Allen, Roger E.

Bell, Jordan R.

Case, Jonathan L.

Cecil, Daniel J.

Gatlin, Patrick N.

Knickerbocker, Jeffrey

Meyer, Paul J.

Petersen, Walter A.

Srikishen, Jayanthi

NASA Technical Reports Server

Day-1
Prob Wind
> 40 kt
Day-1
Prob Wind
> 30 kt
Day-1 Prob of
any Ltg
Day-1 Prob of
“frequent” Ltg
Composite 
Reflectivity
Probability
Matched Mean:
41-hour 
forecast
valid 1100 UTC
17 April 2018, 
suggesting 
discrete
[supercell] 
structure
Prob Wind
> 40 kt
Prob graupel
> 30 kg/m2
(hail proxy)
Forecasting and Monitoring Intense Thunderstorms in the Hindu-Kush Himalayan Region:
Preliminary Results from Spring 2018 Demonstration (P2-14)
Jonathan L. Case1, Patrick N. Gatlin2, Jayanthi Srikishen3, Jeffrey Knickerbocker4, Jordan R. Bell*5, Roger E. Allen6, Paul J. Meyer2, Daniel J. Cecil2, and Walter A. Petersen2
1 ENSCO, Inc., Huntsville, AL   2NASA/Marshall Space Flight Center, 3Universities Space Research Association, 4Spatial Informatics Group, 5University of Alabama  Huntsville, 6Jacobs ESSCA Group
Introduction
o Some of the most intense thunderstorms on Earth plague 
the Hindu-Kush Himalayan (HKH) region of south-central 
Asia, esp. during the pre-monsoon months of March 
through May (see Figure below).
o All thunderstorm hazards are common, including large hail, 
tornadoes, damaging straight-line winds, deadly lightning, 
dust storms, and flash flooding.
o This NASA/SERVIR Applied Sciences Team project seeks to 
use modeling and remote-sending assets to build early 
warning capabilities and facilitate timely disaster response 
for high-impact weather events in the HKH region.
Overarching Project Objectives Methodology and Datasets
o Daily, real-time 12-member NWP ensemble; pre-monsoon months of March-May 2018
 Convection-allowing ensemble system with sufficient spread in solution; 18z daily initializations
• Weather Research and Forecasting (WRF) model within Unified Environmental Modeling System (UEMS)
• 12-km outer grid/4-km nested grid; all analysis done on 4-km nest (see domain figure below)
• 12 different initial/boundary conditions from NCEP/EMC’s GFS and GEFS operational models
• Physics variability using 3 planetary boundary layer and 4 microphysics schemes (see table below)
 48-hour forecasts with hourly output, displayed on internal project web page for real-time and archive
 Cluster: SERVIR Operational Cluster Resource for Applications - Terabytes for Earth Science [SOCRATES]
• Using “head” node and 12 virtual Linux nodes, each with 32 processors and 128 GB RAM
• Each node runs a single ensemble member; post-processing / product generation on head node
o Proxy model fields to represent convective hazards (Kain et al. 2008, 2010)
 Convective Intensity: Composite reflectivity
 Lightning: Lightning Forecast Algorithm (LFA; McCaul et al. 2009)
 Straight-Line Winds: Maximum output interval 10-m wind speed
 Hail Threat: Maximum output interval total column graupel
 Mesocyclone/tornado: Maximum output interval updraft helicity
 Flooding rainfall: Accumulated precipitation thresholds (esp. 3-hourly)
o Develop High-Impact Weather Assessment Toolkit 
(HIWAT) for the HKH region.
o Jointly develop HIWAT capabilities and training with 
the International Centre for Integrated Mountain 
Development (ICIMOD), the NASA/SERVIR hub 
based out of Kathmandu, Nepal.
o Demonstrate capability in end-user environment 
(i.e., “Tethys” web mapping interactive service).
o Transition HIWAT to ICIMOD for future execution 
and maintenance.
Output NWP Ensemble Products
o Summarize 12-member ensemble system into meaningful fields for intense 
thunderstorm forecast guidance (largely following Schwartz et al. 2015)
 Postage stamp plots: Thumbnail view of all ensemble members each hour
 Ensemble statistics: Mean, Minimum, Maximum, Spread/standard dev.
 Paintball plots: Threshold applied to various fields and then color-coded by ensemble 
member with varying transparency
 Probability products: Probability of exceeding thresholds (as in paintball plots)
 Daily summaries: Summarizes first and second 24-h forecast periods for a quick look 
into Day-1 and Day-2 thunderstorm hazards and overall spatial coverage
o Probability products
 Grid point probability: 𝑃𝑟𝑜𝑏𝑖𝑗 % = 100 ×
𝐻𝑖𝑡𝑠
𝑛
; where n = # of ens. members
 Neighborhood probability: Search for “hits” within neighborhood window, then 
compute probability using formulation above; apply Gaussian smoother
 Probability Matched Mean (PMM): Replace ensemble mean values with those 
sampled from distribution of all ensemble members (Ebert 2001; Clark 2017)
Preliminary Storm Reports and Casualties
o Sourced from regional news/media outlets; Mar-May 2018
o Not necessarily an exhaustive list
 17 lightning events with fatalities
 16 damaging wind events and 7 damaging hail events
 Over 200 fatalities estimated
Event Location Lightning Wind Hail
29-Mar-18
Bhutan X
NE India X X
30-Mar-18
Bangladesh X X X
Nepal X
N India X
NE India X X
11-Apr-18 NW India X X
17-Apr-18 N. India X X
21-Apr-18 NE India X
22-Apr-18 Bangladesh X X
29-Apr-18
Bangladesh X
N. India X
30-Apr-18 Bangladesh X X
2-May-18 N. India X X
6-May-18
Bangladesh X
NE India X X
7-May-18 NE India X
9-May-18
Bangladesh X
NE India X X
10-May-18
Bangladesh X X
NE India X
11-May-18
Bangladesh X X X
NE India X X
13-May-18 N. India X X
15-May-18 Bangladesh X
1 2 3 4
5 6 7 8
9 10 11 12
Combined into probabilistic-based forecast guidance (e.g., severe hail)
Day-1 Probability of Large Hail
Ensemble Forecast Concept Design
From: 
Cecil and Blankenship (2012)
REGIONAL NWP MODEL HIGH-IMPACT WEATHER ENSEMBLE PROGNOSTICS
Short-term forecasting / situational awareness
GPM SATELLITE OBSERVATIONS
Threat Assessment
SATELLITE LAND IMAGERY
Impact Assessment
Hailstorm badly damaged hybrid 
bitter gourd seedbeds in Bangladesh
Source: thedailystar.net
HIWAT Components
MP 
PBL 
Goddard 
3-ice with 
graupel
Lin 
6-class
WSM6 
6-class
Morrison
double
moment
Yonsei State 
University (YSU)
HKH1:
GFS
HKH2:
GEFS 03
HKH3:
GEFS 05
HKH4:
GEFS 07
Mellor-Yamada 
Janjic (MYJ)
HKH5:
GEFS 09
HKH6:
GEFS 11
HKH7:
GEFS 13
HKH8:
GEFS 15
Mellor-Yamada 
Nakanishi and 
Niino (MYNN2)
HKH9:
GEFS 17
HKH10:
GEFS 19
HKH11:
GEFS 02
HKH12:
GEFS 0412 km
4 km
12-km/4-km nested domain for
convection-permitting ensemble.
12-member ensemble system with variations of initial/boundary 
conditions and WRF PBL (rows) and microphysics (columns) schemes.
Ongoing and Future Efforts
o Continuing HIWAT ensemble simulations through 2018 wet monsoon
o Transitioning products into NASA/SERVIR Tethys Application
 Interactive web mapping service capable of layering HIWAT probability maps 
over other geo-navigated datasets.
 Data sampling and interactive time series plots generated on the fly for select 
points and/or user-outlined polygons (see sample images below).
o Conduct verification of individual ensemble member precipitation and 
PMM, against GPM/IMERG-Final precipitation rates
o Verification of LFA total lightning flash rates using Earth Networks Total 
Lightning Network as ground truth.
Chance of 
Intense Storms
HIWAT Thunderstorm Hazards Forecasts:
30 March 2018
Chance of 
Damaging 
Winds
Chance of 
Frequent 
Lightning
Chance of
Hail
Point-based forecasts Severe weather reports 
(30 March 2018)
Sample Ensemble Forecast Plots for Select Events
Preliminary Impact Assessment with Satellite Imagery
o Passive and active remote sensing was 
preliminarily evaluated to detect [hail] damage 
from intense thunderstorms in the HKH region.
oDue to small heterogeneous agricultural areas 
in the HKH region, it was difficult to identify 
damaged areas using analysis techniques that 
are successful in the U.S.
oWe will thus re-direct focus to remote-sensing 
methods and identification techniques to map 
flooding and inundation areas from intense 
thunderstorms and annual monsoon rains. 
o These techniques and methods will be 
transferred to end-users and stakeholders 
during the final year of the project.
(above) 8 June 2018 Sentinel-1 False 
color SAR RGB image denotes areas of 
water [blue] in central Bangladesh.
30 Mar Large Hail & Wind; E. Nepal / Bangladesh 17 Apr Supercells / Damaging Wind in Kolkata
Day-2 
Probability
of Wind > 40 kt,
suggesting high
potential for 
strong 
convective
wind speeds
22 Apr Deadly Ltg / High Wind in central Bangl.
E. Nepal / N. Bangl.
Central Bangl.
10z 17 Apr 12z 17 Apr
05z 30 Mar
07z 30 Mar
09z 30 Mar
09z 22 Apr 10z 22 Apr
11z 22 Apr 12z 22 Apr
Acknowledgements: This research is funded by NASA’s Applied Sciences Capacity
Building Program Manager, Dr. Nancy Searby. We would like to thank Dr. Bhupesh
Adhikary and the International Centre for Integrated Mountain Development (in
Kathmandu, Nepal) for their assistance and involvement with this project.
https://ntrs.nasa.gov/search.jsp?R=20180006666 2019-08-31T18:57:41+00:00Z


Forecasting and Monitoring Intense Thunderstorms in the Hindu Kush Himalayan Region: Preliminary Results from Spring 2018 Demonstration (P2-14)

Forecasting and Monitoring Intense Thunderstorms in the Hindu Kush Himalayan Region: Preliminary Results from Spring 2018 Demonstration (P2-14)

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