Evaluation and application of the short-range (0-6 hr) PQPFs from an ensemble prediction system based on LAPS
| Autor: | Hui-Ling Chang, 張惠玲 |
|---|---|
| Rok vydání: | 2014 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 102 Due to the low predictability in severe weather prediction such as typhoon forecasting, it is important to develop a reliable short-range ensemble prediction system (EPS).This study aims to develop the short-range (0-6h) probabilistic quantitative precipitation forecasts (PQPFs) of typhoons from time-lagged multimodel ensembles using the Local Analysis and Prediction System (LAPS). The ultimate goal is to provide valuable precipitation forecasts for typhoons based on the EPS and help the users optimize their decision making by using the ensemble probabilistic forecasts (EPFs). The LAPS ensemble prediction system (EPS) has a good spread-skill relationship and good discriminating ability. Therefore, though it is obviously wet-biased, the forecast biases can be corrected to improve the skill of PQPFs through a linear regression (LR) calibration procedure. Sensitivity experiments for two important factors affecting calibration results are also conducted, including: (1) the experiments on different training samples, and (2) the experiments on the inconsistency of observation accuracy. The first point reveals that the calibration results are sensitive to the training samples. Calibration should be performed based on consistent forecast biases between training and validation samples The second factor indicates that the accuracy of observation is inconsistent in the sea and land areas, and samples are dominated by the ocean ones. Therefore, individual calibration for these two areas is needed to ensure better calibration results. The measure of the usefulness of weather forecasts not only considers the forecast quality, but also the economic benefit associated with the actual use in the daily decision-making process of users. Discrimination ability, which can be assessed by the relative operating characteristic (ROC), is one of the characteristics for evaluating the quality of a forecast and is closely related to the economic value (EV) provided by the same forecast system. Therefore, the other two points in this study is to investigate the consistent and related characteristics between ROC and EV using LAPS PQPFs, and illustrate how to optimize the decision making by using the EPFs. Comparing the ROC and EV derived from EPFs and deterministic forecasts (DFs), EPFs have the advantage over DFs in respect of the discrimination and EV, and such an advantage grows with increasing precipitation intensity. Results from sensitivity experiment on calibration show that the discrimination ability and the maximum EV (EVmax) obtained from a forecast system are insensitive to forecast bias. Due to the terrain-locking effect on typhoon rainfall, LAPS PQPFs have greater discrimination ability, provide more reliable forecast information and offer higher EV to users with high cost-loss ratios in the mountain area than the plain area. Results show that the difference of EV between the mountain and plain areas is mainly attributed to the different discrimination ability in these areas. We also illustrate that even without explicitly knowing the cost-loss ratio, users can still optimize their decision-making and obtain the EVmax by using the EPFs. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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