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Probabilistic Forecasts of Extreme Precipitation Events for the U.S. Hazards Assessment Kenneth Pelman 32 nd Climate Diagnostics Workshop Tallahassee,

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Presentation on theme: "Probabilistic Forecasts of Extreme Precipitation Events for the U.S. Hazards Assessment Kenneth Pelman 32 nd Climate Diagnostics Workshop Tallahassee,"— Presentation transcript:

1 Probabilistic Forecasts of Extreme Precipitation Events for the U.S. Hazards Assessment Kenneth Pelman 32 nd Climate Diagnostics Workshop Tallahassee, Florida

2 Outline Current Hazards Assessment Motivation for Probabilistic Forecast Details of Objective Probabilistic Tool Verification Results Conclusions Future Work

3 Current CPC Hazards Assessment Made each Monday-Friday and covers Days 3-14 Designed to take current state of climate and predict hazardous weather conditions in support of CPC’s mission Hazards include heavy rain (a proxy for flooding), severe weather, extreme heat and cold, and severe drought Hazard forecasts are subjective and deterministic

4 Motivation for a Probabilistic Hazards Assessment Looking to improve on subjective scores Probabilistic forecasts provide more information about uncertainty to users Puts Hazards Assessment in same format as other popular CPC products, such as 6- 10/8-14 day, monthly, and seasonal forecasts

5 Objective Probabilistic Heavy Precipitation Tool Uses 0z, 6z, and 12z GFS ensemble members to forecast for 881 grid points across the CONUS Rainfall totals not bias corrected or calibrated 1,2,and 3-day Hazards are forecast out to 384 hours A Hazard is defined as the greater of 1 inch/day or the 95 th percentile value Climatology (1971-2000) derived from U.S. precipitation dataset (Higgins et. al. 2000) Forecast probability contours in solid green, hazard thresholds in dashed black (in mm)

6 Reliability Diagrams (Using Total Precipitation in Period)

7 Reliability Diagrams (Using only 1 Day in Period)

8 1-Day Event Contingency Table Scores (10% threshold) POD a/(a+c) Threat Score a/(a+b+c) FAR b/(a+b) Bias a+b/a+c Day 30.320.140.801.62 Day 40.260.120.811.45 Day 50.210.100.851.38 Day 60.140.070.871.10 Day 70.090.050.880.83 Day 80.050.040.900.55 Assessment0.120.080.790.57 ab cd

9 2- Day Event Contingency Table Scores (10% threshold) 1 Day in PeriodPODThreat ScoreFARBias Days 2+30.130.090.760.55 Days 3+40.120.080.770.52 Days 4+50.100.070.780.48 Days 5+60.060.050.810.35 Assessment0.120.080.790.57 Total Precipitation in Period POD a/(a+c) Threat Score a/(a+b+c) FAR b/(a+b) Bias (a+b)/(a+c) Days 2+30.210.100.851.38 Days 3+40.170.080.861.18 Days 4+50.160.080.851.19 Days 5+60.150.080.861.09 Assessment0.120.080.790.57 ab cd

10 3-Day Event Contingency Table Scores (10 % threshold) Total Precipitation in Period POD a/(a+c) Threat Score a/(a+b+c) FAR b/(a+b) Bias (a+b)/(a+c) Days 1+2+30.080.050.910.95 Days 2+3+40.090.050.900.91 Days 3+4+50.080.050.880.67 Assessment0.120.080.790.57 1 Day in PeriodPODThreat ScoreFARBias Days 1+2+30.050.040.800.24 Days 2+3+40.04 0.810.22 Days 3+4+50.03 0.820.17 Assessment0.120.080.790.57 ab cd

11 ROC Diagram

12 Conclusions Limited usefullness of this tool in a strict probabilistic sense 1-Day Hazard forecasts show the best improvement over human-made Assessments Tool can immediately be used by forecasters as a first guess There is validity in converting the Hazards Assessments into a probabilistic forecast

13 Future Work Determine best definition of a hazard Generate contingency tables using different thresholds Use calibrated precipitation forecasts and calibrated probabilities. Use more ensembles in forecast (e.g. CAN, ECMWF, CFS)

14 Reference Higgins, R.W., W. Shi, E. Yarosh and R. Joyce, 2000: Improved United States Precipitation Quality Control System and Analysis. NCEP/Climate Prediction Center Atlas No. 7.


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