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Volume 30 Issue 1

Jan.  2013

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2013 >  30(1): 15-28

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

  • 1.

    Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Center for Analysis and Prediction of Storms, University of Oklahoma, USA;Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029


doi: 10.1007/s00376-012-1043-x

  • 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.
  • [1] ZHU Jiangshan, Fanyou KONG, LEI Hengchi, 2012: A Regional Ensemble Forecast System for Stratiform Precipitation Events in Northern China. Part I: A Case Study, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 201-216.  doi: 10.1007/s00376-011-0137-1
    [2] MA Juhui, Yuejian ZHU, Richard WOBUS, Panxing WANG, 2012: An Effective Configuration of Ensemble Size and Horizontal Resolution for the NCEP GEFS, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 782-794.  doi: 10.1007/s00376-012-1249-y
    [3] Zhaorong ZHUANG, Nusrat YUSSOUF, Jidong GAO, 2016: Analyses and Forecasts of a Tornadic Supercell Outbreak Using a 3DVAR System Ensemble, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 544-558.  doi: 10.1007/s00376-015-5072-0
    [4] ZHOU Baiquan, NIU Ruoyun, ZHAI Panmao, 2015: An Assessment of the Predictability of the East Asian Subtropical Westerly Jet Based on TIGGE Data, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 401-412.  doi: 10.1007/s00376-014-4026-2
    [5] FENG Yerong, David H. KITZMILLER, 2006: A Short-Range Quantitative Precipitation Forecast Algorithm Using Back-Propagation Neural Network Approach, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 405-414.  doi: 10.1007/s00376-006-0405-7
    [6] Jiaqi Zheng, Qing Ling, Jia Li, Yerong Feng, 2023: Improving Short-Range Precipitation Forecast of Numerical Weather Prediction Through a Deep Learning-Based Mask Approach, ADVANCES IN ATMOSPHERIC SCIENCES.  doi: 10.1007/s00376-023-3085-7
    [7] Jiangshan ZHU, Fanyou KONG, Xiao-Ming HU, Yan GUO, Lingkun RAN, Hengchi LEI, 2018: Impact of Soil Moisture Uncertainty on Summertime Short-range Ensemble Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 839-852.  doi: 10.1007/s00376-017-7107-1
    [8] ZHU Jiang, LIN Caiyan, WANG Zifa, 2009: Dust Storm Ensemble Forecast Experiments in East Asia, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 1053-1070.  doi: 10.1007/s00376-009-8218-0
    [9] Yuejian ZHU, 2005: Ensemble Forecast: A New Approach to Uncertainty and Predictability, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 781-788.  doi: 10.1007/BF02918678
    [10] T. N. Krishnamurti, Mukul Tewari, Ed Bensman, Wei Han, Zhan Zhang, William K. M. Lau, 1999: An Ensemble Forecast of the South China Sea Monsoon, ADVANCES IN ATMOSPHERIC SCIENCES, 16, 159-182.  doi: 10.1007/BF02973080
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    [12] T. N. KRISHNAMURTI, A. D. SAGADEVAN, A. CHAKRABORTY, A. K. MISHRA, A. SIMON, 2009: Improving Multimodel Weather Forecast of Monsoon Rain Over China Using FSU Superensemble, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 813-839.  doi: 10.1007/s00376-009-8162-z
    [13] Guo DENG, Yuejian ZHU, Jiandong GONG, Dehui CHEN, Richard WOBUS, Zhe ZHANG, 2016: The Effects of Land Surface Process Perturbations in a Global Ensemble Forecast System, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1199-1208.  doi: 10.1007/s00376-016-6036-8
    [14] Lu YANG, Cong-Lan CHENG, Yu XIA, Min CHEN, Ming-Xuan CHEN, Han-Bin ZHANG, Xiang-Yu HUANG, 2023: Evaluation of the Added Value of Probabilistic Nowcasting Ensemble Forecasts on Regional Ensemble Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 937-951.  doi: 10.1007/s00376-022-2056-8
    [15] Sijia LI, Yuan WANG, Huiling YUAN, Jinjie SONG, Xin XU, 2016: Ensemble Mean Forecast Skill and Applications with the T213 Ensemble Prediction System, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1297-1305.  doi: 10.1007/s00376-016-6155-2
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    [18] Jin FENG, Min CHEN, Yanjie LI, Jiqin ZHONG, 2021: An Implementation of Full Cycle Strategy Using Dynamic Blending for Rapid Refresh Short-range Weather Forecasting in China, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 943-956.  doi: 10.1007/s00376-021-0316-7
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    [20] ZHENG Xiaogu, WU Guocan, ZHANG Shupeng, LIANG Xiao, DAI Yongjiu, LI Yong, , 2013: Using Analysis State to Construct a Forecast Error Covariance Matrix in Ensemble Kalman Filter Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1303-1312.  doi: 10.1007/s00376-012-2133-5
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    • Manuscript History

    Manuscript received: 10 January 2013
    Manuscript revised: 10 January 2013
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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

    • 1. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Center for Analysis and Prediction of Storms, University of Oklahoma, USA;Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
    • Manuscript received: 2013-01-10
    • Manuscript revised: 2013-01-10

    Abstract: 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.

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