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Diagnosis of Skill Variability of CPC Long-Lead Seasonal Forecasts: Implications for Production and Use. Bob Livezey and Marina Timofeyeva NOAA/NWS/OCWWS/Climate Services Division. Climate Diagnostics and Prediction Workshop October 21, 2004 Madison WI. Outline. Introduction
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Diagnosis of Skill Variability of CPC Long-Lead Seasonal Forecasts: Implications for Production and Use Bob Livezey and Marina Timofeyeva NOAA/NWS/OCWWS/Climate Services Division Climate Diagnostics and Prediction Workshop October 21, 2004 Madison WI
Outline • Introduction • Skill Stratifications • Results • Conclusions and Lessons
Introduction • Users should only care about the performance of forecasts that can potentially benefit their decision process • Livezey (1990): There are non-random subsets of seasonal forecasts that were skillful enough to be useful
Seasonal Temperature Forecast Skill 1960s to 80s Seasonal Temperature Forecast Skill 1960s to 80s All Seasons 8.3 Winter 12.6 Spring 8.6 Summer 9.3 Fall 2.8 All Seasons 8.3 Winter 12.6 Spring 8.6 Summer 9.3 Fall 2.8
Introduction (Cont.) • This talk will make the point : • That was made by Livezey (1990) • That there are many non-random subsets of forecasts that do not have useful skill • That it is critical for this information to be shared with potential users • That skill analyses with different stratifications are highly informative • That seasonal forecast production should be dominantly objective • That long-lead seasonal forecasts of non-trend signal should only be done on appropriate opportunities, not routinely
Displays and Stratifications • CPC Seasonal Forecasts • For 3-equally probable temperature and precipitation classes at 102 Climate Divisions • Made every month from 1995 to present for 0.5-, 1.5-, …, 12.5 month leads • Skill Measure: Modified Heidke Skill Score of Categorized Forecasts • 1/3 EC’s scored as ‘hits’ • Displays and Stratifications • Summed over all forecasts for each lead for three overlapping seasons at a time (DJF to FMA, FMA to AMJ, etc.) • Stratified further by strong ENSO years vs. other years • Mapped for appropriate combinations of leads
Results • Seasonal Temperature Die-Aways: • Moderate to high national-scale skill confined to Fall/Winter strong ENSO years at short to medium leads • Otherwise skill is dominantly modest and level with lead (derived from biased climatologies, ie long-term trend) • Worst forecasts are for • Fall/Winter at short to medium leads for non strong-ENSO years: Forecasters subtracting value • Summer/Fall at medium to long leads for strong ENSOs: No remedy except science advances • Short-lead forecasts are better now than for the 1960s-80s, ~14 vs ~8 overall, ~20 vs ~13 for the winter
Results • Seasonal Temperature Maps: • Without a strong ENSO, justification for OND-DJF forecasts is questionable • For certain regions/seasons/situations skill is unambiguously useful even for undisciplined, occasional users
Results • Seasonal Precipitation Die-Aways: • Barely useable national-scale skill entirely confined to Fall/Winter strong ENSO years in short to medium leads • Otherwise skill is statistically indistinguishable from zero • Short-lead forecasts overall seem to be no better now than for the 1960s-80s (but at least are now made two-weeks earlier)
Results • Seasonal Precipitation Maps: • Justification for long-lead forecasts is questionable for at least three of six seasonal groups examined • For certain regions/seasons/situations skill is unambiguously useful even for undisciplined, occasional users
Conclusions and Recommendations • There are non-random subsets of seasonal forecasts that are skillful enough even for undisciplined, occasional users • These skills exclusively reflect ENSO and trend signals • There are many non-random subsets of forecasts that do not have useful skill • We must share this information with potential users • Skill analyses with different stratifications are highly informative • Seasonal forecast production should dominantly rely on objective exploitation of ENSO and trend with subjective modification only after rigorous criteria are met • Routine production of certain long-lead forecasts should be terminated (can be accommodated by transition to separate trend and high frequency forecasts with latter issued on forecast of opportunity basis only)
