Exploring the Use of Dynamical Weather and Climate Models for Risk Assessment
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1 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
2 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.
3 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.
4 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.
5 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).
6 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.
7 Global Distribution of WRF Users 6500 users in 95 countries. Real-time forecasting at: 7 domestic 22 international
8 Phase I Investigate simulations of tropical systems for the present climate Configured to a tropical channel domain ±45 latitude km 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.
9 Outgoing Longwave Radiation
10 Tropical Cyclone Numbers # TC / year Observation NRCM Asuka Suzuki NRCM overproduced TCs SST setting? Model physics? Parameterization?
11 Global Distribution of Tropical Cyclone Genesis Asuka Suzuki
12 Atlantic Variability 30 North Atlantic annual variability NRCM Observation #TC/year
13 Atlantic Nest: Aug 2005
14 36km domain 18 storms 12km Nest 29 storms 28 storms observed Asuka Suzuki
15 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
16 Model Setup 4km 12km Jet 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 ( , , , ) or 3 10 years ( , , )
17 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.
18 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
19 Example: Katrina 2005 Day of August 2005 Day of August 2005
20 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.
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