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Probabilistic Forecasts of Extreme Precipitation Events for the U.S. Hazards Assessment. Kenneth Pelman 32 nd Climate Diagnostics Workshop Tallahassee, Florida. Outline. Current Hazards Assessment Motivation for Probabilistic Forecast Details of Objective Probabilistic Tool
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Probabilistic Forecasts of Extreme Precipitation Events for the U.S. Hazards Assessment Kenneth Pelman 32nd Climate Diagnostics Workshop Tallahassee, Florida
Outline • Current Hazards Assessment • Motivation for Probabilistic Forecast • Details of Objective Probabilistic Tool • Verification Results • Conclusions • Future Work
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
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
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 95th 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)
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
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)
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.