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    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/100369


    Title: Analysis of the relative operating characteristic and economic value using the LAPS ensemble prediction system in Taiwan
    Authors: 楊舒芝;Chang, Hui-Ling;Yang, Shu-Chih;Yuan, Huiling;Lin, Pay-Liam;Liou, Yu-Chieng
    Contributors: 地球科學學院大氣科學學系
    Keywords: Bias;Calibration;Climatology;Decision making;Economics;EPS;Meteorology;Probabilistic methods;Probability theory;Rainfall intensity;Studies;Typhoons;Weather;Weather forecasting
    Date: 2015-01-01
    Issue Date: 2026-04-21 13:59:30 (UTC+8)
    Publisher: American Meteorological Society;Washington: American Meteorological Society
    Abstract: 摘要: 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.
    出版者: Washington: American Meteorological Society
    出版日期: 2015-05-01
    出處: Monthly weather review, 2015-05, Vol.143 (5), p.1833-1848
    資源來源: EBSCOhost OmniFile Full Text Select
    版權: Copyright American Meteorological Society May 2015
    識別號: ISSN: 0027-0644
    識別號: EISSN: 1520-0493
    識別號: DOI: 10.1175/MWR-D-14-00189.1
    識別號: CODEN: MWREAB
    Appears in Collections:[Department of Atmospheric Sciences] journal & Dissertation

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