Open AccessAnalysis of the Relative Operating Characteristic and Economic Value Using the LAPS Ensemble Prediction System in Taiwan
Author(s) -
Hui Ling Chang,
Shun Yang,
Huiling Yuan,
Pay Liam Lin,
Yeuh–Yeong Liou
Publication year - 2015
Publication title -
monthly weather review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.862
H-Index - 179
eISSN - 1520-0493
pISSN - 0027-0644
DOI - 10.1175/mwr-d-14-00189.1
Subject(s) - probabilistic logic , calibration , terrain , sensitivity (control systems) , ensemble forecasting , computer science , statistics , range (aeronautics) , typhoon , precipitation , probabilistic forecasting , environmental science , receiver operating characteristic , threshold limit value , quantitative precipitation forecast , meteorology , mathematics , artificial intelligence , geography , cartography , electronic engineering , engineering , medicine , materials science , environmental health , composite material
Measurement of the usefulness of numerical weather prediction considers not only the forecast quality but also the possible economic value (EV) in the daily decision-making process of users. Discrimination ability of an ensemble prediction system (EPS) can be assessed by the relative operating characteristic (ROC), which is closely related to the EV provided by the same forecast system. Focusing on short-range probabilistic quantitative precipitation forecasts (PQPFs) for typhoons, this study demonstrates the consistent and strongly related characteristics of ROC and EV based on the Local Analysis and Prediction System (LAPS) EPS operated at the Central Weather Bureau in Taiwan. Sensitivity experiments including the effect of terrain, calibration, and forecast uncertainties on ROC and EV show that the potential EV provided by a forecast system is mainly determined by the discrimination ability of the same system. The ROC and maximum EV (EVmax) of an EPS are insensitive to calibration, but the optimal probability threshold to achieve the EVmax becomes more reliable after calibration. In addition, the LAPS ensemble probabilistic forecasts outperform deterministic forecasts in respect to both ROC and EV, and such an advantage grows with increasing precipitation intensity. Also, even without explicitly knowing the cost–loss ratio, one can still optimize decision-making and obtain the EVmax by using ensemble probabilistic forecasts.