Severe Thunderstorm

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Severe Thunderstorm Observational Regional
Modeling (STORM) Programme
National Coordinate Programme, Sponsored by Dept.
of Science and Technology, Gov. of India
Prof. U.C. Mohanty
Centre for Atmospheric Sciences, Indian Institute
of Technology, Delhi Hauz Khas, New Delhi-110016,
India
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Acknowledgement
Dept. of Science and Technology, Indian
Meteorological Department, Indian Air force,
Indian Army, NE- SAC, NCMRWF, IITM, IIT Delhi,
IIT Kharagpur, Calcutta University, Dept. of
Space, Ministry of Earth Sciences and
others. Dr. D. R. Sikka, Dr. P. V. Joseph, Dr.
P. Sanjeeva Rao, Prof. S. K. Dube, AVM. Ajit
Tyagi, Mr. R. C. Bhatia. Litta A. J, Sujata
Pattanayak and Ashish Routray
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Major Participating agencies

• 35 Institutions and several individual scientists
  
• DST, New Delhi
• IMD Delhi / RMC, Kolkata / RMC Guwahati
• NCMRWF, Noida
• IIT New Delhi
• IIT Kharagpur
• IAF, Directorate of Meteorology, New Delhi
• Indian Navy (DNOM), New Delhi
• DRDO station, Chandipur
• IITM, Pune
• University of Calcutta, Kolkata

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OUTLINE

• Introduction
• Meso-scale model capabilities (Glimpses of
  results)
• Thunderstorm Climatology
• STORM Programme
• Mesoscale simulation of a severe thunderstorm
• Future Challenges

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INTRODUCTION

• Convection is the most dominant physical process
  in tropics, which determines tropical rainfall
  circulation and can be explicitly resolved with
  high resolution mesoscale models.
• Meso convective systems broadly divided into two
  groups
• Induced by surface inhomogeneity forced by
  terrain and surface characteristics features
  (systems like sea and land breezes, mountain
  valley winds, urban circulation).
• Synoptically induced forced by instabilities due
  to large scale disturbances (systems like
  cyclones, squall lines, cloud clusters etc.).

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Weather and Climate in the Tropics
Dictated by
CONVECTION
Mesoscale in Nature
Intense Convection Processes
Leading To
MESO-NETWORK STATIONS
SEVERE THUNDERSTORMS TORNADOES
Tropical Synoptic systems ITCZ, Monsoons and TCs
Organizes
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Meso-scale model capabilities (Glimpses of
results)
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Simulation of Extreme Weather Events

• Tropical cyclone (1995 1999 2006 2007)
• MM5, WRF (ARW), HWRF
• MTC (25-27 June 2005) WRF (ARW)
• Mumbai heavy rainfall event (25-28 July 2005)
  WRF (ARW)
• Western disturbances and associated heavy
  snowfall (21-25 Jan. 1999) MM5
• Severe Thunderstorm (20 May 2006)
• WRF (NMM)

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TRACK OF ORISSA SUPER CYCLONE
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Vector displacement error in track forecast
Time ? Case ? Initial positional error in large scale analysis (in km) 00 hours 12 hours 24 hours 36 hours 48 hours
Case-1 (25-31 Oct. 1999) 122 00 20 31 31 31
Case-2 (15-19 Oct. 1999) 584 104 120 146 144 137
Case-3 (19-23 Nov. 1998) 133 39 56 46 306 350
Case-4 (13-16 Nov. 1998) 559 31 82 107 136 162
Case-5 (15-20 May 1997) 347 81 126 156 307 329
Case-6 (4-7 Nov. 1996) 358 00 32 86 115 -
Case-7 (22-26 Nov. 1995) 545 00 33 35 115 248
Case 8 (7-10 Nov. 1995) 165 22 56 46 112 201
Average 352 35 66 82 158 208
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Comparison of 24 hours accumulated precipitation
(mm) as obtained from NASA (observed), MM5, WRF
for Bay of Bengal cyclone Mala
Day-1
Day-2
Day-3
OBS
MM5
WRF
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Track of the cyclone Mala from WRF and MM5 model
simulations with different initial conditions
WRF
MM5
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Track of the Arabian Sea cyclone Gonu(2-7 June
2007)
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Observed and Model simulated accumulated
precipitation valid on 27 July 2005 0300 UTC
Station recorded 24 hrs accumulated rainfall (cm)
on 27 July 20050300 UTC
Simulated 24 hrs accumulated rainfall (cm) on 27
July 20050300 UTC
TRMM accumulated precipitation for 25-27 July 2005
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Cell-A
Cell-A
Cell-B
Cell-B
Cloud mixing ratio and circulation vectors
Rain water mixing ratio and circulation vectors
Cell-C
Cell-C
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24hrs accumulated day-1 rainfall (cm) valid on 03
UTC 26th June, 2005
TRMM (mm)
Simulation of MTC (Gujurat heavy rainfall)
3DV ANA
CNTRL
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Observed rainfall (cm)
S.No Station (Gujarat State) Name Rainfall (cm) Day-1 (03 UTC 260605) Rainfall (cm) Day-1 (03 UTC 260605) Rainfall (cm) Day-1 (03 UTC 260605)
S.No Station (Gujarat State) Name OBS CNTRL 3DV ANA
1 Gandevi 37 3 10
2 Valsad 30 3 10
3 Pardi 21 2 11
4 Chikhili 20 4 9
5 Bansda 15 4 7
6 Kamrej 16 8 17
7 Silvassa 14 4 12.5
8 Surat 17 6 18
9 Dhandhuka 13 3 2
10 Mangrol 13 15 10
11 Palsana 13 9 15
12 Bardoli 14 9 15
13 Valod 11 9.5 10
14 Vapi 10 2 10
15 Daman 9 4.3 6
16 Rajpipla 9 9.7 4
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Precipitation distribution all valid at 0300 UTC
over the region of study (a) Observed
precipitation (cm) and (b) Model predicted
precipitation (cm)
Day-1
22/01/1999
23/01/1999
MODEL SIMULATED
Day-2
OBSERVED
Western Disturbances
24/01/1999
Day-3
Day-4
25/01/1999
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Observed and simulated precipitation (cm) at some
of the station in Jammu Kashmir and Himachal
Pradesh
Sonamarg Sonamarg Haddan Taj Haddan Taj Gulmarg Gulmarg Manali Manali
Observed Simulated Observed Simulated Observed Simulated Observed Simulated
Day 1 2.1 2.5 4.3 3.3 2.7 1.7 4.7 3.7
Day 2 3.9 3.1 5.8 4.6 5.7 3.9 3.4 2.7
Day 3 4.7 3.5 5.0 5.5 8.6 6.8 5.5 4.9
Day 4 2.5 2.1 3.2 3.4 4.4 6.5 2.7 2.1
Accum-ulated 13.2 11.2 18.3 16.8 21.4 20.9 16.3 13.4
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Thunderstorm Climatology
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Important synoptic features favorable for severe
thunderstorms E and NE India

• Potentially unstable atmosphere.
• Low level moisture incursion (up to 1.5 km) and
  wind convergence
• A cyclonic circulation in the lower troposphere
  lying over Bihar, Orissa, Gangetic West Bengal
• Trough in the middle and upper troposphere
  Westerlies say between 500 to 200 hPa and close
  to 80?E. Anticyclonic circulation over the Bay
  between 500 and 200 hPa (mostly during later half
  of the month of May) can also provide divergent
  flow conditions as by the trough in the westerly.
  
• Subtropical westerly jet maxima over STORM
  region. During latter half of May month, it may
  be absent.
• Strong wind shear between 850 and 200 hPa.
• All these features have been highlighted in
  several previous studies by different
  investigators.

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Hail occurrences during a hundred years
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Monthly distribution of Hail storms in India
Diurnal variation of Hail storms in India
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ANNUAL THUNDERSTORM FREQUENCY
100
80
94.0
100
60
80
120
120
110.8
108.7
112.0
122.0
101.2
109.9
69.9
120.5
60
107.5
85.3
98.0
73.4
83.4
95.0
107.4
79.0
81.2
84.4
80
52.0
80
77.5
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THUNDERSTOM CLIMATOLOGY OVER INDIAN REGION
(TYAGI, MAUSAM 2007)
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Climatological Thunderstorm in West Bengal
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Severe Thunderstorm Climatology ( 21 years ) of
Guwahati Airport
Source IMD Aviation Manual
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STORM Programme
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What is STORM Programme?

• A Comprehensive Observational and Modeling study
  on genesis, evolution and life cycle of intense
  tropical convective activities over E and NE
  region of India during pre-monsoon period known
  as KAL BAISAKI through
• Meso-network observation
• Mesoscale analysis prediction systems

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Importance of STORM programme

• Thunderstorms are most spectacular weather
  phenomena, resulting from vigorous convective
  activity.
• The understanding and prediction of these weather
  events is a challenge due to lack of meso-scale
  observations and insufficient understanding.
• Realizing the importance of these weather events
  and their socio-economic impact, the STORM
  programme has been initiated.

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STORM-Objectives

• To understand genesis, development and
  propagation of severe thunderstorms
• To enhance the knowledge Dynamical and
  thermodynamical structure role of microphysical
  processes for intensification
• To study behavior of atmospheric electrification
  during intensification process and interaction
  with cloud microphysical processes
• Development of meso-scale prediction system with
  improved forecast skill

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Uniqueness of the Programme

• First of its kind in the tropical South Asia,
  especially over the E and NE Indian subcontinent.
• Comprehensive meso-network observations that
  overlaps the southern tip of MONSOON TROUGH.
• Site can be suffixed with existing major
  observational facilities such as DWR, Met.
  Towers, Buoys, AWS etc.

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• Location of Intense Land-Ocean Atmosphere
  Interaction (land falling tropical cyclones,
  land-sea breeze circulation systems, etc.)
• Multi-institutional interest on mesoscale studies
  over the region for various applications

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Socio-Economic Impact of Severe Thunderstorm (Kal
Baisaki)

• Severity of NORWESTERS next to Tropical Cyclones
  
• Average frequency of occurrence
• Kalbaisaki is 28 (5) in pre-monsoon
  period
• Tropical Cyclones (2) (1)
• Hail Storms and Squall Winds
• Loss of human life and animals
• Extensive damage to standing crops and property
• Highest lightning-associated casualty in the
  world.
• Highest frequency of hail storms in the world.
• Frequency of occurrence is second highest to that
  in the central regions of United States.
• May lead to flood in NE India
• Major aviation hazard with several reported air
  plane accidents.

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Severe Thunderstorm 22nd April 2003,
Dhubri,Assam.

• Number of affected Villages 6
• Population Affected 4900
• No. of human lives lost 35
• No. of persons with serious injuries 150
• No. of persons with minor injuries 1350
• No. of cattle head lost 517
• No. of poultry lost 1340
• No. of houses fully damaged 1350
• No of houses partially damaged 650
• Total estimated damage Rs. 2.00 Crore

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Proposed Additional Instrumentation

• AWS - meso-network of 100 AWS(Total 250)
• RS/RW - 4 stations
• Dropsondes - 1 (instrumented IAF aircraft)
• Wind Profilers - 3
• Mobile Doppler Radar - 1
• Research Ship at the
• Head Bay - 1
• Micro-tower - 4 with 6 levels of instruments
• Disdrometer - 3
• Atmospheric Electric
• Sensors - 1
• Aerosol Sampler - 1
• Aerosol particle
• sensor - 2
• Electric Mill - 3

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Deliverables

• A better insight into the genesis, evolution and
  propagation of Severe Thunderstorms
• Understanding of Dynamical and microphysical
  structure of Severe Thunderstorms
• Customization of mesoscale models for location
  specific (Kolkota, Gauhati, etc) deterministic
  mesoscale prediction.
• Improvement in Warning systems for aviation
  hazards, human activity and farming practices.

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Derivatives from STORM programme

• Collection of Data from Meso network, Data
  Processing and Mesoscale data assimilation
• Mesoscale models initial conditions sensitivity
  numerical experiments, customization of models
  and validation of results
• Data impact studies for future modernization of
  meteorological observations in India.
• Complimentary to the proposed CTCZ over the
  entire monsoon trough region in northern India
• Calibration and Validation of DWR products.
• Manpower Generation and Public Awareness.

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Pilot Experiment, 2006
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Pilot Experiment (20?N-27?N, 86?-90?E),
2006 Scale Environment of STORM Synoptic Scale
Environment and mesoscale
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Guwahati
Patna
Murshidabad
Asnsol
Ranchi
Kolkata
Digha
Bhubaneswar
Outer and Inner Meso-Net Quadrangles
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IOP DAYS during Pilot Experiment 2006
IOP Days Dates No. of days
1 14-15 April 2
2 25-26 April 2
3 4-7 May (two spells) 4
4 10-12 May 3
5 24-25 May 2
6 27-28 May 2
Total 15 days
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Network of 10 AWS for PFE - 2006
IMD
IAF
IMD
IAF
IIT
IAF
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Tracks of thunderstorms observed during
April-May, 2006
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Pilot Experiment, 2007
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Pilot Experiment 2007 (17?N-30?N, 84?-97?E
) Scale Environment of STORM Synoptic Scale
Environment and mesoscale
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Map depicting Outer and Inner Meso-Net
Quadrangles
North-Eastern Sector
Eastern Sector
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India Meteorological Department (IMD) Surface,
Upper Air and Radar Observatories STORM
Programme Domain
EASTERN SECTOR A. Surface Observatories
DEPARTMENTAL Alipore Diamond Harbour Digha Dum
Dum Haldia Malda Sriniketan Balasore Bhubaneswar B
hagalpur Gaya Patna Jamshedpur Ranchi Gangtok
Jharsuguda
RS/RW Stations Dum Dum Siliguri Patna Ranchi Bhuba
neswar Radar Stations Kolkata (Doppler Weather
Radar) Dum Dum Patna Ranchi Bhubaneswar Paradeep
PART TIME Canning Balurghat Berhampur Contai Krish
nanagar Midnapore Cuttack Keonjhargarh Chaibasa Ha
zaribagh
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II. NORTH-EASTERN SECTOR A. Surface Observatories
DEPARTMENTAL Guwahti Tezpur North
Lakhimpur Dibrugarh Imphal Cherrapunjee Passighat
Silchar Dhubri Lengpui Barapani Shillong Jorhat Na
harlagun Banderdewa Agartala Kailashahar
PART TIME Banderdewa Tangla Chaparmukh Aizawl Lumd
ing Deomali Rangia Kohima Goalpara B. Upper Air
Observatories PBO Observatories Guwahati
Dibrugarh Imphal Agartala
RS/RW Observatories Guwahati Dibrugarh
Agartala RADAR Observatory Guwahati
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Indian Air Force Surface and Upper Air (PBO)
Observatories over Eastern and North Eastern
Sectors
Kalaikunda Panagarh Barrackpore Purnea Bagdogra Hasimara Shillong Tezpur Jorhat Chabua Kumbhirgram
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List of installed locations of AWS in the NER as
on 24th February 2007
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IOP DAYS during Pilot Experiment 2007
IOP Days Dates No. of days
1 20-21 April 2
2 22-26 April (three spells) 5
3 30 April 1
4 3-4 May 2
5 7- 9 May (three spells) 3
4 11-13 May (two spells) 3
5 15-18 May (two spells) 4
6 22 May 1
7 26-28 May 3
Total 24 days
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Tracks of thunderstorms observed during
April-May, 2007
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Simulation of Severe Thunderstorm event (20 May
2006) during STORM 2006 over Calcutta using
WRF(NMM) Mesoscale Model
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Synoptic Situation

• A squall passed over Calcutta on 20th May at
  1633hrs from easterly direction. Max wind speed
  76 kmph lasted for 2 minutes.
• Few places recorded moderate rainfall over
  Gangetic West Bengal and isolated rainfall over
  Dum Dum (5cm) and Alipore (4cm)

Realized weather phenomenon over Calcutta on
20th May 2006
Date Wx. phenomenon Time Rainfall Rainfall Remarks
Date Wx. phenomenon Time Date Amount in mm Remarks
20-05-06 TS without Rain TS with rain Rain with no TS Squall 1550-1602 1602-1755 1755-1810 1633-1635 21-05-06 052.1 Rainfall reported next morning
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WRF-NMM MODEL EXPERIMENTS
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WRF-NMM model configuration used in this study
Model WRF-NMM of NCEP/ NOAA, Version 2.2
Dynamics Non-hydrostatic with terrain following hybrid pressure sigma vertical co-ordinate
Map projection Rotated lat-lon
Central point of the domain 22.5ºN / 88.0ºE
Horizontal grid distance 3 km (21.0ºS 24.0ºN, 86.3ºE 89.7ºE)
Number of vertical level 38 sigma levels
Horizontal grid scheme Arakawa E-grid
Time integration scheme Horizontal Forward-backward scheme Vertical Implicit scheme
Initial Lateral boundary condition FNL Analysis Forecast
Radiation scheme Long wave GFDL scheme Short wave GFDL scheme
Planetary boundary layer scheme Mellor-Yamada- Janjic
Surface layer Janjic similarity scheme
Land Surface NMM Land Surface scheme
Cumulus parameterization scheme Grell and Devenyi scheme
Microphysics Ferrier scheme
Topography 30 s elevation data (USGS)
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WRF (NMM) Model Domain
Domain 1 3 Km
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Comparison of Relative Humidity ()
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Hovmoller Diagram of Relative Humidity ()
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Relative Humidity () (09UTC - 14UTC)
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Comparison of Surface Pressure (hPa)
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Sea level pressure (hPa) (09UTC - 14UTC)
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Comparison of Temperature (deg C)
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Temperature (deg C) (09UTC-14UTC)
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Comparison of Surface Wind Speed (m/s)
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Wind Speed (m/s)
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Vector Wind
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Hovmoller Diagram of Pressure Vertical Velocity
(Pa/s)
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Moisture convergence at 850 hPa
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Comparison of Progressive Accumulated Rainfall
(mm)
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PrecipitableWater Content (Kg/m2) (09UTC -
14UTC)
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Skew-T plots of WRF-NMM
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Critical Values of Stability Indices

• Thunderstorms are likely to develop in regions
  where the stability indices are at critical levels

Stability Index Description Condition for Severe Weather
Lifted Index T500 Tparcel lt -3
K Index (T850 T500) DT850 - (T700 DT700)  gt 33
Total Totals (T850 TD850-2(T500) gt 44
CAPE gt 1500
CIN lt 50
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Comparison of Convective Available Potential
Energy (CAPE)
gt 1500
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Comparison of Convective Inhibition (CIN)
lt 50
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Comparison of K Index
gt 33
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Comparison of Total Totals Index
gt 44
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Comparison of Lifted Index
lt -3
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Future Challenges
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• Establishment of dense meso network of
  observations.
• Probing of thunderstorm using multi-
  observational platforms such as satellites,
  aircrafts, mobile doppler weather radars,
  radiosondes, dropsondes, wind profilers and AWS.
• Comprehensive mesoscale data assimilation
  utilizing conventional and non-conventional
  observations from multi-observation platforms.

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• Prediction of life cycle of thunderstorm along
  with associated hazards using very high
  resolution ( 1-3 km) state-of-the-art mesoscale
  models.
• Role of physical processes in particular deep
  convection, cloud microphysics, planetary
  boundary layer, land surface processes with high
  resolution meso-scale model and special field
  experiment datasets.
• Observation and understanding of cloud
  microphysics, aerosol concentration and
  atmospheric electricity in association with
  severe thunderstorm.

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THANK YOU