses reveal significant positive trends (0.43 mm/day/dec) in the North West for ISMR in the 1979-2017 period. This study cautions against the significant changes in Indian rainfall in a perspective of global climate change.
Atmospheric ammonia (NH3) is an alkaline gas and a prominent constituent of the nitrogen cycle that adversely affects ecosystems at higher concentrations. It is a pollutant, which influences all ...three spheres such as haze formation in the atmosphere, soil acidification in the lithosphere, and eutrophication in water bodies. Atmospheric NH3 reacts with sulfur (SOx) and nitrogen (NOx) oxides to form aerosols, which eventually affect human health and climate. Here, we present the seasonal and inter-annual variability of atmospheric NH3 over India in 2008–2016 using the IASI (Infrared Atmospheric Sounding Interferometer) satellite observations. We find that Indo-Gangetic Plains (IGP) is one of the largest and rapidly growing NH3 hotspots of the world, with a growth rate of +1.2% yr−1 in summer (June–August: Kharif season), due to intense agricultural activities and presence of many fertilizer industries there. However, our analyses show insignificant decreasing trends in annual NH3 of about −0.8% yr−1 in all India, about −0.4% yr−1 in IGP, and −1.0% yr−1 in the rest of India. Ammonia is positively correlated with total fertilizer consumption (r = 0.75) and temperature (r = 0.5) since high temperature favors volatilization, and is anti-correlated with total precipitation (r = from −0.2, but −0.8 in the Rabi season: October–February) as wet deposition helps removal of atmospheric NH3. This study, henceforth, suggests the need for better fertilization practices and viable strategies to curb emissions, to alleviate the adverse health effects and negative impacts on the ecosystem in the region. On the other hand, the overall decreasing trend in atmospheric NH3 over India shows the positive actions, and commitment to the national missions and action plans to reduce atmospheric pollution and changes in climate.
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•A detailed analysis of atmospheric NH3 over India using satellite observations•Intense agriculture and numerous fertilizer plants make the Indo-Gangetic Plain (IGP) as one of the largest NH3 hotspots of the world.•There is a decreasing trend in annual atmospheric NH3 over India in accordance with the national missions and action plans.•The IGP still shows an increasing trend in NH3 during the monsoon/Kharif season.
ABSTRACT
Understanding the conditions of droughts are imperative for many purposes especially in planning and agricultural fields. In this paper an attempt is made to analyse rainfall distribution ...during droughts associated with El Niño and non‐El Niño events using India Meteorological Department (IMD) daily rainfall data set having a spatial resolution of 0.25° latitude × 0.25° longitude grid. Patterns of rainfall during drought years which are not associated with El Niño have below normal rainfall over most places of Indian subcontinent, except peninsular India and eastern region. Most of the drought conditions of the Indian summer monsoon rainfall are associated with El Niño (13 of the 18 years) indicating that about 72% of the drought years are associated with the influence of Pacific Ocean. North India and most of the central Indian regions are under below normal rainfall especially over west coastal stations there the severity of drought is strong. The drought that are associated with El Nino are much intense in most parts of the subcontinent, it severely affected the entire west coastal belts, monsoon zone and eastern regions than the droughts associated with non‐El Nino years. The spatial patterns of rainfall during flood years associated with La Niña events and drought years associated with El Niño reveal that the spatial structure of rainfall is highly non‐linear. These results are also verified using APHRODITE rainfall data. Over central India and Western Ghats (WGs), the drought associated with El Niño gives clear indication of droughts from the early June onward, however, in the case of non‐El Niño‐related droughts, the indication of drought can be seen only after the first week of July. The study suggests that droughts associated with El Niño events bring severe drought conditions over WG region. However, over central India, there is no considerable difference in cumulative rainfall associated with the two types of droughts. The intraseasonal properties of rainfall are prominently different from non‐El Niño to El Niño droughts. During El Niño droughts, the variance of rainfall in both the central Indian and WG regions is weaker than the droughts that are not associated with El Niño.
This study explores the potential of atmospheric moisture content, its transport and its divergence over the ocean and land as proxies for the variability of Indian summer monsoon rainfall (ISMR) for ...the period 1950-2019. The analyses using multiple linear regression reveal that the interannual and intraseasonal variability of ISMR and the mean ISMR is largely controlled by Arabian Sea moisture flux and Ganga river basin moisture content, and these parameters exhibit statistically significant high correlations in most regions. The regression model and the parameters are statistically significant and the model could explain rainfall variability of about 12%-50% in various regions. The model shows a false alarm rate (FAR) of 0.25-0.45 and a probability of detection (POD) of 0.43-0.50 for wet years in West Central, North West and North Central India. The FAR and POD are about 0.06-0.32 and 0.60-0.70, respectively for dry years in those regions. The model reproduces flood and drought years of about 32%-50% and 55%-70% in those regions. Also, the moisture indices could clearly identify the majority of wet and dry years that occurred during the period. The ISMR variability associated with moisture indices is unaffected by El Niño Southern Oscillation. Henceforth, this study demonstrates the significance of atmospheric moisture on regional rainfall distribution and suggests that these parameters can be used in both statistical and dynamical models to better predict monsoon and global precipitation.
Changes in rainfall patterns can have a profound impact on water availability, and therefore, examining the variability of rainfall is critical in addressing water resources and regional climate ...change. Tripura state of northeast India is known to have received a high amount of rainfall in the past few decades, but currently the region suffers from water shortage as soon as the rainy season retreats. Here, we use the surface, satellite and reanalysis data of Tripura in 1986–2019 to examine the seasonal and annual trends in rainfall. The satellite and reanalysis data agree very well with the surface rainfall measurements for Tripura and reproduce the seasonal and inter-annual variability. We find a decreasing trend in the seasonal and annual averaged rainfall at most stations for the period 1986–2019. The monsoon rainfall is declining at a rate of 0.025–0.216 mm/year, with the highest rate of −0.216 mm/year at the Sabroom station during the period. The correlation analysis of rainfall with land use and land cover (LULC) suggests the impact of LULC on rainfall; indicating the anthropogenic influence in rainfall changes there. Our analysis also shows a substantial increase in the Arabian Sea and Bay of Bengal sea surface temperature (SST) after 2000, and the changes in SST with respect to the El Niño, La Niña and Indian Ocean Dipole events contribute significantly to the rainfall variability in the region; suggesting plausible causes of recent changes in regional climate in the northeast.
Studies were carried out on the data from Braemore mountain observatory (lat. 8°45′N, long. 77°5′E) using a single-lens ceilometer (LIDAR), an electric field mill and a portable automatic weather ...station throughout the year 2010. The simultaneous data collected using the above instruments indicate the existence of strong updrafts followed by the formation of thunderclouds, a characteristic of the mountain slopes, during the thunderstorm months. Changes in atmosphere related to condensation and formation of water droplets during updraft events on the mountain slope could be detected from the ceilometer scattering data. Results of the study point to the cause of relatively more thunderstorm activity in that zone. This seems to be due to excessive updraft, which is strongly related to lightning activity in the region.
This paper discusses the abnormal changes in weather elements observed at a tropical mountain location and a coastal station in India. Abnormal changes were noticed in the atmospheric parameters at a ...time close to the occurrence of tsunami on the Indian coasts due to high magnitude earthquakes in the Sumatra region on 26 December 2004. Close to the time of this earthquake occurrence, uncharacteristic and large magnitude changes in weather elements were recorded at Braemore (8°45′N, 77°05′E, 360 m amsl), a mountain field station at Western Ghats. Abnormal changes were also recorded at Minambakkam (13°N, 80°18′E, 16 m SLP), close to eastern coastal belts. In the Braemore field station, simultaneous changes were observed in the atmospheric parameters; decrease in pressure by 0.6 hPa, increase in relative humidity by 30% and a prominent reduction in air temperature by more than 3°C on the day of tsunami. Also, unusually the relative humidity did not reach 100% on the previous night. However, in the Minambakkam station, the relative humidity increased by 10% associated with a sharp decrease in temperature by about 2.5°C. The changes in both the stations occurred almost at the same time and duration. Therefore, it may be concluded that these changes are associated with the high magnitude earthquake and subsequent tsunami.
The study of the clouds and their properties has remained unexplored, especially during the southwest (SW) monsoon season due to the unavailability of reliable data sets. Here we made an attempt to ...study the cloud base height (CBH) and its characteristics during the SW monsoon period of 2007 using CBH data obtained by a Vaisala Laser Ceilometer (VLC). The VLC was made operational at Thiruvananthapuram since July 2006 to monitor the CBH every 15 s. The relation of CBH with meteorological parameters is studied using the radiosonde observations. We found that clouds during the SW monsoon season have mainly concentrated below 2500 m. A layer with relatively void clouds was present between 2500 and 4000 m. We call this region as cloud-free zone. The amplitude of variability of CBH was less compared to the variability of the cloud frequency. Active monsoon is when the cloud frequency exceeds 70% and break phase is when it is less than 40%. The cloud frequency increases when the wind shear increases in the lower levels. Similarly, temperature is more during break phase of monsoon however, the relative humidity shows an increase during active phase of monsoon. Multiple clouds were also noticed during active phase, but it was negligible during break phases of monsoon.
The Indian summer monsoon rainfall (ISMR) during June to September contributes most of the annual rainfall over India and plays an important role in Indian agriculture and thus the economy. It ...exhibits high spatio-temporal variabilities forced from both internal and external factors, which are important for better understanding and prediction of ISMR. Since the internal factors, mainly in the form of intraseasonal oscillations set a limit to the predictability, the major focus is given to the external forcing factors including the coupled air–sea interactions, sea surface temperature variations, snow cover, etc. This paper mainly aims to review the results of recent research analysis on ISMR variability and the major climate factors that determine the variability. Focus is given on the contributions from the coupled ocean–atmosphere processes in the Indian and Pacific Oceans to the ISMR variability (primarily the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Several studies were carried out in recent decades to explore the ISMR variabilities and their influences from tropical oceans. The studies, which focused the impact of ENSO and IOD on the ISMR variability have been considered in exploring their relationships and observed changes in recent decades. In the backdrop of varying relationship of ISMR with ENSO and IOD in the regional scale, it is important to study further the regional teleconnection of ISMR variabilities with oceanic factors, especially from the Indian and Pacific Ocean basin.
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