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广州“5.7”暴雨预报的模式不确定性研究

陈黛雅 沈学顺 霍振华

陈黛雅,沈学顺,霍振华. 2023. 广州“5.7”暴雨预报的模式不确定性研究. 气象学报,81(1):1-21 doi: 10.11676/qxxb2023.20220047
引用本文: 陈黛雅,沈学顺,霍振华. 2023. 广州“5.7”暴雨预报的模式不确定性研究. 气象学报,81(1):1-21 doi: 10.11676/qxxb2023.20220047
Chen Daiya, Shen Xueshun, Huo Zhenhua. 2023. A study on the model uncertainty of rainstorm forecast in Guangzhou on 7 May 2017. Acta Meteorologica Sinica, 81(1):1-21 doi: 10.11676/qxxb2023.20220047
Citation: Chen Daiya, Shen Xueshun, Huo Zhenhua. 2023. A study on the model uncertainty of rainstorm forecast in Guangzhou on 7 May 2017. Acta Meteorologica Sinica, 81(1):1-21 doi: 10.11676/qxxb2023.20220047

广州“5.7”暴雨预报的模式不确定性研究

doi: 10.11676/qxxb2023.20220047
基金项目: 国家重点研发计划“高精度可扩展数值天气预报模式研究”项目(2017YFC1501904)
详细信息
    作者简介:

    陈黛雅,主要从事对流尺度集合预报研究。E-mail:daiya_chen@126.com

    通讯作者:

    沈学顺,主要从事数值预报与数值模拟研究。E-mail: shenxs@cma.gov.cn

  • 中图分类号: P457P458

A study on the model uncertainty of rainstorm forecast in Guangzhou on 7 May 2017

  • 摘要: 2017年5月7日,在弱天气尺度强迫下,广州发生了暖区特大暴雨,局地发展迅速,降水强度极端,多家业务模式出现了漏报情况。为了探究此次降水过程模式预报的不确定性,采用条件非线性最优参数扰动(Conditional Nonlinear Optimal Perturbation related to Parameters,CNOP-P)方法筛选出最能体现中小尺度系统非线性误差增长特征的关键物理参数,以此构造CNOP-P-RP模式扰动方案,并基于CMA-Meso模式进行对流尺度集合预报试验,最后探究了CNOP-P关键参数影响局地对流发生、发展不同阶段的物理机理。结果显示,不同降水阶段的CNOP-P敏感参数主要与垂直扩散、云雨自动转换或其他水成物向雨滴的转换有关。与业务上常用的随机物理倾向扰动(Stochastically Perturbed Parameterization Tendencies,SPPT)方案相比,在本次降水过程中,基于CNOP-P-RP方案构造的集合预报试验具有更高的降水和地面要素的概率预报技巧,集合预报系统可靠性也占优。进一步分析发现,垂直扩散不确定性导致的山前温度梯度和地面冷池的变化在对流触发和暴雨发展中起了重要作用。7日00—04时(北京时,下同),花都强降水中心附近垂直扩散的增强使热量、动量和水汽的垂直输送加强,由此造成的雪、霰粒子融化增多是降水量增大的主要原因,说明该阶段雨滴的形成虽以云水的凝结碰并为主,但冰相粒子的作用不容忽视;7日04—08时,随着水汽输送和上升运动增强,更活跃的暖雨过程主导了增城强降水中心降水量的增多。该研究初步证明CNOP-P-RP方案在刻画对流尺度模式不确定性方面的可行性,可为华南暖区暴雨预报的改进提供一定参考。

     

  • 图 1  2017年5月6日20时起报的不同业务模式对广东地区24 h累计降水量的预报结果 (a. NCEP_GFS 50 km模式,b. ECMWF_IFS 12.5 km模式)(陈静等,2017

    Figure 1.  Forecasts of 24 h accumulated precipitation in Guangdong by different operational models initialized at 20:00 BT 6 May 2017 (a. NCEP_GFS 50 km model,b. ECMWF_IFS 12.5 km model) (Chen,et al,2017

    图 2  模式预报区域的划分

    Figure 2.  Division of model prediction area

    图 3  A阶段 (a) 和B阶段 (b) 的rio随预报时间的变化 (灰色虚线为筛选阈值1.5%)

    Figure 3.  Variations of rio at stage A (a) and stage B (b) with forecast time (the gray dotted line shows the screening threshold of 1.5%)

    图 4  A阶段4 h累计降水量观测值 (a) 和对照预报 (b),EXP1a (c) 和EXP2a (d) 中4 h累计降水的集合平均 (色阶) 和集合离散度 (实线),EXP1a集合平均相对于对照预报 (e) 和EXP2a集合平均相对于对照预报 (f) 的4 h累计降水量之差 (HD:花都,ZC:增城,单位:mm)

    Figure 4.  Observed (a) and control experiment forecast (b) of 4 h accumulated precipitation at stage A,ensemble average (shaded) and ensemble spread (solid line) of 4 h accumulated precipitation in EXP1a (c) and EXP2a (d),(e) difference in 4 h accumulated precipitation between the ensemble average of EXP1a and the control experiment,(f) difference in 4 h accumulated precipitation between the ensemble average of EXP2a and the control experiment forecast (HD:Huadu,ZC:Zengcheng,unit:mm)

    图 5  B阶段4 h累计降水量观测值 (a) 和对照预报 (b),EXP1b (c) 和EXP2b (d) 中4 h累计降水的集合平均 (色阶) 和集合离散度 (实线),EXP1b集合平均相对于对照预报 (e) 和EXP2b集合平均相对于对照预报 (f) 的4 h累计降水量之差 (单位:mm)

    Figure 5.  Observed (a) and control experiment forecast (b) of 4 h accumulated precipitation at stage B,ensemble average (shaded) and ensemble spread (solid line) of 4 h accumulated precipitation in EXP1b (c) and EXP2b (d),(e) difference in 4h accumulated precipitation between the ensemble average of EXP1b and the control experiment forecast,(f) difference in 4 h accumulated precipitation between the ensemble average of EXP2b and the control experiment forecast (unit:mm)

    图 6  集合预报试验中逐时降水的BS评分 (a. ≥0.1 mm,b. ≥1.6 mm,c. ≥7 mm,d. ≥15 mm)

    Figure 6.  BS score of hourly precipitation for ensemble prediction experiment (a. ≥0.1 mm,b. ≥1.6 mm,c. ≥7 mm,d. ≥15 mm)

    图 7  集合预报试验中连续分级概率评分 (a—c),集合预报一致性评分 (d—f) 和离群值评分 (g—h) 随预报时间的演变 (a、d、g. 2 m气温,b、e、h. 2 m湿度,c、f、i. 10 m风速)

    Figure 7.  Evolutions of continuous ranked probability score (a—c),ensemble prediction consistency score (d—f) and outlier score (g—h) with prediction time in ensemble prediction experiments (a,d,g. 2 m temperature,b,e,h. 2 m humidity,c,f,i. 10 m wind speed)

    图 8  7日00时 (a) 和02时 (b) EXP1a集合平均与对照预报的2 m气温差 (色阶,单位:10−1°C)、地面气压差 (绿线,单位:10−1 hPa) 和10 m风差值 (单位:10−1 m/s)

    Figure 8.  Differences in 2 m temperature (shaded,unit:10−1℃),surface pressure (green lines,unit:10−1 hPa) and 10 m wind (unit:10−1 m/s) between the ensemble average of EXP1a and control experiment forecast at 00:00 BT (a) and 02:00 BT 7 May (b)

    图 9  7日00时 (a) 和02时 (b) EXP1a集合平均与对照预报的边界层高度差 (色阶,单位:m) 和2 m比湿差 (黑线,单位:g/kg)

    Figure 9.  Differences in boundary layer height (shaded,unit:m) and specific humidity (black lines,unit:g/kg) between the ensemble average of EXP1a and control experiment forecast at 00:00 BT (a) and 02:00 BT 7 May (b)

    图 10  7日04时 (a) 和06时 (b) EXP1b集合平均与对照预报的2 m气温差 (色阶,单位:10−1°C)、地面气压差 (绿线,单位:10−1 hPa) 和10 m风速差 (单位:10−1 m/s)

    Figure 10.  Differences in 2 m temperature (shaded,unit:10−1℃),surface pressure (green lines,unit:10−1 hPa) and 10m wind (unit:10−1 m/s) between the ensemble average of EXP1b and control experiment forecast at 04:00 BT (a) and 06:00 BT 7 May (b)

    图 11  HP_a与LP_a (a),HP_b与LP_b (b)的温度差 ℃ (色阶,单位:℃) 和垂直速度差 (黑线,单位:10−2 m/s) 的时间高度剖面

    Figure 11.  Time-height cross sections of differences in temperature (shaded,unit:℃) and vertical velocity (black lines,unit:10−2 m/s) between HP_a and LP_a (a),HP_b and LP_b (b)

    图 12  HP_a与LP_a (a),HP_b与LP_b (b) 的水凝物混合比之差时空平均的垂直廓线 (Qr:雨,Qv:水汽,Qc:云水,Qi:云冰,Qs:雪,Qg:霰)

    Figure 12.  Spatiotemporal average vertical profiles of differences in hydrometeor mixing ratio between HP_a and LP_a (a) and between HP_b and LP_b (b)(Qr:rain,Qv:water vapor,Qc:cloud water,Qi:cloud ice,Qs:snow,Qg:graupel)

    表  1  从各参数化过程中选取的物理参数

    Table  1.   Physical parameters selected from various parameterization schemes

    物理过程序号代码名称参数名称参考值扰动范围
    边界层过程P1RLAM渐近混合长度150[30,450]
    边界层过程P2BRCR临界理查森数0.5[0.125,1]
    边界层过程P3PFAC廓线指数2[1,3]
    边界层过程P4CFAC计算近地层顶Prandtl数的比例系数7.8[3.9,15.6]
    云微物理过程P5AVTR计算雨滴下落速度的参数841.9[420,1263]
    云微物理过程P6AVTG计算霰粒子下落速度的参数330[165,495]
    云微物理过程P7AVTS计算雪粒子下落速度的参数11.72[5,18]
    云微物理过程P8N0R雨滴谱截距8×106[8×105,8×107]
    云微物理过程P9PEAUT云滴的碰并效率0.55[0.1,0.85]
    云微物理过程P10DENG霰粒子密度500[100,900]
    云微物理过程P11N0G霰粒子谱截距4×106[2×105,6×107]
    云微物理过程P12XNCR云滴数浓度3×108[1×107,1×109]
    云微物理过程P13DIMAX云冰的最大直径5×10−4[2×10−4,8×10−4]
    云微物理过程P14R0云雨自动转换的临界液滴半径8×10−6[4×10−6,1.2×10−5]
    云微物理过程P15QS0雪霰自动转换的临界混合比6×10−4[1×10−4,1×10−3]
    下载: 导出CSV

    表  2  相关云微物理参数的作用

    Table  2.   Effects of relevant cloud microphysical parameters

    序号代码名称参数名称相关的云微物理转换项
    P5AVTR计算雨滴下落速度的参数云水碰并雨;雨滴凝结/蒸发;雨滴碰并云冰增长为雪/霰;
    P6AVTG计算霰粒子下落速度的参数云水碰并霰;霰融化为雨;霰升华/凝华;霰融化并蒸发;
    P7AVTS计算雪粒子下落速度的参数云水碰并雪;雪融化为雨;雪升华/凝华;雪融化并蒸发;
    P8N0R雨滴谱截距云水碰并雨;雨撞冻霰;雨蒸发/凝结;云冰碰并雨滴增长为雪/霰;雨滴碰并云冰增长为雪/霰;雪碰并雨滴增长为霰;雨滴碰并雪增长为雪/霰;雨滴碰并霰;
    P9PEAUT云滴的碰并效率云雨自动转换;
    P10DENG霰粒子密度霰融化为雨;云冰碰并霰;云水碰并霰;雨碰并霰;霰升华/凝华;霰融化并蒸发;
    P11N0G霰粒子谱截距霰融化为雨;云冰碰并霰;云水碰并霰;雨碰并霰;霰升华/凝华;霰融化并蒸发;
    P12XNCR云滴数浓度云雨自动转换;云水异质冻结核化;
    P13DIMAX云冰的最大直径云冰碰并雨增长为雪/霰;云冰碰并雪;云冰碰并霰;云冰升华/凝华;冰雪自动转换;
    P14R0云雨自动转换的临界液滴半径云雨自动转换;
    P15QS0雪霰自动转换的临界混合比雪霰自动转换;
    下载: 导出CSV

    表  3  模式积分时间的设置

    Table  3.   Setting of mode integration time

    降水阶段起报时间研究时段
    A阶段2017年5月6日20时2017年5月7日00—04时
    B阶段2017年5月6日20时2017年5月7日04—08时
    下载: 导出CSV

    表  4  A阶段的CNOP-P求解结果

    Table  4.   CNOP-P solution results at stage A

    迭代步数CNOP-P对应的参数敏感性排序目标函数谱投影梯度
    0P2 P13 P10 P8 P4 P11 P1 P7 P14 P3 P15 P6 P12 P5 P9−363789.865.14×10−1
    1P1 P5 P8 P6 P14 P12 P9 P11 P13 P15 P2 P7 P10 P4 P3−1890936.431.05×10
    2P1 P5 P8 P6 P7 P12 P14 P9 P2 P3 P10 P11 P4 P13 P15−2428671.822.37×10−2
    3P1 P6 P12 P7 P5 P8 P9 P14 P2 P10 P3 P13 P4 P11 P15−2444782.845.747×10−4
    4P1 P6 P7 P12 P8 P9 P14 P2 P10 P5 P3 P4 P13 P11 P15−2396353.531.05×10−5
    5P1 P6 P7 P12 P9 P8 P14 P10 P2 P5 P13 P3 P4 P11 P15−2412798.595.95×10−6
    6P1 P6 P7 P12 P9 P8 P14 P10 P2 P5 P3 P13 P4 P11 P15−2407900.108.83×10−6
    7P1 P6 P7 P12 P9 P8 P14 P10 P2 P5 P3 P13 P4 P11 P15−2364014.093.32×10−6
    8P1 P6 P7 P12 P9 P8 P14 P2 P10 P5 P3 P13 P4 P11 P15−2377794.966.63×10−6
    9P1 P6 P7 P12 P9 P8 P14 P2 P10 P5 P3 P13 P4 P11 P15−2369254.156.74×10−6
    10P1 P6 P7 P12 P9 P8 P14 P2 P10 P5 P3 P13 P4 P11 P15−2388536.836.16×10−6
    下载: 导出CSV

    表  5  B阶段的CNOP-P求解结果

    Table  5.   CNOP-P solution results at stage B

    迭代步数CNOP-P对应的参数敏感性排序目标函数谱投影梯度
    0P3 P2 P8 P1 P7 P13 P4 P9 P5 P10 P11 P15 P14 P12 P6−280918.014.48×10−1
    1P6 P5 P14 P1 P8 P7 P9 P12 P2 P15 P10 P13 P11 P4 P3−633662.631.87×10−2
    2P6 P5 P14 P1 P8 P7 P12 P9 P13 P10 P15 P3 P11 P2 P4−669609.183.12×10−4
    3P5 P6 P14 P1 P8 P7 P9 P12 P10 P13 P15 P11 P3 P2 P4−687939.931.44×10−4
    4P5 P6 P14 P1 P8 P7 P12 P9 P10 P13 P15 P3 P11 P2 P4−683710.552.39×10−4
    5P5 P6 P14 P1 P8 P7 P9 P12 P10 P13 P15 P3 P11 P2 P4−686132.896.26×10−5
    6P5 P6 P14 P1 P8 P7 P9 P12 P10 P13 P15 P3 P11 P2 P4−692323.125.79×10−5
    7P5 P6 P14 P1 P8 P7 P9 P12 P10 P13 P15 P3 P11 P2 P4−677959.371.37×10−4
    8P5 P6 P14 P1 P8 P7 P9 P12 P10 P13 P15 P3 P11 P2 P4−680330.138.11×10−5
    9P5 P6 P14 P1 P8 P7 P9 P12 P10 P13 P15 P3 P11 P2 P4−683884.211.36×10−5
    10P5 P6 P14 P1 P8 P7 P9 P12 P10 P13 P15 P3 P11 P2 P4−687757.991.80×10−5
    下载: 导出CSV

    表  6  确定关键参数个数的对比试验设置

    Table  6.   Settings of comparative experiments to determine the number of key parameters

    试验序号降水阶段扰动参数个数扰动参数序号
    EXPa_2A阶段2P1 P6
    EXPa_4A阶段4P1 P6 P7 P12
    EXPa_6A阶段6P1 P6 P7 P12 P9 P8
    EXPa_8A阶段8P1 P6 P7 P12 P9 P8 P14 P2
    EXPa_10A阶段10P1 P6 P7 P12 P9 P8 P14 P2 P10 P5
    EXPa_12A阶段12P1 P6 P7 P12 P9 P8 P14 P2 P10 P5 P3 P13
    EXPa_15A阶段15P1 P6 P7 P12 P9 P8 P14 P2 P10 P5 P3 P13 P4 P11 P15
    EXPb_2B阶段2P6 P5
    EXPb_4B阶段4P6 P5 P14 P1
    EXPb_6B阶段6P6 P5 P14 P1 P8 P7
    EXPb_8B阶段8P6 P5 P14 P1 P8 P7 P9 P12
    EXPb_10B阶段10P6 P5 P14 P1 P8 P7 P9 P12 P10 P13
    EXPb_12B阶段12P6 P5 P14 P1 P8 P7 P9 P12 P10 P13 P15 P11
    EXPb_15B阶段15P6 P5 P14 P1 P8 P7 P9 P12 P10 P13 P15 P11 P3 P2 P4
    下载: 导出CSV

    表  7  对流尺度集合预报试验设置

    Table  7.   Settings of convective scale ensemble prediction experiments

    试验序号降水阶段模式扰动方案扰动参数序号
    EXP1aA阶段CNOP-P-RPP1 P6 P7 P12 P9 P8 P14 P2
    EXP1bB阶段CNOP-P-RPP6 P5 P14 P1 P8 P7 P9 P12
    EXP2aA阶段SPPT/
    EXP2bB阶段SPPT/
    下载: 导出CSV

    表  8  强降水中心4 h累计降水量对比 (单位:mm)

    Table  8.   Comparison of 4 h cumulative precipitation at heavy precipitation center (unit:mm)

    降水阶段观测值对照预报集合平均强降水成员均值弱降水成员均值
    A97.256.663.180.834.8
    B63.318.045.397.516.5
    下载: 导出CSV
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  • 收稿日期:  2022-03-17
  • 录用日期:  2022-12-20
  • 修回日期:  2022-07-15
  • 网络出版日期:  2022-08-01

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