PDF File

Exploring the Use of Dynamical
Weather and Climate Models for
Risk Assessment
James Done
Willis Research Network Fellow
National Center for Atmospheric Research
Boulder CO, US
• Leverages resources in the academic community to
complement existing methods in catastrophe modeling.
• Provides decision makers with an improved
understanding of quantitative risk data
• Funds post-doctoral researchers to focus on industryrelated issues
• Siesmic, climate/hurricanes, flood/hydrological. GIS and
Statistical methods.
• Expected outcomes: model development, peer-reviewed
publications, industry briefings and seminars.
Using Dynamical Models for Risk Assessment
• Industry is increasingly reliant on quantitative risk data for cat models.
• Traditionally, risk has been estimated by sampling from probability
distributions fitted to historical data.
• Problems:
- stationary statistics,
- historical data issues.
• Explore a combined approach using both statistical and dynamical
methods in obtaining a more accurate estimate of risk.
Using Dynamical Models for Risk Assessment
• Global Climate Models (GCMs) provide a complete time and space view of
the climate system;
- full view of each hazard
- correlations between hazards in time and space
• Used to simulate past and present climates and provide projections of
possible future climates.
• High computational expense currently limits their spatial resolution to over
100km.
• What can GCMs tell us about high impact weather?
• How can we obtain detailed hazard information from GCMs?
One approach - embed ‘weather’ models inside GCMs
over regions of interest.
The Nested Regional Climate Model
• Downscaling climate variability and climate change to
the regional scale (water resources, tropical cyclones,
warm-season rainfall etc).
• Upscaling of regional phenomena with global impacts
(eastern boundary upwelling regimes, mesoscale
convection etc).
The Weather Research and
Forecasting Model
NRCM derived from the WRF model
• Maintained by NCAR as a Community Model for past 10 years.
• Research and Operational Model
• Fully compressible nonhydrostatic equations
• Conserves mass and total water
• Plug-in Physics to suit application/spatial scale
• Can represent all scales of motion:
– 50m Large-eddy simulations (e.g atmospheric boundarylayer) to 100s kms global modeling.
http://www.wrf-model.org
Global Distribution of WRF Users
6500 users in
95 countries.
Real-time
forecasting at:
7 domestic
22 international
Phase I
Investigate simulations of tropical systems for the present climate
Configured to a tropical channel domain ±45° latitude.
12
4 12
4
• 36km grid: 10 years of simulation
• 12km 2-way Atlantic nest: May-Dec 2005
Forcing data:
• NCEP/NCAR Reanalyses (Northern and Southern boundaries)
• AMIP SSTs 0.5°lat/lon. Monthly.
Outgoing Longwave Radiation
Observation
20
05
20
04
20
03
20
02
20
01
20
00
20
00
19
99
19
98
19
97
160
140
120
100
80
60
40
20
0
19
96
# TC / year
Tropical Cyclone Numbers
NRCM
Asuka Suzuki
• NRCM overproduced TCs
– SST setting? Model physics? Parameterization?
Global Distribution of Tropical Cyclone Genesis
Asuka Suzuki
Atlantic Variability
North Atlantic annual variability
30
20
15
10
5
0
19
96
19
97
19
98
19
99
20
00
20
00
20
01
20
02
20
03
20
04
20
05
#TC/year
25
NRCM
Observation
Atlantic Nest: Aug 2005
36km domain
18 storms
12km Nest
29 storms
28 storms observed
Asuka Suzuki
NRCM plans for 2008:
To explore the potential impacts of climate change on
North Atlantic tropical cyclone activity
• Dynamically downscale current and future climate from NCAR Community
Climate System Model (CCSM3) archived simulations undertaken for IPCC.
• CCSM is a coupled climate system model:
- atmosphere, ocean, land surface and sea-ice.
- future projections of atmosphere and ocean states under global warming.
• Examine how frequency and intensity of TCs are likely to change over the
next 50 years.
• Water resource variations over the Western US
Model Setup
4km
Jet
12km
36km
• CCSM T85 (~150km ∆x) lateral and lower boundary conditions
• Time-slice ensemble experiments.
- five ensemble members differ in their climate change scenario.
- either 4 × 5 years (1998-2002, 2018-2022, 2038-2042, 2058-2062)
or 3 ×10 years (1995-2005, 2020-2030, 2045-2055)
Extensions
• Conduct sets of high-resolution (~1km) vortex-tracking nests for specific
hurricanes in both current and future climate.
- assess likely inaccuracies of larger dataset
- specify climatology of most intense hurricanes.
• Explore other/complimentary approaches to downscaling the Global
Model data.
Estimating Hazard Footprint of Landfalling Cyclones
by Resolving Inner-Core Dynamics at 1km Grid Spacing
WRF model domain:
Fixed 12km domain
• 5-day forecasts
• Simple mixed-layer
ocean model
Vortex following, 2-way
4km and 1.33km nests
χ
• Experimentation with 3D-VAR and Ensemble Kalman Filter
data assimilation techniques.
NCAR
Example:
Katrina 2005
Day of August 2005
Day of August 2005
Example: Hurricane Dean Making Landfall
Model wind speed (ms-1) at ~70m above surface
WRF Model
• Distorted eyewall
• Flow into eye
• Wind speed ‘jets’ over land associated with roll vortices
• Jet wind speeds approach pre-landfall values.