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集合变分混合同化方案在快速循环同化系统中的应用研究

张涵斌 李玉焕 陈敏 冯琎 范水勇 沈海波

张涵斌, 李玉焕, 陈敏, 等. 2020. 集合变分混合同化方案在快速循环同化系统中的应用研究[J]. 大气科学, 44(6): 1349−1363 doi:  10.3878/j.issn.1006-9895.2008.20118
引用本文: 张涵斌, 李玉焕, 陈敏, 等. 2020. 集合变分混合同化方案在快速循环同化系统中的应用研究[J]. 大气科学, 44(6): 1349−1363 doi:  10.3878/j.issn.1006-9895.2008.20118
ZHANG Hanbin, LI Yuhuan, CHEN Min, et al. 2020. Implementation of Hybrid En-3DVAR Assimilation Scheme in Rapid Cycling Assimilation System [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(6): 1349−1363 doi:  10.3878/j.issn.1006-9895.2008.20118
Citation: ZHANG Hanbin, LI Yuhuan, CHEN Min, et al. 2020. Implementation of Hybrid En-3DVAR Assimilation Scheme in Rapid Cycling Assimilation System [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(6): 1349−1363 doi:  10.3878/j.issn.1006-9895.2008.20118

集合变分混合同化方案在快速循环同化系统中的应用研究

doi: 10.3878/j.issn.1006-9895.2008.20118
基金项目: 国家重点研究发展计划项目2018YFC1506804,江苏省研究生科研创新计划项目KYCX18_1000
详细信息
    作者简介:

    张涵斌,男,1987年出生,副研究员,主要从事集合预报研究。E-mail: zhb828828@163.com

    通讯作者:

    李玉焕,E-mail: yhli@ium.cn

  • 中图分类号: P456

Implementation of Hybrid En-3DVAR Assimilation Scheme in Rapid Cycling Assimilation System

Funds: National Key Research and Development Project (Grant 2018YFC1506804), Research Innovation Program for Graduates of Jiangsu Province (Grant KYCX18_1000)
  • 摘要: 基于北京市气象局快速循环同化系统RMAPS-ST以及对流尺度集合预报系统RMAPS-EN,构建了En-3DVAR集合变分混合同化系统,将该系统应用到业务快速循环同化系统中并进行试验,分别在冷启动与循环启动环境下对比了混合同化系统(Hybrid)与三维变分(3DVAR)的同化预报效果。获得的结论如下:单点试验结果表明,混合同化系统分析增量的分布与集合预报离散度分布具有较好的对应关系;在冷启动和循环启动中,三维变分的分析增量都表现出各向同性的特点,混合同化分析增量均表现出一定的流依赖特征;降水个例分析表明,在冷启动环境中,Hybrid与3DVAR效果相当,而在循环启动中,Hybrid的降水预报相对于3DVAR有较明显的改进效果;批量试验检验结果表明,冷启动中,Hybrid与3DVAR的评分大致相当,而在循环启动中,Hybrid相对于3DVAR的评分有明显改进;集合离散度和背景场误差的相关性分析表明二者在循环启动环境下具有更好的相关性。
  • 图  1  RMAPS-ST循环同化系统区域设置

    Figure  1.  Domain configuration of RMAPS-ST (Rapid-refresh Multi-scale Analysis and Prediction System–Short Term) system

    图  2  RMAPS Hybrid En-3DVAR混合同化系统运行流程

    Figure  2.  Flowchart of the hybrid En-3DVAR (ensemble-three-dimensional variational data assimilation) system of RMAPS

    图  3  2018年7月15日12时(协调世界时,下同)区域集合预报RMAPS-EN起报12 h预报时效的500 hPa纬向风集合离散度(阴影,单位:m s−1)和业务RMAPS-ST的d02区域(图1)分析场的位势高度场(等值线,单位:gpm)分布

    Figure  3.  Horizontal pattern of ensemble spread of 500-hPa zonal wind (shadings, units: m s−1) from 12-h forecast with ensemble forecast system of RMAPS-EN initiated at 1200 UTC 15 July 2018, and the corresponding geopotential height (solid lines, units: gpm) from the operational RMAPS-ST analysis of domain d02 in Fig. 1

    图  4  不同集合权重构建背景误差协方差的单点试验模式第15层纬向风分析增量水平分布(单位:m s−1):(a)0;(b)1/5;(c)1/2;(d)1

    Figure  4.  Zonal wind analysis increment horizontal distributions (units: m s−1) for different ensemble proportions in background error covariance at the fifteenth level of model: (a) 0; (b) 1/5; (c) 1/2; and (d) 1

    图  5  2018年7月16日00时四种同化方案在模式层第16层纬向风的分析增量(单位:m s−1):(a)3DVAR-cold方案;(b)Hybrid-cold方案;(c)3DVAR-cycle方案;(d)Hybrid-cycle方案

    Figure  5.  Analysis increments (units: m s−1) of zonal wind at the 16th model level for the four schemes at 0000 UTC 16 July 2018: (a) 3DVAR-cold scheme (3DVAR in the cold run); (b) hybrid-cold scheme (hybrid in the cold run); (c) 3DVAR-cycle scheme (3DVAR in the partial cycle run); (d) hybrid-cycle scheme (hybrid in the partial cycle run)

    图  6  2018年7月16日00时起报的18 h预报时效的(a)3DVAR-cold方案、(b)Hybrid-cold方案700 hPa高度风场(箭头,单位:m s−1)及相对湿度(阴影),以及(c)在冷启动、循环设置下Hybrid相对于3DVAR方案的700 hPa高度风场(箭头,单位:m s−1)、相对湿度的差异分布。(d–f)同(a–c),但为循环启动设置下物理量的分布

    Figure  6.  Distributions of wind vectors (arrows, units: m s−1) and relative humidity (shadings) at 700 hPa from the 18th-hour forecast obtained from (a) 3DVAR-cold scheme, (b) hybrid-cold scheme, and (c) the differences between 3DVAR-cold scheme and hybrid-cold scheme at 0000 UTC 16 July 2018. (d–f) As in (a–c), but for distributions for 3DVAR-cycle scheme and hybrid-cycle scheme

    图  7  2018年7月16日18时至2018年7月17日00时的6 h累计降水量分布实况以及四种方案对该时段降水量的预报(单位:mm):(a)实况;(b)3DVAR-cold方案预报;(c)Hybrid-cold方案预报;(d)3DVAR-cycle方案预报;(e)Hybrid-cycle方案预报

    Figure  7.  Six-hour accumulated precipitation (units: mm) obtained from observation and forecast from the four schemes from 1800 UTC 16 July to 0000 UTC 17 July 2018: (a) Observation; (b) forecast from 3DVAR-cold scheme; (c) forecast from hybrid-cold scheme; (d) forecast from 3DVAR-cycle scheme; (e) forecast from hybrid-cycle scheme

    图  8  2018年7月16日00时至7月17日00时的逐6 h累计降水量的四种方案(3DVAR-cold、hybrid-cold、3DVAR-cycle、hybrid-cycle)预报的不同降水量级的TS评分和Bias评分:(a)0.1 mm TS评分;(b)1 mm TS评分;(c)10 mm TS评分;(d)0.1 mm Bias评分;(e)1 mm Bias评分;(f)10 mm Bias评分

    Figure  8.  The TS (threat score) and Bias score of 6-h accumulative forecast precipitation from 0000 UTC 16 July to 0000 UTC 17 July 2018 in four schemes (3DVAR-cold scheme, hybrid-cold scheme, 3DVAR-cycle scheme, hybrid-cycle scheme): (a) 0.1 mm TS; (b) 1 mm TS; (c) 10 mm TS; (d) 0.1 mm Bias score; (e) 1 mm Bias score; (f) 10 mm Bias score

    图  9  四种方案(3DVAR-cold、hybrid-cold、3DVAR-cycle、hybrid-cycle)(a)2 m高度处温度、(b)10 m高度处纬向风的12 h、24 h预报均方根误差

    Figure  9.  RMSE of (a) temperature at 2-m height, (b) zonal wind at 10-m height for the 12th and 24th forecast hours in the four schemes (3DVAR-cold scheme, hybrid-cold scheme, 3DVAR-cycle scheme, hybrid-cycle scheme)

    图  10  不同要素的预报误差与集合扰动的相关系数分布:(a)纬向风;(b)经向风;(c)温度;(d)气压

    Figure  10.  Distributions of correlation coefficients between ensemble perturbations and forecast errors: (a) Zonal wind; (b) meridional wind; (c) temperature; (d) pressure

    表  1  试验设置

    Table  1.   Test settings

    试验方案背景场背景误差协方差同化方法
    3DVAR-coldECMWF分析场NMC静态3DVAR
    Hybrid-coldECMWF分析场NMC静态+集合Hybrid
    3DVAR-cycleRMAPS-ST 3 h循环预报场NMC静态3DVAR
    Hybrid-cycleRMAPS-ST 3 h循环预报场NMC静态+集合Hybrid
    下载: 导出CSV

    表  2  不同背景场设置(cold和cycle)下Hybrid同化方案相较于3DVAR同化方案的各物理量不同预报时效的均方根误差改进百分比

    Table  2.   The improvement RMSE (Root Mean Square Error) percentage of different variables at different forecast lead time for the hybrid relative to 3DVAR in different backgrounds (cold and cycle runs)

    物理量不同预报时效的均方根误差改进百分比(cold)不同预报时效的均方根误差改进百分比(cycle)
    6 h12 h18 h24 h6 h12 h18 h24 h
    200 hPa纬向风2.59%−2.13%−0.58%1.97%10.45%−0.45%1.62%1.18%
    500 hPa纬向风3.56%0.41%1.44%−0.11%3.34%1.02%0.58%0.79%
    850 hPa纬向风1.19%0.33%1.29%−2.61%1.24%2.81%2.43%−1.05%
    200 hPa经向风3.91%−2.43%−2.87%−0.58%8.61%3.13%−0.27%2.87%
    500 hPa经向风1.99%0.82%1.90%1.17%3.22%4.09%6.91%1.04%
    850 hPa经向风0.07%0.76%1.00%1.08%0.89%1.20%2.16%−2.32%
    500 hPa温度0.96%−1.77%-0.17%−2.69%3.16%5.04%1.10%−0.78%
    850 hPa温度−0.06%0.19%0.77%−0.81%1.45%4.03%1.44%0.24%
    500 hPa位势高度−0.35%1.55%2.10%2.38%−0.65%2.73%1.43%1.66%
    700 hPa相对湿度−0.02%2.02%2.69%0.34%1.02%3.15%1.18%0.58%
    850 hPa相对湿度−0.02%−0.40%0.18%−0.47%1.04%1.26%1.08%1.21%
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-02-21
  • 网络出版日期:  2020-08-25
  • 刊出日期:  2020-11-15

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