Jonathan J. Gourley

Jonathan J. Gourley
National Weather Center
University of Oklahoma
Norman, OK, USA
Contemporary observations and forecasts of
flash floods in the United States
Flash Flood
Research Team
Prof. Yang
Hong
Quantifying
Flash flood
moisture sources dam impacts
Probabilistic
QPE
Coupling to
landslide
prediction
model
Streamflow
error
modeling
Ensemble
forecasting
FLOCAST
observations
from experts
Societal
impacts
Probabilistic
flash flood
forecasting
using NWP
Collection and
use of flood
photo catalogue
Conditions
favorable
for flash
flooding
Human
factors in
product
interpretation
mPING and
flash flood
modeling
Hydrologic
modeling in
complex terrain
Motivation
Skill (CSI) of FFG
1 Oct 2006 – 31 Aug 2010
Verification: NWS Storm Data reports
Clark, R. A., J. J. Gourley, Z. L. Flamig, Y. Hong, and E. Clark, 2014: CONUS-wide evaluation of National
Weather Service flash flood guidance products, Wea. Forecasting, 29, 377-392.
Multi-Radar Multi-Sensor QPE (MRMS)
Flooded Locations And Simulated Hydrographs (FLASH)
- An NWS CONUS-wide flash-flood forecasting system
MRMS/Q3 Rainfall
Observations
-1km2/2 min
Stormscale Distributed
Hydrologic Model Ensemble
-1km2/10 min
Probabilistic Forecast
Products on the Flash
Flood Impacts
Type of flash flood impact
according to SHAVE database
Simulated surface water
flows and return period
150
200
250 mm
40%
60%
80%
t=0100
t=0000
20
fatalities
10-11 June 2010, Albert Pike Rec
Area, Arkansas
t=2300
Probability of life-threatening
flash flood
MRMS-FLASH: Real-time, direct simulation of flash floods a reality
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1-km2/2-min resolution of MRMS precipitation forcing and
products
Distributed modeling approach (threshold exceedance) is more
skillful than traditional FFG used in operations
Project will readily incorporate dual-pol radar products and
stormscale ensemble precipitation forecasts (warn-on-forecast)
Outputs will be probabilistic and targeted on anticipated impacts
Photo source: National Geographic
FLASH MODELING SYSTEM
Two cores currently available in FLASH
Atmospheric
Atmospheric Forcing
Forcing
RainFact
RainFact
RS0
RS0
Stream
Variable Infiltration Curve
RI0
RI0
RR
Ksat
Surface
flow
AET
AET
RS
RS
Cell-To-Cell Surface
Runoff Routing
Soil Layer
Interflow
CREST
RI
RI
Cell-To-Cell Interflow
Runoff Routing
SAC-SMA
Parameters from Basin Properties
KSat
51 mm/h
0.01 mm/h
Kinematic
Wave
Routing
31 May 2013 21z – 1 Jun 2013 12z loop (5 min increments)
of WSR-88D composite reflectivity
Archived mosaicked WSR 88-D composite reflectivity (UN qc’ed) from NSSL MRMS server
> 250 mm
31 May 2013 Oklahoma City Flash
Flood - deadliest event in city history
NWS Operational Flash Flood Guidance
FLASH distributed hydrologic model forecast
FLASH forecasts were able capture the flood more
accurately due to 1) downstream channel routing and
2) low infiltration rates parameterized for urban zones
Body
recovered
Body
recovered
Man killed by
floodwaters
7 people sheltered here; all died
Multiple bodies recovered
in Oklahoma River
11 people sheltered here; 5 died
During the storms, 23 people lost their lives (13 from flooding in OKC).
This is the deadliest flood in OKC history & the worst in the state since 1984
Reports from Twitter, Facebook, KFOR-TV, KOCO-TV, News9, and The Oklahoman; Photos from The Oklahoman
STUDY BASINS
Proof of concept study: 9 Basins
• 18 stream gauges from US flash
flood observation database*
Period of Study: Oct. 2002 – Sep 2011
Total of 189 events
Event was defined by
Observed Q > NWS action stage
*Gourley, J. J., Y. Hong, Z. L. Flamig, A. Arthur, R. A. Clark, M. Calianno, I. Ruin, T. Ortel, M. E. Wieczorek, E. Clark, P.-E. Kirstetter,
and W. F. Krajewski, 2013: A unified flash flood database across the United States, Bull. Amer. Meteor. Soc., 94, 799-805.
FLASH’s PEAK FLOW MODELING
SKILL
Rank Correlation = 0.69
Rank Correlation = 0.65
ONGOING WORK
Uncertainty characterization of hydrologic modeling system
• Identify hydroclimatological, physiographic, & geomorphologic factors
that drive the peak/timing errors
• Derive error models and transfer to ungauged grid points
Error model relating simulated
to observed flooding
“Flash floods are not
only hard to predict,
they are difficult to
observe.”
- anonymous
“Crowdsourcing” with Meteorological
Phenomena Indication Near the Ground
(mPING)
 ~50k
downloads
 ~500k
reports
submitted
since Dec.
2012
 Includes all
standard
reports of
weather
 Going global
!!!
Expert Witness Reports
• Target emergency management community
– First responders, EMs, trained spotters, NWS
– Recruitment for victim interviews
• Detailed survey about FF occurrence
– Location, time, depth, extent, impacts, etc.
– Description of event
– Option to provide a photograph
• Based on Gourley et al. (2010)*
– Previous FF verification during the SHAVE Project
– Similar questions utilized
• Web based questionnaire
– Collect data with 24 hours after event
Gourley, J. J., J. M. Erlingis, T. M. Smith, K. L. Ortega, and Y. Hong, 2010: Remote collection and analysis of witness
reports on flash floods. J. Hydrol., 394, 53-62.
Web-Based Questionnaire
Expert Witness Reports – Photos & Data
The Good
The Bad
The Ugly
Role of vehicles
Importance of routing in West
Contemporary approaches to flash
flood forecasting
Associate classified photographs to model forecasts of flash flooding and GIS
exposure factors; in forecast mode, search photo analogue database to find most
likely impact type/magnitude
Hazard Grid from FLASH distributed
hydrologic modelling system
Exposure Grid from GIS (pop
density, roads, land use, etc.)
Photograph showing
anticipated impact type
and magnitude
Photo credit: Don Becker, U. S.
Geological Survey
Summary
• FLASH provides a framework for model
development and forecasting in ungauged basins
• Key features of the system
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Resolution at flash flood scale
Scalability up to mainstem river flooding
Consistency across the CONUS, eventually global
Ensemble capability (QPE + model physics) through
parallelization on 16-core server
Future forcing using 0-6 hr precipitation forecasts
Probabilistic products focused on societal impacts
(urban street flooding vs. cropland flooding)
uestions?
[email protected]
or access to US flash flood observations database and realtime forecast products: http://blog.nssl.noaa.gov/flash/

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