2006 01 18 THORPEX

Site-Specific and Event-Specific Critical Weather Forecasting: A Global to Local Problem : 

Site-Specific and Event-Specific Critical Weather Forecasting: A Global to Local Problem David P. Bacon Nash’At N. Ahmad, Thomas J. Dunn, Mary S. Hall, and Ananthakrishna Sarma Center for Atmospheric Physics Science Applications International Corporation January 18, 2006 David P. Bacon (703)676-4594 david.p.bacon@saic.com This work is supported in part by the NOAA THORPEX program

THORPEX:Pushing Back the Limits of Predictability: 

THORPEX: Pushing Back the Limits of Predictability To accomplish this goal, we need a change in the operational paradigm Probabilistic forecasts – Circumvent the unknown by trying to quantify the bounds of the possible Increased physics – Gain greater understanding of those fixed features that impact on the weather Orography Coastal boundaries Vegetation & land-use Surface properties

OMEGA: 

OMEGA The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is a atmospheric simulation system designed around an adaptive unstructured grid Originally intended to forecast the dispersion of hazardous materials in the boundary layer, OMEGA emphasizes surface and boundary layer physics OMEGA has now been extended to a global-to-local simulation and forecast system with the unique ability to dynamically adjust its grid resolution to place high resolution preferentially over areas determined by the evolving weather (or other hazard)

Static Grid Adaptation: 

Static Grid Adaptation The OMEGA grid will automatically adapt to: Complex terrain Land/Water boundaries Any specified 2-D field Specified regions Rectangular Circular

Generation of Global OMEGA Grids: 

Generation of Global OMEGA Grids Global / Local resolution: ~ 100 / 10 km

An Example of Static Adaptation: 

An Example of Static Adaptation

Adaptivity Criteria: 

Adaptivity Criteria Static Terrain slope Land-water boundaries Dynamic Pressure minima + windspeed minima Pressure gradient Integrated column water Potential temperature gradient

Hurricane Georges (1998): 

Hurricane Georges (1998) Dynamic grid adaptation 20-80 km resolution Initialized from NOGAPS 0000Z September 24, 1998 SST from September 17

THORPEX Question #1:What is the potential improvement in a global model produced by the introduction of high resolution orography / coastal boundaries: 

THORPEX Question #1: What is the potential improvement in a global model produced by the introduction of high resolution orography / coastal boundaries Explore the benefit to 7-day precipitation forecasts of including – at variable resolution – full terrain elevation and coastal boundary information Explore the impact of high resolution land coverage information

Orographic Snowstorm: 

Orographic Snowstorm Center Location Observed Simulated H1 44.36N, 103.75W 24.41 25.3 H2 44.25N, 104.10W 13.97 20.1 H3 44.50N, 104.50W 14.78 12.5 Center Location Observed Simulated H4 44.00N, 103.80W 11.00 12.2 H5 43.80N, 103.30W 22.70 9.9 H6 43.50N, 104.00W 10.97 13.5 H1 H2 H3 H4 H6

Rainfall Prediction: 

Rainfall Prediction Courtesy of Dr. Sethu Raman, State Climatologist of North Carolina Observed Predicted

Accurate Surface Information is Essential: 

Accurate Surface Information is Essential Surface information (boundary conditions) is as important to accurate forecasting as atmospheric information (initial conditions)

Tokyo Heat Wave – Uniform Global Grid: 

Tokyo Heat Wave – Uniform Global Grid

Tokyo Heat Wave – Local Grid Resolution: 

Tokyo Heat Wave – Local Grid Resolution

Tokyo Heat Wave – Uniform Grid Results: 

Tokyo Heat Wave – Uniform Grid Results

Tokyo Heat Wave –Global Static Adaptive Grid: 

Tokyo Heat Wave –Global Static Adaptive Grid

Tokyo Heat Wave – Local Adaptive Grid Resolution: 

Tokyo Heat Wave – Local Adaptive Grid Resolution

Tokyo Heat Wave – Adaptive Grid Results: 

Tokyo Heat Wave – Adaptive Grid Results

Why Adaptive Grids?: 

Why Adaptive Grids? This scenario has four (4) primary drivers: Warm air advection from Asia Dependent on position, strength, and persistence of the large-scale sub-tropical high Resolvable by climate and regional climate models Adiabatic warming of subsiding air Both synoptic and downslope Downslope depends on accurate terrain representation Partially resolvable by CM / RCM Surface heating Supra-urban and urban Partially resolvable by CM / RCM SST and sea-breeze Dependent on accurate terrain / surface representation Not resolvable by CM / RCM

THORPEX Question #2:What is the potential improvement in the forecast skillof a global model produced by dynamic adaptation: 

THORPEX Question #2: What is the potential improvement in the forecast skill of a global model produced by dynamic adaptation Explore the benefit to 7-14-day forecasts of permitting dynamic adaptation to evolving weather systems (over the forecast area and elsewhere)

Severe Precipitation Event: LA / 17-23 FEB 2005: 

Severe Precipitation Event: LA / 17-23 FEB 2005

24 Hour Integrated Precipitation: 

24 Hour Integrated Precipitation

Global Uniform Grid: 

Global Uniform Grid

Global Static Adaptive Grid: 

Global Static Adaptive Grid

Global Static Adaptive Grid w/ Local Refinement: 

Global Static Adaptive Grid w/ Local Refinement

Global Static & Dynamic Adaptive Gridw/ Local Refinement: 

Global Static & Dynamic Adaptive Grid w/ Local Refinement

Global Static & Dynamic Adaptive Gridw/ Local Refinement: Elevation: 

Global Static & Dynamic Adaptive Grid w/ Local Refinement: Elevation

Static Uniform Grid:500mb Analysis & 96hr Forecast: 

Static Uniform Grid: 500mb Analysis & 96hr Forecast

Static Adaptive Grid:500mb Analysis & 96hr Forecast: 

Static Adaptive Grid: 500mb Analysis & 96hr Forecast

Static Uniform Grid:850mb Analysis & 96hr Forecast: 

Static Uniform Grid: 850mb Analysis & 96hr Forecast

Static Adaptive Grid:850mb Analysis & 96hr Forecast: 

Static Adaptive Grid: 850mb Analysis & 96hr Forecast

Uniform Grid Precipitation Forecast: 

Uniform Grid Precipitation Forecast

Static Adaptive Grid Precipitation Forecast: 

Static Adaptive Grid Precipitation Forecast

Static Adaptive (w/ Refinement) Grid Precipitation Forecast: 

Static Adaptive (w/ Refinement) Grid Precipitation Forecast

Dynamic Adaptive (w/ Refinement) Grid Precipitation Forecast: 

Dynamic Adaptive (w/ Refinement) Grid Precipitation Forecast

High Impact Weather Forecasts:Linking Models and GeoSpatial Data: 

High Impact Weather Forecasts: Linking Models and GeoSpatial Data Which has more value: A. Forecast of precipitation for a city (e.g. 1-3 inches) B. GeoReferenced contours of precipitation over a population density data layer With additional flooding tools With additional landslide tools …

Penang – Flooding / Roadblocks: 

Penang – Flooding / Roadblocks

Penang – Roadblock Report: 

Penang – Roadblock Report

Penang – Consequences / # People: 

Penang – Consequences / # People

Closing Remarks: 

Closing Remarks To move from 3-5 day forecasts with skill to 14 days will require a change in the operational paradigm Probabilistic / Ensemble techniques Increased resolution / physics of fixed features via adaptive grids Probabilistic / Ensemble techniques using adaptive grids While current adaptation routines are physics-based, there is no prohibition to including socio-economic-based criteria Such optimization is essential to meeting the THORPEX goal of improving high impact weather forecasts A secondary factor in improving high-impact weather is to improve the linkage between meteorological information and other geo-spatial data of importance to disaster planning, response, and recovery.

For Further Information: 

For Further Information Contact: Dr. David Bacon Center for Atmospheric Physics Science Applications International Corporation 1710 SAIC Dr. McLean, VA 22102 (703)676-4594 (703)676-5509 (FAX) david.p.bacon@saic.com or Visit the OMEGA Web site: http://vortex.atgteam.com This work is supported in part by the NOAA THORPEX program