coldest night (about 0.13 °C per decade). The significant
increase in the intensity of warmest day during pre-monsoon
(about 0.29 °C per decade) and winter (about 0.26 °C per
decade) seasons contribute largely to the accelerated annual
increase in the intensity of the warmest day over India in the
recent period (Table 2.5). The annual increase in the intensity of the warmest night is dominated by the significant
increases in the winter season (about 0.17 °C per decade).
The significant decrease in the intensity of coldest night
during the pre-monsoon (about 0.28 °C per decade) and
monsoon (about 0.15 °C per decade) seasons contribute to
the accelerated annual decrease in the intensity of the coldest
night over India during the recent period 1986–2015.
Significant increasing (decreasing) trends in heatwaves
(cold waves) are observed during the hot (cold) weather
season over most parts of India (Rohini et al. 2016, 2019;
Ratnam et al. 2016; Pai et al. 2017). These periods containing consecutive extremely hot days (cold nights) are
defined when departure in daily maximum (minimum)
temperature exceeds (are below) the objectively defined
threshold value (Pai et al. 2017). The observed frequency,
total duration and maximum duration of heat waves during
the hot summer months (April–June) are increasing over
central and north-western parts of India (Rohini et al. 2016).
The increase in the number of intensive heat waves between
March and June in India over a recent-past decade was
attributed to the presence of an upper-level cyclonic anomaly
over the west of North Africa and a cooling anomaly in the
Pacific (Ratnam et al. 2016). A significant decadal variation
was observed in the frequency, spatial coverage and area of
the maximum frequency of heat (cold) wave events over
India (Pai et al. 2017). The variability of heat waves over
India was found to be influenced by both the tropical Indian
Ocean and central Pacific sea surface temperature anomalies.
A noticeable increase (decrease) in the frequency of
heatwave days was observed during the El Nino (La Nina)
events. It is also assessed that the spatial extent affected by
concurrent meteorological droughts and heatwaves is
increasing across India during the period 1981–2010 relative
to the base period 1951–1980 (Sharma and Mujumdar
2017).
2.3 Projected Temperature Changes Over
India
The projected future changes in temperature over India are
assessed using the recently available high-resolution regional climate information from CORDEX South Asia and
NEX-GDDP datasets generated by downscaling the
CMIP5 AOGCM global-scale climate change projections
using dynamical (i.e. regional climate modelling) and statistical (i.e. empirical) methods, respectively, (see more
details in Box 2.3). The downscaled future projections in
temperature are assessed over the Indian land area, by
masking out the oceans and territories outside the geographical borders of India, and are reported for two 30-year
future periods: 2040–2069 and 2070–2099 relative to the
reference baseline period: 1976–2005, representing the
mid-term and long-term changes in future climate over India.
Box 2.3 Downscaled High-Resolution CORDEX
South Asia and NEX-GDDP Climate Change
Projections
The coupled Atmospheric-Ocean General Circulation
Models (AOGCMs) are the primary tools used to
assess the nature and extent of the anthropogenic
changes that are leading to global climate change since
1950s (Bindoff et al. 2013). The AOGCMs
Table 2.5 Observed changes in India land mean annual and seasonal intensity indices of daily extreme temperatures for the periods 1951−2015
and 1986–2015
Season
Linear trends 1951–2015 (°C per decade)
Linear trends 1986–2015 (°C per decade)
Coldest night
(TNn)
Coldest day
(TXn)
Warmest night
(TNx)
Warmest day
(TXx)
Coldest night
(TNn)
Coldest day
(TXn)
Warmest night
(TNx)
Warmest day
(TXx)
Annual
0.00 ± 0.07
−0.01 ± 0.06 −0.02 ± 0.05 0.07
*
± 0.05
0.13
* ± 0.12
0.02 ± 0.13
0.12
*
± 0.10
0.21
*
± 0.11
Winter (Dec–
Feb)
−0.01 ± 0.08 −0.09
*
± 0.08 −0.01 ± 0.08 0.02 ± 0.09
−0.08 ± 0.19 −0.10 ± 0.28 0.17
*
± 0.14
0.26
*
± 0.18
Pre-monsoon
(Mar–May)
−0.02 ± 0.09 −0.02 ± 0.10 −0.09
* ± 0.07 0.05 ± 0.07
0.28
* ± 0.20
−0.03 ± 0.32 0.10 ± 0.16
0.29
*
± 0.18
Monsoon (Jun–
Sep)
−0.01 ± 0.05 0.04 ± 0.05
−0.02 ± 0.04 0.09
*
± 0.06
0.15
* ± 0.09
0.10 ± 0.15
0.05 ± 0.09
0.12 ± 0.20
Post-monsoon
(Oct–Nov)
0.05 ± 0.09
0.04 ± 0.09
0.03 ± 0.08
0.10 ± 0.10
0.19 ± 0.19
0.01 ± 0.25
0.20 ± 0.22
0.17 ± 0.26
Estimates are derived from the IMD gridded station data. Trends and significance have been calculated as in Table 2.1. Bold values with star sign (*)
indicate that trend is significant (i.e. a trend of zero lies outside the 90% confidence interval)
30
J. Sanjay et al.
increase in the intensity of warmest day during pre-monsoon
(about 0.29 °C per decade) and winter (about 0.26 °C per
decade) seasons contribute largely to the accelerated annual
increase in the intensity of the warmest day over India in the
recent period (Table 2.5). The annual increase in the intensity of the warmest night is dominated by the significant
increases in the winter season (about 0.17 °C per decade).
The significant decrease in the intensity of coldest night
during the pre-monsoon (about 0.28 °C per decade) and
monsoon (about 0.15 °C per decade) seasons contribute to
the accelerated annual decrease in the intensity of the coldest
night over India during the recent period 1986–2015.
Significant increasing (decreasing) trends in heatwaves
(cold waves) are observed during the hot (cold) weather
season over most parts of India (Rohini et al. 2016, 2019;
Ratnam et al. 2016; Pai et al. 2017). These periods containing consecutive extremely hot days (cold nights) are
defined when departure in daily maximum (minimum)
temperature exceeds (are below) the objectively defined
threshold value (Pai et al. 2017). The observed frequency,
total duration and maximum duration of heat waves during
the hot summer months (April–June) are increasing over
central and north-western parts of India (Rohini et al. 2016).
The increase in the number of intensive heat waves between
March and June in India over a recent-past decade was
attributed to the presence of an upper-level cyclonic anomaly
over the west of North Africa and a cooling anomaly in the
Pacific (Ratnam et al. 2016). A significant decadal variation
was observed in the frequency, spatial coverage and area of
the maximum frequency of heat (cold) wave events over
India (Pai et al. 2017). The variability of heat waves over
India was found to be influenced by both the tropical Indian
Ocean and central Pacific sea surface temperature anomalies.
A noticeable increase (decrease) in the frequency of
heatwave days was observed during the El Nino (La Nina)
events. It is also assessed that the spatial extent affected by
concurrent meteorological droughts and heatwaves is
increasing across India during the period 1981–2010 relative
to the base period 1951–1980 (Sharma and Mujumdar
2017).
2.3 Projected Temperature Changes Over
India
The projected future changes in temperature over India are
assessed using the recently available high-resolution regional climate information from CORDEX South Asia and
NEX-GDDP datasets generated by downscaling the
CMIP5 AOGCM global-scale climate change projections
using dynamical (i.e. regional climate modelling) and statistical (i.e. empirical) methods, respectively, (see more
details in Box 2.3). The downscaled future projections in
temperature are assessed over the Indian land area, by
masking out the oceans and territories outside the geographical borders of India, and are reported for two 30-year
future periods: 2040–2069 and 2070–2099 relative to the
reference baseline period: 1976–2005, representing the
mid-term and long-term changes in future climate over India.
Box 2.3 Downscaled High-Resolution CORDEX
South Asia and NEX-GDDP Climate Change
Projections
The coupled Atmospheric-Ocean General Circulation
Models (AOGCMs) are the primary tools used to
assess the nature and extent of the anthropogenic
changes that are leading to global climate change since
1950s (Bindoff et al. 2013). The AOGCMs
Table 2.5 Observed changes in India land mean annual and seasonal intensity indices of daily extreme temperatures for the periods 1951−2015
and 1986–2015
Season
Linear trends 1951–2015 (°C per decade)
Linear trends 1986–2015 (°C per decade)
Coldest night
(TNn)
Coldest day
(TXn)
Warmest night
(TNx)
Warmest day
(TXx)
Coldest night
(TNn)
Coldest day
(TXn)
Warmest night
(TNx)
Warmest day
(TXx)
Annual
0.00 ± 0.07
−0.01 ± 0.06 −0.02 ± 0.05 0.07
*
± 0.05
0.13
* ± 0.12
0.02 ± 0.13
0.12
*
± 0.10
0.21
*
± 0.11
Winter (Dec–
Feb)
−0.01 ± 0.08 −0.09
*
± 0.08 −0.01 ± 0.08 0.02 ± 0.09
−0.08 ± 0.19 −0.10 ± 0.28 0.17
*
± 0.14
0.26
*
± 0.18
Pre-monsoon
(Mar–May)
−0.02 ± 0.09 −0.02 ± 0.10 −0.09
* ± 0.07 0.05 ± 0.07
0.28
* ± 0.20
−0.03 ± 0.32 0.10 ± 0.16
0.29
*
± 0.18
Monsoon (Jun–
Sep)
−0.01 ± 0.05 0.04 ± 0.05
−0.02 ± 0.04 0.09
*
± 0.06
0.15
* ± 0.09
0.10 ± 0.15
0.05 ± 0.09
0.12 ± 0.20
Post-monsoon
(Oct–Nov)
0.05 ± 0.09
0.04 ± 0.09
0.03 ± 0.08
0.10 ± 0.10
0.19 ± 0.19
0.01 ± 0.25
0.20 ± 0.22
0.17 ± 0.26
Estimates are derived from the IMD gridded station data. Trends and significance have been calculated as in Table 2.1. Bold values with star sign (*)
indicate that trend is significant (i.e. a trend of zero lies outside the 90% confidence interval)
30
J. Sanjay et al.