An assessment of applicability of the extreme forecast index in KMA seasonal prediction
Abstract
The study is to assess the forecasting applicability of the Extreme Forecast Index (EFI), for the Global Seasonal forecasting system version 5 (GloSea5) of the Korea Meteorological Administration (KMA).
The EFI is a measure of the difference between the ensemble forecast distribution and the model climate distribution. In this study, EFI algorithm are applied to extreme hot temperature forecasts using GloSea5 hindcast data during the summer(June, July, August) from 1991 to 2010, with raw and bias-corrected forecast. The bias correction was calculated in a cross-validated method where each corrected forecast dose not contribute to the forecast average. The skill of the EFI forecasts is assessed using the verification metrics; hit rate and the false alarm rate. These hit and false alarm rates were evaluated with performance diagram for EFI. As a result, the EFI shows warm signals and high value of EFI for heat wave cases; the Korea in 1994 and the Europe in 2003. The spatial distribution of bias-corrected EFI predicts unusual weather in Korea (EFI≥0.6) and Europe (EFI≥0.4). For the performance diagram, the bias-corrected EFI forecasts are more concentrated in the upper right corner along the diagonal than for the raw EFI. The bias-corrected forecast performs slightly better than the raw forecast. We expected that these results will lead to forecasting of unusual weather occurred during seasonal scales.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A11K2377H
- Keywords:
-
- 3329 Mesoscale meteorology;
- ATMOSPHERIC PROCESSESDE: 3354 Precipitation;
- ATMOSPHERIC PROCESSESDE: 1880 Water management;
- HYDROLOGYDE: 4313 Extreme events;
- NATURAL HAZARDS