Comparison of ensemble methods for summer-time numerical weather prediction over East Asia

Autor:	Steve Cocke, D. W. Shin, Hae-Dong Kim, W.-S. Jung, Sung-Dae Kang
Rok vydání:	2011
Předmět:	Global Forecast System Atmospheric Science Ensemble forecasting Meteorology Quantitative precipitation forecast Environmental science Forecast skill Predictability Numerical weather prediction Ensemble learning Physics::Atmospheric and Oceanic Physics North American Mesoscale Model
Zdroj:	Meteorology and Atmospheric Physics. 113:27-38
ISSN:	1436-5065 0177-7971
DOI:	10.1007/s00703-011-0148-6
Popis:	Summer-time short- to medium-range predictability of precipitation, 500-hPa geopotential height, and wind fields over East Asia are investigated by comparing three ensemble forecast configurations: multi-analysis, multi-convection, and multi-model. These three systems are used in this study in order to assess initial condition uncertainties, model uncertainties, and a combination of initial condition and model uncertainties in an ensemble forecast approach. Each system has a set of six members. Ensemble forecast skill is verified in both deterministic and probabilistic senses using the European Center for Medium-range Weather Forecasting analyses and the Tropical Rainfall Measuring Mission Microwave Imager 2A12 rain estimates. The multi-model configuration, which considers both the initial condition and model uncertainties to predict weather phenomena over East Asia, is an optimal set of ensemble members. The bias-corrected ensemble and the superensemble (SE) show similar predictability, but slightly better skill is obtained from the SE forecasts.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c6b946ea88a44bb0ab6fc9af8876d876 https://doi.org/10.1007/s00703-011-0148-6 Zobrazit plný text záznamu Full text from SpringerLink