Title: An assessment of climate variability and climate change on heat wave characteristics in India
Abstract: Heat wave is an
important class of climate hazard due to its impact on human health. Changes in
characteristics of heat waves such as intensity, duration, frequency and
geographical exposure have the potential to have serious societal impacts.
Observations suggest that in some parts of the world such changes are already
happening, leading to impact on human health in terms of heat-stress and
mortality. Heat waves are expected to intensify around the globe in the future,
with potential increase in heat stress and heat-induced mortality in the
absence of adaptation measures. India has a high current exposure to heat
waves, and with limited adaptive capacity, impacts of increased heat waves
might be quite severe. An understanding of heat wave characteristics is a
pre-requisite to assess vulnerabilities due to heat waves. The primary objective of this thesis was to understand and
analyze the climatic mechanisms that are driving changes in heat waves in
India. Daily observed maximum temperature data and a combination of re-analysis
data for upper air circulation fields were used to identify key mechanisms
responsible for occurrences of heat waves in India. Using observed data, this
study explored whether changes in internal variability in the climate system
are driving observed trends, or else the observed changes could be related to
anthropogenic influence. Multiple research tools, methods and data were
employed including interpolated station data, re-analyses data, general
circulation model outputs and regional climate model outputs to address
fundamental questions about the influence of climate variability and climate
change on heat wave characteristics. Main results of the thesis are highlighted
as: 1. This study showed that heat waves during El Ni~no years
were longer and hotter, and argues that this is related to a delay in the onset
of the Indian Summer Monsoon. Further, it was found that the shift in the
circulation pattern due to El Ni~no resulted in (i) weakening of
south-westerlies in the Arabian sea region, and (ii) the occurrence of a larger
number of clear sky days over India. This explains heat waves during El Ni~no years
were warmer and had a longer duration. 2. This study found that anthropogenic influence is
detectable in the extreme temperatures over India. Further, using record breaking statistics the
study showed that the number of local record breaking seasonal extremes, in
climate with trends, were five times larger than the climate with no trends.
Seasonal extremes are often associated with heat wave like conditions; this
implies that the climate change may increase the chance of occurrence of extreme
temperatures during heat waves. 3. Although the debate on the role of natural variability
over climate change for the occurrence of individual events of extreme is still
valid, results of this study indicate that the anthropogenic influence on
general trends in extremes cannot be overruled for occurrence of individual
record braking event. This is particularly important for India to understand
the risk due to record breaking extremes, keeping its existing vulnerabilities
in mind. 4. This study also presents the first projections of future
heat waves in India based on multiple climate models and scenarios for CMIP5
data. Projections from climate models inform that heat waves are projected to
be more intense, longer duration, frequent and has a tendency to occur earlier
in the year. Southern India, currently not influenced by heat waves, is
expected to be severely affected by the end of the twenty-first century.
Projections indicate that a sizable part of India will experience heat stress
conditions in the future. In northern India, the average number of days with
extreme heat stress condition during pre-monsoon hot season will reach 30. The
intensification of heat waves might lead to severe heat stress and increased
mortality. 5. Further, the study suggests that CORDEX-RCMs (regional
climate models for South Asia) are able to reproduce the observed inter-annual
and seasonal variability of temperature better than their driving GCMs. This
may be a reason why RCMs provide useful simulations of severe heat wave
characteristics than their driving GCMs. However, for projection of heat wave
characteristics CORDEX-RCMs show a higher inter-model uncertainty in comparison
to their driving GCMs.
Publication Year: 2017
Publication Date: 2017-04-23
Language: en
Type: dissertation
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