A Regional Ensemble Forecast System for Stratiform Precipitation Events in the Northern China Region. Part II: Seasonal Evaluation for Summer 2010

In this study, the Institute of Atmospheric Physics, Chinese Academy of Sciences - regional ensemble forecast system (IAP-REFS) described in Part I was further validated through a 65-day experiment using the summer season of 2010. The verification results show that IAP-REFS is skillful for quantitat...

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Published inAdvances in atmospheric sciences Vol. 30; no. 1; pp. 15 - 28
Main Author 朱江山 孔凡铀 雷恒池
Format Journal Article
LanguageEnglish
Published Heidelberg SP Science Press 01.01.2013
Springer Nature B.V
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ISSN0256-1530
1861-9533
DOI10.1007/s00376-012-1043-x

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Summary:In this study, the Institute of Atmospheric Physics, Chinese Academy of Sciences - regional ensemble forecast system (IAP-REFS) described in Part I was further validated through a 65-day experiment using the summer season of 2010. The verification results show that IAP-REFS is skillful for quantitative precipitation forecasts (QPF) and probabilistic QPF, but it has a systematic bias in forecasting near-surface variables. Applying a 7-day running mean bias correction to the forecasts of near-surface variables remarkably improved the reliability of the forecasts. In this study, the perturbation extraction and inflation method (proposed with the single case study in Part I) was further applied to the full season with different inflation factors. This method increased the ensemble spread and improved the accuracy of forecasts of precipitation and near-surface variables. The seasonal mean profiles of the IAP-REFS ensemble indicate good spread among ensemble members and some model biases at certain vertical levels.
Bibliography:In this study, the Institute of Atmospheric Physics, Chinese Academy of Sciences - regional ensemble forecast system (IAP-REFS) described in Part I was further validated through a 65-day experiment using the summer season of 2010. The verification results show that IAP-REFS is skillful for quantitative precipitation forecasts (QPF) and probabilistic QPF, but it has a systematic bias in forecasting near-surface variables. Applying a 7-day running mean bias correction to the forecasts of near-surface variables remarkably improved the reliability of the forecasts. In this study, the perturbation extraction and inflation method (proposed with the single case study in Part I) was further applied to the full season with different inflation factors. This method increased the ensemble spread and improved the accuracy of forecasts of precipitation and near-surface variables. The seasonal mean profiles of the IAP-REFS ensemble indicate good spread among ensemble members and some model biases at certain vertical levels.
short-range ensemble forecast, rain enhancement operation, probabilistic forecast
11-1925/O4
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ISSN:0256-1530
1861-9533
DOI:10.1007/s00376-012-1043-x