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Development and assessment of optimal methods for regional prediction with bias correction

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  • Development and assessment of optimal methods for regional prediction with bias correction
  • Yhang, Yoobin양유빈
  • APCC


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Title Development and assessment of optimal methods for regional prediction with bias correction
Similar Titles
Material Type Reports
Author(English)

Yhang, Yoobin

Author(Korean)

양유빈

Publisher

Busan:APCC

Date 2015
Series Title; No 연구보고서 / 2015-03
Subject Country South Korea(Asia and Pacific)
Language English
File Type Link
Subject Industry and Technology < Others
Territorial Development < Environment
Holding APCC

Abstract

Improved dynamical downscaling methods with ageneral circulation model (GCM) bias corrections are developed and assessedover East Asia. A set of regional climate simulationsis performed with the Global/Regional Integrated Model system (GRIMs) embedded in the Climate Forecast System (CFS) seasonal prediction data for 2005 winter. Four bias correction methods areconsidered: 1) ensemble average, 2) anomaly nesting, 3) anomaly nesting with standard deviation, and 4) ensemble anomaly nesting. Theanalysis reveals that the simulation with ensemble anomaly nesting method improves the downscaled climate in both seasonal mean and extreme events relative to the simulations with original CFS data without bias correction. This dynamically downscaled forecast is compared with the CFS produced by global forecast model in weak, normal, and strong winter monsoon year. (The rest omitted)