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The HMT-HPC Winter Weather Experiment explores the use of ensemble systems to improve the accuracy and communication of winter weather forecasts. The experiment includes daily activities, ensemble guidance, and analysis of forecast performance. Results show that storm-scale ensembles provide added benefits for winter weather forecasting by quantifying and communicating forecast uncertainty.
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The 2012 HMT-HPCWinter Weather Experiment Faye E. Barthold1,2, David R. Novak1, Michael J. Bodner1,Thomas E. Workoff1,3, Dan Petersen1, Richard Otto1, Michael Musher1, Richard Bann1, Andrew Orrison1, Jun Du4, and Scott Rentschler5 1NOAA/NWS/Hydrometeorological Prediction Center 2I.M.Systems Group, Inc. 3Systems Research Group, Inc. 4NOAA/NWS/Environmental Modeling Center 5Air Force Weather Agency
Winter Weather at HPC HPC Winter Weather Desk Internal NWS forecast guidance Public probabilistic forecasts HMT-HPC Accelerates R2O – O2R to enhance HPC services Identifies, tests, and provides training on new forecasting techniques Collaborates with other NOAA Testbeds, forecasters, and academia
Motivation Winter weather forecasts remain challenging Precipitation type and amount Forecast skill improving, but little information provided about forecast confidence Forecasts used to make increasingly important decisions
HMT-HPC Winter Weather Experiment GOAL: Explore the use of ensemble systems to better quantify and communicate uncertainty in winter weather forecasts 21 participants representing operations, research, and academia Daily Activities Probabilistic 24 hr snowfall forecasts 2”, 4”, 8” thresholds Model diagnostics investigation Forecast confidence discussion Societal impacts scenario Subjective evaluation January 9 – February 10, 2012
Ensemble Guidance Ensemble clusters Trend reverse (“flip-flop”) tool Critical temperature probability tool
HMT-HPC Winter Weather Experiment What added benefits do storm scale ensembles provide for winter weather forecasting? 24 hr HPC snowfall analysis valid 00Z 4 February 2012 SREF mean 24 hr snowfall accumulations (51 hr forecast)
HMT-HPC Winter Weather Experiment What added benefits do storm scale ensembles provide for winter weather forecasting? 24 hr HPC snowfall analysis valid 00Z 4 February 2012 AFWA mean 24 hr snowfall accumulations (48 hr forecast)
HMT-HPC Winter Weather Experiment Is the new NCEP SREF an improvement over the current operational system? 24 hr HPC snowfall analysis valid 00Z 3 January 2012 SREF mean 24 hr snowfall accumulations (75 hr forecast)
HMT-HPC Winter Weather Experiment Is the new NCEP SREF an improvement over the current operational system? 24 hr HPC snowfall analysis valid 00Z 3 January 2012 SREFP mean 24 hr snowfall accumulations (75 hr forecast)
Results Ensemble Mean Performance
Results Ensemble Probability Performance
Communicating Uncertainty Societal impacts scenario Mock briefing for a non-meteorological decision maker on the upcoming winter weather event Difficult to differentiate between projecting authority in the delivery of the briefing and conveying the level of forecast confidence Invert the scientific communication pyramid* Lessons Learned *Somerville, R. C. J., and S. J. Hassol, 2011: Communicating the science of climate change. Phys. Today, 64 (10), 48-53.
Operational Impacts Forecasters have confidence in using the SREFP for winter weather forecasts HPC is working with NCO to explore providing routine access to the AFWA ensemble Revealed challenges associated with snow-to-liquid ratio and precipitation type forecasts HMT-HPC working with EMC to explore alternatives Training resources for decision support briefings are available to HPC forecasters
Summary SREFP provided better winter weather forecasts than the current operational SREF AFWA ensemble provided realistic forecast details, but tended to have a high bias with snowfall amounts Effectively communicating forecast information takes practice Provide the bottom line first during decision support briefings Full report available at: http://www.hpc.ncep.noaa.gov/hmt/HMT-HPC_2012_Winter_Weather_Experiment_summary.pdf