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An Experiment to Evaluate the Use of Quantitative Precipitation Forecasts from Numerical Guidance by Operational Forecasters. Joshua M. Boustead and Daniel Nietfeld NOAA/NWS WFO Omaha/Valley, NE Ray Wolf NOAA/NWS WFO Davenport, IA. Presentation Overview. Study purpose and methodology
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An Experiment to Evaluate the Use of Quantitative Precipitation Forecasts from Numerical Guidance by Operational Forecasters Joshua M. Boustead and Daniel Nietfeld NOAA/NWS WFO Omaha/Valley, NE Ray Wolf NOAA/NWS WFO Davenport, IA
Presentation Overview • Study purpose and methodology • Data results • Survey results • Snowfall forecast • Watch/warning statistics • Gridded forecast results • Forecasting implications, conclusions, and future work
Study Motivation • Strong interest in the role of the future forecaster • Can we still add value to the everyday forecast? • How can we better concentrate on high-impact weather? • How can we better utilize increasingly high-tech tools into the everyday forecast? • How does this increasingly high-tech information affect the forecaster?
Study Purpose • To evaluate if and how operational forecasters are biased by numerically generated quantitative precipitation forecasts (QPF) • Use these results to develop an updated methodology for operational forecasters on how to approach a daily forecast and utilize the latest technology, including high resolution model output
Study Methodology • Utilizing the National Weather Service’s (NWS) Warning Event Simulator (WES) operational forecasters from two NWS offices made two forecasts for two winter weather case • The forecasters first completed the forecast, including making a warning decision, without the use of model QPF • The forecasters then went through the same case again with model QPF, again making a snowfall forecast as well as a warning decision • Once each scenario was completed, the forecasters completed a survey about the specific case
Study Methodology • Two winter weather cases were chosen from the Central and Northern Plains • December 7-8, 2005 from the Pleasant Hill, MO (EAX) forecast area • February 28 – March 1, 2004 from the Bismarck, ND (BIS) forecast area
Survey Results • Forecaster Demographics: • Forecasters were from the NWS offices in Omaha/Valley, NE and Davenport, IA • Operational forecasters involved were of a high experience level
Survey Results • Forecaster confidence without using model QPF: • Majority of operational forecasters felt confident in making a forecast without model QPF • Potentially due to the high experience level of the forecasters
SurveyResults • Forecaster confidence after seeing QPF: • Most forecasters indicated that seeing QPF either increased their forecast confidence or it was unchanged
Snowfall Forecast Results • MAE was computed for each location and then averaged for before and after the use of QPF • MAE decreased 0.5 inches for both the EAX and BIS case post QPF
Snowfall Forecast Results • Majority of the forecasts were unchanged post QPF • Majority of the forecasts that did change their forecast, increased accuracy
Warning Results • The probability of detection (POD) and false alarm ratio (FAR) were computed by county for each of the forecast areas • Forecasters showed improvement in both the POD and in FAR ratio once QPF was used
Gridded Forecast ResultsEAX Case • EAX Pre and Post QPF MAE • Forecasters had the most confidence in the northern CWA • Much better agreement over the southern CWA post QPF • Also a 2 to 3 inch decrease in MAE over the south
Gridded Forecast ResultsEAX Case • EAX Pre and Post QPF Standard Deviation • Forecast differences decreased over the north and south • Slight increase in differences over the center
Gridded Model ForecastsEAX Case • Greatest agreement of snow band across central CWA • Viewing QPF increased the forecast confidence in the southern CWA
Gridded Forecast ResultsBismarck Case • BIS Pre and Post QPF MAE • Good agreement and low error over the northwest forecast area • Mean errors of 5 to 6 inches over the southern and eastern forecast area
Gridded Forecast ResultsBismarck Case • Pre and Post QPF Standard Deviation • Significant increase in forecaster clustering across the central forecast area • Greater than 4 inch differences continue over the southern forecast area
Gridded Model ForecastsBIS Case • Models agree northwest CWA to get least QPF • Larger uncertainty in the south • Forecasters tended to pick a model • Led to continued large MAE in the southern CWA
Discussion • Only a slight improvement in snowfall forecasts was noted once forecasters viewed QPF • When snowfall forecasts were modified, a higher percentage were improved than degraded • Model QPF seemed best utilized to resolve snow-no snow areas • This led to improvements in both FAR and POD • High MAE did not always mean high standard deviation, which can indicate a systematic forecasting error • Doesn’t clearly answer the question does model QPF bias forecasters • Some evidence in the BIS case where model agreement was poor • Possible forecast methodology • Make entire forecast without QPF • Utilize QPF for placement for defining snow-no snow areas
Future Work • Conduct the study using two warm season convective cases • Investigate forecaster philosophy from the surveys where standard deviation is low and mean absolute error is higher • Investigate what, if any, synoptic patterns increase forecaster uncertainty and MAE • Continue to increase the number of forecasters in the study, and from different areas of the CONUS