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Andrea Schumacher, CIRA/CSU Mark DeMaria, NOAA/NESDIS/StAR Dan Brown and Ed Rappaport, NHC.

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Presentation on theme: "Andrea Schumacher, CIRA/CSU Mark DeMaria, NOAA/NESDIS/StAR Dan Brown and Ed Rappaport, NHC."— Presentation transcript:

1 Andrea Schumacher, CIRA/CSU Mark DeMaria, NOAA/NESDIS/StAR Dan Brown and Ed Rappaport, NHC

2  Generally accepted that improvements to hurricane forecasts will benefit society  Longer lead times  more time to prepare  Better track forecasts  reduce areas warned and/or evacuated unnecessarily  However, quantifying these benefits a difficult task  How much money will a better forecast save?  How many lives could be saved? 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009

3  Use wind speed probability model to…  Develop an objective warning scheme that reasonably simulates official NHC warnings (building off previous work by M. Mainelli and M. DeMaria)  Artificially “improve” input forecasts, use warning scheme to diagnose changes in warning properties  Warning properties considered here  Coastal distance  Duration --> time until warning is dropped 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009

4  Operational at NHC since 2006 (replaced Strike Probability Program)  Methodology  Samples errors from NHC track and intensity forecasts over last 5 years to generate 1,000 forecast realizations  Wind radii of realizations from radii CLIPER model  Calculates probabilities over domain from realizations  Versions for Atlantic, NE and NW Pacific  Current products  Cumulative and incremental probabilities  34, 50 and 64 kt winds  0, 12, …, 120 hr  Text and graphical products  Distributed via NHC web page, NDFD, AWIPS 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009

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6  Rerun MC probability model  Used 64-kt (hurricane force) wind probabilties  Used 36-h cumulative probabilities (best match for NHC hurricane warning criteria)  U.S. mainland hurricane warnings from (20 tropical cyclones)  343 breakpoints  Choose wind speed probability thresholds  p > p up –> put warning up  p take warning down 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009

7 First Guess (Prelim w/ Ivan) : p up = 10.0%, p down = 2.0% Best fit: p up = 8.0%, p down = 0.0% 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009 MCPNHC Average Distance Warned (mi) Average Warning Duration (hr) MCP Objective vs. NHC MAE, Distance (mi)65 MAE, Duration (hr)5 R 2, Distance0.94 R 2, Duration0.74

8 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009 NHC Hurricane Warnings Objective Scheme Hurr Warnings

9 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009

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11  Two steps needed  Use best tracks from ATCF to adjust tracks and intensities closer to observed values  Scale the sampled track (intensity) errors in the Monte Carlo scheme  For this study, 20% and 50% error reductions were used  Apply objective hurricane warning scheme to MC wind speed probabilities based on “improved” forecasts 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009

12 Average = mi Average = 33.6 hr We’re closer.. Developed relationship between forecast improvements and warning length & duration… but what are these worth to society?

13 63rd Interdepartmental Hurricane Conference, 2-5 Mar % Track and Intensity Forecast Improvement 50% Track and Intensity Forecast Improvement Warning Reductions Length (blue) ~50mi Duration ~ 7 h Warning Reductions Length (blue) ~ 100mi Duration ~ 6 h

14  An objective hurricane warning scheme was developed  Scheme issues hurricane warnings when p>8% and lowers warnings when p=0%  Scheme simulates official NHC hurricane warnings from relatively well  20% (50%) forecast improvement in both track & intensity yields  29 mi or 5% (91 mile or 13%) reduction in coastal length of warning  2 hr or 8% (5 hr or 24%) reduction in warning duration (i.e., dropped earlier) 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009

15  Integrate social science research  Previous social science work focused on evacuation behavior, but there are connections (e.g., links between warnings, risk perception, and evacuation behavior)  $600,000 - $1 million per mile estimate for cost of evacuation ▪Too generic, doesn’t account for population density differences ▪Whitehead 2003 suggests might actually be less  Some emergency management guidance products estimate costs of evacuation decisions ▪Emergency Management Decision Support System (EMDSS, Lindell and Prater 2007) 63rd Interdepartmental Hurricane Conference, 2-5 Mar 2009

16  DeMaria, M., J. A. Knaff, R. Knabb, C. Lauer, C. R. Sampson, R. T. DeMaria, 2009: A New Method for Estimating Tropical Cyclone Wind Speed Probabilities. Wea. Forecasting, Submitted.  Jarell, J.D. and M. DeMaria, An Examination of Strategies to Reduce the Size of Hurricane Warning Areas. 23 rd Conference on Hurricanes and Tropical Meteorology, Dallas, TX, Janurary  Lindell, M.K. and C.S. Prater, 2007: A hurricane evacuation management decision support system (EMDSS). Natural Hazards, 40,  Whitehead, J.C., 2003: One million dollars per mile? The opportunity costs of Hurricane evacuation. Ocean and Coastal Management, 46, rd Interdepartmental Hurricane Conference, 2-5 Mar 2009


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