Research - (2022) Volume 10, Issue 5
An increase in Greenhouse gases and aerosols in the atmosphere are the main reasons for an increasing trend in the extreme weather events throughout the world. The variations in extreme weather events will affect the human life and their needs such as food and water. Therefore, the study of pattern of extreme weather events is significant in understanding their effects on the human life and their essential needs. The extreme weather events flood, tropical cyclone, heat wave, gale, squall, lightning, dust-storm, hailstorm and thunderstorm have been considered to understand the form over India. The data of the incidence of these events has been obtained from IMD and other public sector agencies. The regression analysis of combination of different events revealed that effect of floods is more significant than the cyclones on the social and economic activities. It was observed an increasing trend in the all the extreme events, except the cyclones.
Cyclones • Floods • Extreme events • Regression analysis • Economic activities
The climate of India is dominated by the monsoon season (June to September). India witnessed a worst drought in the year 1918. The cyclones in 1971, droughts of 1972 and 1987, heat wave in 1995 and 1998 and cold wave in 2003 killed so many people in Bangladesh. The subcontinent has experienced a super cyclone was a major natural disaster in the year 1999. As the data pertaining to the occurrence of extreme weather events and their impact is scatter in publications and literature the analysis of the extreme events of the subcontinent and the research on their pattern is also scanty. When the ecosystem and society is unable to cope up with the effectiveness of the extreme weather event, then it becomes a disaster. The reasons for the extreme weather event may be the exponential growth of population, increasing greenhouse gases and industrial revolution which have changed the climate. Extremes of summertime heat have a greater impact on human health than any other severe weather in the United States 9, with elderly people being most at risk. Increased heat stress has increased the mortality rate in US [1]. Analysis of extreme weather events over Australian region showed an increase in extreme wet conditions, heavy rainfall, frequency of extreme warm and cool days, and a decrease in the frequency of incidence of tropical cyclones [2]. M Verdecchia et.al reported the results of a climate simulation for doubling of atmospheric carbon dioxide concentration over the European region [3].
Temperature and precipitation extremes and their potential future changes are evaluated in an ensemble of global coupled climate models participating in the Intergovernmental Panel on Climate Change (IPCC) diagnostic exercise for the Fourth Assessment Report (AR4) [4]. Under enhanced greenhouse conditions, return periods for extreme precipitation events are shorter and there is a general increase in the intensity of precipitation and number of wet spells in most areas. There is a decrease in frequency of cold temperature extremes and an increase in hot extremes in many areas. Greenhouse gases and climate variability was reported by [5]. David R. Easterling et al. reported that the observational data analysis showed an increasing trend in the precipitation, and changes in extreme temperatures [6]. Whereas the Model output has showed a increase in high temperatures and decrease in extreme low temperatures and increase in extreme precipitations.
To study the extreme events ranging from globally warm years to locally extreme rainfall intensities, data on a daily time scale is required. The assessment of climatological trends in the frequency of rare and extreme weather events using stochastic concept of binomial distributed counts, the probability of moderately rare events decreases rapidly with shorter record length, but does not significantly increase with longer length when very rare events are considered [7]. Due to the available data, the analysis was restricted the types of extreme weather events. Europe-average indices of wet extremes increase for the study period, although the spatial coherence of the trends is low [8].
It is important to assess the incidence and changes in climate extremes on a regional level that dependent on the analysis technique employed [9]. The studies Pall P et.al showed that the twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales and partially responsible for increases in heavy precipitation [10]. The data pertaining to the extreme weather events and their intensity over Indian subcontinent is scanty and scattered; very few attempts were carried out to analyze the extreme events [11, 12]. Significant rising trends in the frequency and the magnitude of extreme rain events in central India have been reported in a study using recent gridded dataset [13].
An increase in the mortality rate in India was reported during the heat waves succeeding the ElNino [14]. The paper aims at the analysis of the extreme weather events and their socio economic impact for the period 1967 to 2005. In the next sections the author presents the data and methodology used in the study, followed by results and discussion. Finally, the future scope of the study also presented.
From the reports on ‘Disastrous Weather Events’ published by India Meteorological Department (IMD), New Delhi the author has extracted the data on occurrence of extreme climate events and their impacts for the period 1967 to 2006. Due to qualitative nature of the data during the period 1967-1977, the data has been extracted from the reports published by Ministry of Agriculture and Ministry of Home Affairs. The features such as intensity, magnitude, location and date of occurrence and estimates of harm of the flood, tropical cyclone, heat wave, cold wave, also gale, squall, lightning, dust storm, hailstorm and thunderstorm have been pulled out from these reports (Table 1). Though the data the damage caused by these extreme events contains the human loss of life, affected human population, effected villages and agriculture and total economic loss, the mortality has been taken as damage indicator as the mortality data is consistent throughout the period of study. Regression analysis of annual data is used to obtain the annual trend of the extreme events. The statistics of extreme events over India and on state wise are presented. The paper aims at the analysis of the extreme weather events and their socio economic impact for the period 1967 to 2005.
Table 1. Top weather related hazards in India and trends in their occurrences (1978-2006).
| Event | Total number | Mortality | Percent mortality | Trend | P-value |
|---|---|---|---|---|---|
| Flood | 2973 | 43573 | 50.2 | 3.42 | 0 |
| Cyclone | 62 | 18853 | 21.7 | -0.04 | 0.08 |
| Heat wave | 373 | 8514 | 9.8 | 0.55 | 0 |
| Cold wave | 376 | 6668 | 7.7 | 0.29 | 0 |
| Thunderstorm | 1123 | 3490 | 4 | 1.9 | 0 |
| Lightning | 1353 | 3395 | 3.9 | 2.75 | 0 |
| Hailstorm | 934 | 989 | 1.1 | 1 | 0 |
| Dust storm | 146 | 584 | 0.7 | 0.17 | 0 |
| Squall | 284 | 362 | 0.4 | 0.35 | 0 |
| Gale | 245 | 291 | 0.3 | 0.12 | 0.25 |
Table 2 depicts the leading states in the number of extreme events and their impact on the socio economics. The Spatial distribution of events has been examined by associating each event with one (or more) states. From the Table 2, it is evident that Maharashtra is the leading position in experiencing the total number of extreme events, as it witnessed.
Table 2. Leading states in the extreme events by number and mortality.
| Extreme Event | No. of Event | Mortality |
|---|---|---|
| Cold wave | Bihar | Bihar |
| Cyclone | Andhra Pradesh | Orissa |
| Dust storm | Uttar Pradesh | Uttar Pradesh |
| Flood | Maharashtra | Uttar Pradesh |
| Gale | Kerala | Orissa |
| Hail storm | Maharashtra | Bihar |
| Heat wave | Rajasthan | Andhra Pradesh |
| Lightning | Maharashtra | Maharashtra |
| Squall | AS | WB |
| Thunderstorm | WB | WB |
| Total events | MH | OR |
It also leads in number of occurrences of flood, hailstorm and lightning. Bihar is in forefront with maximum number of cold wave occurrence. Cyclone landfall is highest in Andhra Pradesh (AP). UP leads in dust storm. Gale activity is greatest in Kerala. Heat wave occurrence is highest in Rajasthan. Squall occurrence is in its peak spatially in Assam. Thunder storm activity is greatest in West Bengal (WB). It is evident that leading sates in mortality does not necessarily correspond to those leading in occurrences. For example AP leads in occurrences of cyclone while Orissa (OR) leads in its mortality. This reveals that exposure of the people to the events and their adaptive capacity play important role in weather hazards impact.
Foregoing analysis depicted following conclusions: Major share of occurrence of climate extremes is due to floods; and cyclone which has most devastating impact has least share.
Total number of climate extremes considered in the study is significantly increasing in India. Except cyclone and gale all the extremes depict significant increasing trend. Total number of climate extremes considered in the study is significantly increasing in India. Except cyclone and gale all the extremes depict significant increasing trend. Maharashtra is the leading state in total number of events and floods while Rajasthan, Bihar and Andhra Pradesh are leading in heat wave, cold wave and cyclone respectively. Almost all the states depict increasing trends in heat wave and flood occurrences. Assessment of occurrence of the climate extremes needs more spatiotemporal details for the study and formulation of policy for impact, vulnerability and adaptation of climate sensitive sectors and regions. The paper aims at the analysis of the extreme weather events and their socio economic impact for the period 1967 to 2005.
Citation: Boppe, S. and Sharma, A . Impact of Extreme Weather Events in India on Human Life - A Study. J Climatol Weather Forecast. 2022, 10 (5), 001-002
Received: 18-Apr-2022, Manuscript No. JCWF-22-16908; Editor assigned: 19-Apr-2022, Pre QC No. JCWF-22-16908 (PQ); Reviewed: 10-May-2022, QC No. JCWF-22-16908 (Q); Revised: 12-May-2022, Manuscript No. JCWF-22-16908 (R); Published: 21-May-2022, DOI: 10.35248/2332-2594.22.10 (5).347
Copyright: ©2022 Boppe S. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
