Global Distribution of the Skill of Tropical Cyclone Activity Forecasts on Short- to Medium-Range Time ScalesSource: Weather and Forecasting:;2015:;volume( 030 ):;issue: 006::page 1695Author:Yamaguchi, Munehiko
,
Vitart, Frédéric
,
Lang, Simon T. K.
,
Magnusson, Linus
,
Elsberry, Russell L.
,
Elliott, Grant
,
Kyouda, Masayuki
,
Nakazawa, Tetsuo
DOI: 10.1175/WAF-D-14-00136.1Publisher: American Meteorological Society
Abstract: perational global medium-range ensemble forecasts of tropical cyclone (TC) activity (genesis plus the subsequent track) are systematically evaluated to understand the skill of the state-of-the-art ensembles in forecasting TC activity as well as the relative benefits of a multicenter grand ensemble with respect to a single-model ensemble. The global ECMWF, JMA, NCEP, and UKMO ensembles are evaluated from 2010 to 2013 in seven TC basins around the world. The verification metric is the Brier skill score (BSS), which is calculated within a 3-day time window over a forecast length of 2 weeks to examine the skill from short- to medium-range time scales (0?14 days). These operational global medium-range ensembles are capable of providing guidance on TC activity forecasts that extends into week 2. Multicenter grand ensembles (MCGEs) tend to have better forecast skill (larger BSSs) than does the best single-model ensemble, which is the ECMWF ensemble in most verification time windows and most TC basins. The relative benefit of the MCGEs is relatively large in the north Indian Ocean and TC basins in the Southern Hemisphere where the BSS of the single-model ensemble is relatively small. The BSS metric and the reliability are found to be sensitive to the choice of threshold wind values that are used to define the model TCs.
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contributor author | Yamaguchi, Munehiko | |
contributor author | Vitart, Frédéric | |
contributor author | Lang, Simon T. K. | |
contributor author | Magnusson, Linus | |
contributor author | Elsberry, Russell L. | |
contributor author | Elliott, Grant | |
contributor author | Kyouda, Masayuki | |
contributor author | Nakazawa, Tetsuo | |
date accessioned | 2017-06-09T17:36:50Z | |
date available | 2017-06-09T17:36:50Z | |
date copyright | 2015/12/01 | |
date issued | 2015 | |
identifier issn | 0882-8156 | |
identifier other | ams-88085.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4231826 | |
description abstract | perational global medium-range ensemble forecasts of tropical cyclone (TC) activity (genesis plus the subsequent track) are systematically evaluated to understand the skill of the state-of-the-art ensembles in forecasting TC activity as well as the relative benefits of a multicenter grand ensemble with respect to a single-model ensemble. The global ECMWF, JMA, NCEP, and UKMO ensembles are evaluated from 2010 to 2013 in seven TC basins around the world. The verification metric is the Brier skill score (BSS), which is calculated within a 3-day time window over a forecast length of 2 weeks to examine the skill from short- to medium-range time scales (0?14 days). These operational global medium-range ensembles are capable of providing guidance on TC activity forecasts that extends into week 2. Multicenter grand ensembles (MCGEs) tend to have better forecast skill (larger BSSs) than does the best single-model ensemble, which is the ECMWF ensemble in most verification time windows and most TC basins. The relative benefit of the MCGEs is relatively large in the north Indian Ocean and TC basins in the Southern Hemisphere where the BSS of the single-model ensemble is relatively small. The BSS metric and the reliability are found to be sensitive to the choice of threshold wind values that are used to define the model TCs. | |
publisher | American Meteorological Society | |
title | Global Distribution of the Skill of Tropical Cyclone Activity Forecasts on Short- to Medium-Range Time Scales | |
type | Journal Paper | |
journal volume | 30 | |
journal issue | 6 | |
journal title | Weather and Forecasting | |
identifier doi | 10.1175/WAF-D-14-00136.1 | |
journal fristpage | 1695 | |
journal lastpage | 1709 | |
tree | Weather and Forecasting:;2015:;volume( 030 ):;issue: 006 | |
contenttype | Fulltext |