Contribution to Third International Scientific Conference on the Global Energy and Water Cycle Objective Evaluation of QPF and PQPF Forecasts Based on NCEP Ensemble Yuejian Zhu and Zoltan Toth GSC/SAIC at Environmental Modeling Center National Centers for Environmental Prediction NWS/NOAA USA 1. Introduction: A subjective comparison of probabilistic quantitative precipitation forecasts (PQPF) based on the operational T62 resolution ensemble of forecasts ( Toth and Kalnay, 1997 ) and the T126 control quantitative precipitation forecasts (QPF) forecast at National Centers for Environmental Prediction (NCEP) indicates that the time period of skillful precipitation forecasts can be extended by a day or two by using the ensemble PQPF information ( Zhu and etc. 1998 ). In this study, we objectively evaluate QPF and PQPF forecasts based on the lower resolution T62 ensemble and the higher resolution T126 control forecasts over the continental United States by using daily analysis precipitation from hourly Gage data. QPF forecasts from the controls will be converted to PQPF forecasts based on past observed frequencies associated with given QPF values, while QPF information will be derived from the ensemble based PQPF probability distribution using the median (or other percentile such as 30%, 70% and so on) values. 2. Method: For representing PQPF distributions, the three-parameter Pearson Type lll (PE3) distribution ( Lehman 1997 ) will be used. For the comparison of QPF forecasts based on the control and ensemble forecasts, Equitable Threat Scores (ETS) and Standard Bias Scores (SBS) will be used for the evaluation for both controls and ensemble based PQPF forecasts. The evaluation period will be the full winter season of 1997-1998 which was December 1997, January 1998 and Feburary 1998. The observation data was 24 hours analysis from hourly accumulated Gage data ( Baldwin and etc. 1996 ). By the definition, the ETS is the ratio of (HIT - EXP) and (OBS + FCS - HIT - EXP) for all greater than the threshold value, where OBS is the numbers of observation, FCS is the numbers of forecasting, HIT is the numbers of forecasting hitting observation, and EXP is the ( FCS * OBS / TOT ), where the TOT is the total verifyable points. The SBS is the ratio of FCS and OBS. In a commom sense, the higher ETS is consider better, but for SBS, 1 is best. 3. Results: Based on the ETS and SBS from the full winter season, Figur 1 displays the season avaerage for 84-108 hours ( 24 hours ) forecast period for T126 control forecast ( MRF ), T62 low resolution control forecast ( T62 ) and medium ensemble forecast ( P50 ). For lower threshold values ( from 0.2 mm to 10.0 mm per day ), the medium ensemble forecast showes the highest ETS and good BiS which 1.0 is best. For higher threshold values ( beyond 25.0 mm per day ), the both control forecasts showes the good scores than ensemble medium, in practice, the real sample is very small when the threshold is larger. On the other hand, the different PQF will be drived from ensemble based PQPF by appling percentile such as 30%, 40%, 50%, 60% and 70% ( here 50% is the medium on the figur 1 ). Figur 2 showes the QPF from different percentile for the same season and forecast period. Clearly, it showes the best ETS and SBS from differnet percentile for each threshold value. From this diagram, we should be able to conclude that the QPF of emsemble is over-forecast for small precipitation ( such as 0.2 and 2.0 mm/day ) and less forecast for large precipitation amount ( such as 10 and 15 mm/day ). 4. Conclusion: From this seasonal objective evaluation and subjective evaluation which we did before, the ensemble based PQPF is more skillful when compared to control forecasts. The results of this study will be used in designing the calibration algorithm for ensemble-based NCEP PQPF forecasts. 4. References Lehman, R., 1997: Modeling precipitation data with Pearson Type III Distributions: Overview of new interactiive software "PFIT". Preprints of the 13th Conference on Hydrology, 2-7 February 1997, Long Beach, California, p. J150-J153. Baldwin, M., and K. Mitchell: The NCEP hourly multisensor U. S. precipitation analysis. Preprints, 11th NWP Conf. Norfolk, VA, 19-23 Aug. 1996, J95-96. Toth, Z., and E. Kalnay, 1997: Ensemble forecasting at NCEP and the breading method. Mon. Wea. Rev., 125, p. 3297-3319 Zhu, Y., Z. Toth, E. Kalnay and S. Tracton, 1998: Probabilistic Quantitative Precipitation Forecasts based on the NCEP global ensemble, Preprints, 14th Int. Conf. on Interative Information and Processing Systems for Meteorology, Oceanography, and Hydrology,11-16 January 1998, Phoenix, Arizona, p. J8-J11. Zhu, Y., G. Iyengar, Z. Toth, S. Tracton and T. Marchok, 1996: Objective evaluation of the NCEP global ensemble forecasting system. Preprints, 15th Conference on Weather Analysis and Forecasting, 19-23 august 1996, Norfolk, Virginia, p. J79-J82.