Changes in some Weather Characteristics in India

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Changes in some Weather Characteristics in India
S. K. Dash Acknowledgements to Co-authors in
papers J. C. R. Hunt, F. Giorgi, U. C. Mohanty,
S. R. Kalsi, K. Prasad, R. K. Jenamani, M. S.
Shekhar, M. Kulkarni and S. K. Panda Centre
for Atmospheric Sciences Indian Institute of
Technology Delhi Hauz Khas, New Delhi 110 016
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Outline of the talk

• Introducing the inhomogeneous aspects
• Changes in surface temperature
• Trends in intensities and spells in rainfall
• Summer monsoon weakening?
• Evaluation of RegCM3 in simulating monsoon
• Regional Climate Change Hyper-Matrix Framework

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Inhomogeneous aspects of weather and climate in
India
4
Topographical map of India
5
Five homogeneous zones of India. The numbers
inside the zones indicate mean monsoon rainfall
(mm), standard deviation (mm) and coefficient of
variation () from top to bottom respectively
Dash et al., 2002, Mausam, 53(2), 133-144
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Seven zones based on surface temperature
http//www.tropmet.res.in
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Most Recent Weather Events in India
Extreme Weather Events in India

• Flash Floods Landslides
• Cold Wave, Fog, Snow
• Storms and Avalanches
• Floods Droughts
• Tropical Cyclones and
• Tidal Waves
• Heat Waves

Chiang Mai2007 The Science and Practice of flood
Disaster In Urbanising Monsoon
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Changes in Surface Temperature
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Changes in the maximum and minimum temperatures
in different zones during the last century. The
upper numbers indicate maximum and lower ones
represent minimum temperatures. Also sign is
for an increase and is for decrease. The map of
seven zones has been obtained from
http//www.tropmet.res.in
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Surface air temperature (0C) changes during
different seasons averaged over the whole of
India ( sign indicates an increase and
represents decrease)
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NORTH
Maximum Temperature Anomaly(oC)
Anomalies of average land surface maximum air
temperatures (0C) relative to their respective
mean (1901-2003) value over northern and southern
parts of India. The smoothed curve is obtained
using 21- point binomial filter.
SOUTH
Maximum Temperature Anomaly(oC)
Dash and Hunt, 2007, Current Science, Vol 93
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NORTH
Minimum Temperature Anomaly (oC)
Anomalies of average land surface minimum air
temperatures (0C) relative to their respective
mean (1901-2003) value over northern and southern
parts of India. The smoothed curve is obtained
using 21- point binomial filter.
SOUTH
Minimum Temperature Anomaly (oC)
Dash and Hunt, 2007, Current Science, Vol 93
13
DELHI
MUMBAI
Total cloud amount Anomaly ()
Total cloud amount Anomaly ()
Year
Year
KOLKATA
CHENNAI
Total cloud amount Anomaly ()
Total cloud amount Anomaly ()
Year
Year
Anomalies of average total cloud amount () for
June, July, August and September relative to
their respective mean (1960-2004) value over four
metropolitan cities in India. The smoothed curve
is obtained using 21-point binomial filter.
Dash and Hunt, 2007, Current Science, Vol 93
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Variation of the number of fog days in the month
of January for 1989 to 2003 at New Delhi and the
corresponding 5-year running mean values.
Trends of average duration of visibility (hrs /
day) lt 200 meters for 1964 to 1998 at Delhi.
Dash et al., 2007, Climatic Change, DOI 10.1007
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Highest maximum temperature recorded at some
stations during heat wave of Andhra Pradesh in
May June 2003 and the earlier recorded highest
maximum temperature.
Dash et al., 2007, Climatic Change, DOI 10.1007
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Some inferences on surface temperature

• Indication of warming Differences in the trends
  in the minimum and maximum temperatures in the
  North and south. Different impacts of Ocean and
  Himalayas?
• Asymmetry in the increasing temperature trends
  between different seasons. In last 2-3 decades
  the increase in maximum and minimum temperatures
  during October to February is about 0.30C more
  than during rest of the months.
• Frequent occurrences of weather events leading to
  the perception of extreme cases Climate
  equilibrium?

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Trends in the intensity and spells of rain
events in India
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Classification of rain events based on intensities

• Gamma Cumulative Distribution Function was
  fitted to the daily rainfall values to categories
  the rain events in different groups.
• The classification is made as follows
• Heavy Inverse of gamma CDF for
  probability
• 0.99
• Moderate Inverse of gamma CDF for
  probabilities
• lie between 0.4 lt0.99
• Low Inverse of gamma CDF for
  probability
• lt 0.4

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Characteristics of rain events based on duration
of spells

• Long Spell Consecutive rainfall for 4 days
• Short Spell Consecutive rainfall for less than
  4 days
• Dry Spell lt2.5mm/day
• Prolonged Dry Spell consecutively dry for
  4 days

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The moderate rainfall values (mm/day) defined as
inverse of the gamma cumulative distribution for
probability 0.4 to lt 0.99
Dash et al. submitted to JGR
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The number of long spell rainfall events shows
decreasing trend in monsoon season in last 54
years. This suggests that planetary scale
motions, may be southwest monsoon over the
country is weakening.
Number of long spell rain events Continuous
rainfall for gt 4 days over all India in
different seasons. The red line is linear trend
line.
Dash et al. submitted to JGR
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Number of short spell rain events (Continuous
rainfall for lt 4 days) over all India in
different seasons. The red line is linear trend
line.
Short spell rainfall events over India show
increasing trend. This is an indication of
increasing or intensifying of meso-scale
conventions and synoptic scale motions.
Dash et al. submitted to JGR
23
Number of dry spells and prolonged dry spells
over all India in monsoon season. Dashed line
is linear trend line.
Dash et al. submitted to JGR
24
Summary of trends in heavy and moderate rain
events in different Indian regions for the summer
monsoon season. Asterisks denote significant
trend at 5 level.
Dash et al. submitted to JGR
25
Summary of trends in long, short, dry and
prolonged dry spells of rainfall in different
Indian regions for the monsoon season. Asterisks
denote significant trend at 5 level.
Dash et al. submitted to JGR
26
Some inferences on rain events

• Heavy rain events increase and moderate low
  events decrease
• Short dry spells increase and long spells
  decrease
• Trends not statistically significant in all zones
• Weakening of monsoon circulation?

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Weakening of summer monsoon circulation?
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Difference between the 850hPa mean monsoonal
wind speeds in the two decades (1991-2000) and
(1951-1960). The shaded region shows the
significant change calculated using t test at 5
level.
Dash et al. submitted to JGR
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(a)
(b)
Eleven-year running means of annual
frequency of disturbances with the minimum
intensity of (a) monsoon depressions and (b) low
pressure areas over the Indian region
(1889-2003).
Dash et al., 2004, On the decreasing frequency of
monsoon depressions over the Indian region,
Current Science,86(10), 1404-1411.
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(a)
Latitudinal variation of zonal wind component in
July over Indian region between 550E-950E a)850
hPa b)200 hPa
(b)
Dash et al., 2004, On the decreasing frequency of
monsoon depressions over the Indian region,
Current Science,86(10), 1404-1411.
31
(a)
(a) 11-year running means of anomalies of
horizontal wind shear at 850hPa in July between
latitudes 00 and 250N averaged over longitudes
550E to 950E.
(b)
(b) 11-year running means of vertical wind shear
anomalies in July between 850 hPa and 200 hPa
levels averaged over the Indian region 00 to 250N
and 550E to 950E.
Dash et al., 2004, On the decreasing frequency of
monsoon depressions over the Indian region,
Current Science,86(10), 1404-1411.
32
(a) 11-year running means of anomalies of
horizontal wind shear at 850hPa in August between
latitudes 00 and 250 N averaged over longitudes
550E to 950E.
(a)
(b) 11-year running means of vertical wind shear
anomalies in August between 850 hPa and 200 hPa
levels averaged over the Indian region 00 to 250
N and 550E to 950E.
(b)
Dash et al., 2004, On the decreasing frequency of
monsoon depressions over the Indian region,
Current Science,86(10), 1404-1411.
33
Simulation of Summer Monsoon by RegCM3
34
Model domain used in RegCM3 and the five
homogeneous zones of India such as North West
India (NWI), West Central India (WCI), Central
Northeast India (CNI), North East India (NEI) and
South Peninsular India (SPI) (Parthasarathy et
al., 1995)
Central Lat and Lon- 20oN, 80oE
101 X 115 Points along XY direction
Domain covers 55oE to 105oE and 5oS to 45oN
with Grid distance- 55 Km
Dash et al., 2006, Theor. Appl. Climatol, special
issue, 1-12.
35
JJAS average wind (m/s). The left and right
panels refer to levels 850hPa and 200hPa
respectively. (a) and (b) are winds with Kuo
scheme whereas (c) and (d) are those with Grell
scheme. (e) and (f) are wind differences
(Grell-Kuo) and (g) and (h) are NCEP/ NCAR
reanalyzed winds
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(b)
(a)
14
(d)
16
(c)
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The characteristics of the lower and upper level
monsoon winds simulated with the Kuo scheme are
weaker than the Grell scheme. The values of wind
at 850hPa and 200hPa with Grell scheme are close
to that of NCEP/NCAR Reanalysis.
2.4
(f)
(e)
4.5
16
(g)
(h)
20
Dash et al., 2006, Theor. Appl. Climatol, special
issue, 1-12.
36
150
260
a
b
270
d
c
JJAS average accumulated rainfall (cm) for (a)
Kuo, (b) Grell, (c) Grell Kuo and (d) GPCC
rainfall
Dash et al., 2006, Theor. Appl. Climatol, special
issue, 1-12.
37
Comparison of JJAS mean rainfall (cm) over
All-India and its five homogeneous zones
simulated by RegCM3 in Kuo and Grell convection
schemes with IMD observed rainfall
Good agreement between RegCM3 and IMD rainfall
for AI, NWI, WCI and SPI in all four
years. Precipitation is underestimated over CNI
and NEI.
Grell scheme simulates more rainfall than Kuo
scheme for all four years for AI and its five
homogeneous zones. Precipitation with Grell
scheme is more realistic than Kuo scheme.
Dash et al., 2006, Theor. Appl. Climatol, special
issue, 1-12.
38
Standardized anomaly of daily rainfall over India
in JJAS as simulated by RegCM3 for the years
1993-1996. The solid and shaded arrows below and
above the vertical bars represent the days of
break and active monsoon phases respectively as
defined by IMD.
Dash et al., 2006, Theor. Appl. Climatol, special
issue, 1-12.
39
Region over which 10cm of snow has been
introduced uniformly in the snow experiment
Shekhar and Dash, 2005, Current Science, 88(11),
1840-1844.
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Differences (no-snow minus snow) in the
composites of four years (1993 to 1996) of temp
at 500hPa in (a) AM, (b) JJAS, surface pressure
in (c) AM, (d) JJAS, wind at (e) 850hPa and (f)
200hPa simulated by RegCM3
a
b
High snow depth over Tibet is characterized by
low temperature at 500hPa and high surface
pressure. These are responsible for weakening of
Indian summer monsoon circulation. Westerly wind
at 850hPa and easterly at 200hPa is stronger over
the Arabian Sea and Indian Peninsula in the
no-snow experiment than in the snow experiment.
c
d
e
f
Shekhar and Dash, 2005, Current Science, 88(11),
1840-1844.
41
a
c
b
f
d
e
Comparison of JJAS mean rainfall (cm) over (a)
All India and its five homogeneous zones as
simulated by RegCM3 in no-snow and snow
experiments
Decrease of rainfall 30 for AI 23 for NWI 20
for WCI 25 for CNI 15 for SPI
For AI (decrease in rainfall) 37 in 1993 38 in
1994 20 in 1995 25 in 1996
Shekhar and Dash, 2005, Current Science, 88(11),
1840-1844.
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Comparison of rainfall simulated by IITD Spectral
GCM, RegCM3 and measured by IMD in 2002 and 2003
Dash et al. submitted to Advances in Geosciences
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The Regional Climate Change Hyper Matrix Framework
F. Giorgi, N.S. Diffenbaugh, X. J. Gao, E.
Coppola, S. K. Dash, O. Frumento, S. A. Rauscher,
A. Remedio, I. Seidou Sanda, A. Steiner, B. Sylla
and A. S. Zakey
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Regional Climate Change Hyper-Matrix Framework
(HMF)
Internal Variability
RCD Configuration
GCM Configuration
Forcing Scenario
Experiment (i,j,k )
Geographic Region
RCD Approach
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First Phase of the Regional Climate Change
Hyper-Matrix Framework

• Initial hyper-matrix framework is built on the
  Abdus Salam International Centre for Theoretical
  Physics (ICTP)-based regional climate network of
  scientists (RegNET), the ICTP Regional Climate
  Model version3 (RegCM3) and the AOGCM ensemble of
  the third phase of the Coupled Model
  Intercomparison Project (CMIP3).
• In the first phase we will investigate the
  geographical uncertainty dimensions, with six
  continential-scale model domains (North and
  Central America, South America, Europe, Africa,
  Central Asia and South and East Asia) at 25 k.m.
  grid spacing (a state-of-art resolution for long
  term RCM experiments)
• Focus will be initially on the near past (as
  reference period and for model evaluation) and
  the near future (1980-2040) for which the
  scenario uncertainty is less relevant and on the
  late 21st century/early 22nd century (2071-2100),
  for which the signal is larger.
• The scenario uncertainty is very important, and
  we plan to experiments from the CMIP3 data set
  and/or new simulations generated for the IPCC
  Fifth Assessment Report (IPCC AR5).

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Thank You