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- Author or Editor: FEDOR MESINGER x
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Abstract
Bias-adjusted threat and equitable threat scores were designed to account for the effects of placement errors in assessing the performance of under- or overbiased forecasts. These bias-adjusted performance measures exhibit bias sensitivity. The critical performance ratio (CPR) is the minimum fraction of added forecasts that are correct for a performance measure to indicate improvement if bias is increased. In the opposite case, the CPR is the maximum fraction of removed forecasts that are correct for a performance measure to indicate improvement if bias is decreased. The CPR is derived here for the bias-adjusted threat and equitable threat scores to quantify bias sensitivity relative to several other measures of performance including conventional threat and equitable threat scores. The CPR for a bias-adjusted equitable threat score may indicate the likelihood of preserving or increasing the conventional equitable threat score if forecasts are bias corrected based on past performance.
Abstract
Bias-adjusted threat and equitable threat scores were designed to account for the effects of placement errors in assessing the performance of under- or overbiased forecasts. These bias-adjusted performance measures exhibit bias sensitivity. The critical performance ratio (CPR) is the minimum fraction of added forecasts that are correct for a performance measure to indicate improvement if bias is increased. In the opposite case, the CPR is the maximum fraction of removed forecasts that are correct for a performance measure to indicate improvement if bias is decreased. The CPR is derived here for the bias-adjusted threat and equitable threat scores to quantify bias sensitivity relative to several other measures of performance including conventional threat and equitable threat scores. The CPR for a bias-adjusted equitable threat score may indicate the likelihood of preserving or increasing the conventional equitable threat score if forecasts are bias corrected based on past performance.
Abstract
A step-mountain (eta) coordinate limited-area model is being developed at the National Meteorological Center (NMC) to improve forecasts of severe weather and other mesoscale phenomena. Precipitation forecasts are reviewed for the 20-day period 16 June–5 July 1989. This period was chosen not only because of intense warm-season precipitation, including that of Tropical Storm Allison, but also because two sets of forecasts from NMC's nested grid model (NGM) were available for comparison, one using the operational Kuo convection and the other using the eta model's Betts-Miller convection scheme. Thus, a three-way model comparison was possible.
Particular attention is paid to the forecasts of precipitation maxima. With verification performed on accumulated 24-h amounts averaged over the limited fine mesh (LFM) model grid boxes, the eta model shows skill at the highest observed precipitation category in 14 out of 58 verification periods, about one fourth of all cases. The forecasts also show a high degree of consistency in that successful forecasts starting from different initial times are produced for the same verification period.
Although the eta model was less successful than the NGM in predicting the lightest precipitation category, it demonstrated noted improvement in the 0.50-inch and greater categories, regardless of the convection scheme used in the NGM. Evidence is presented which indicates that the greater accuracy of the eta model is primarily a result of its space differencing schemes.
Abstract
A step-mountain (eta) coordinate limited-area model is being developed at the National Meteorological Center (NMC) to improve forecasts of severe weather and other mesoscale phenomena. Precipitation forecasts are reviewed for the 20-day period 16 June–5 July 1989. This period was chosen not only because of intense warm-season precipitation, including that of Tropical Storm Allison, but also because two sets of forecasts from NMC's nested grid model (NGM) were available for comparison, one using the operational Kuo convection and the other using the eta model's Betts-Miller convection scheme. Thus, a three-way model comparison was possible.
Particular attention is paid to the forecasts of precipitation maxima. With verification performed on accumulated 24-h amounts averaged over the limited fine mesh (LFM) model grid boxes, the eta model shows skill at the highest observed precipitation category in 14 out of 58 verification periods, about one fourth of all cases. The forecasts also show a high degree of consistency in that successful forecasts starting from different initial times are produced for the same verification period.
Although the eta model was less successful than the NGM in predicting the lightest precipitation category, it demonstrated noted improvement in the 0.50-inch and greater categories, regardless of the convection scheme used in the NGM. Evidence is presented which indicates that the greater accuracy of the eta model is primarily a result of its space differencing schemes.
