GRAPES Hybrid-3DVar对台风苏迪罗的数值试验

庄照荣; 李兴良; 陈静; 孙健

doi:10.3878/j.issn.1006-9895.1911.19193

GRAPES Hybrid-3DVar对台风苏迪罗的数值试验

doi: 10.3878/j.issn.1006-9895.1911.19193

庄照荣^{1, 2,},
李兴良^{1, 2, ,},
陈静^{1, 2},
孙健^{1, 2}

1.
国家气象中心，北京 100081
2.
中国气象局数值预报中心，北京 100081

基金项目: 国家重点研发计划项目2017YFA0603901、2018YFC1507502、2017YFC1502001

详细信息

作者简介:
庄照荣，女，1978年出生，博士研究生，主要从事资料同化研究，E-mail: zhuangzr@126.com

通讯作者:
李兴良，E-mail: lixliang@cma.gov.cn

中图分类号: P435
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- 文章访问数: 233
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- 被引次数: 0
出版历程
- 收稿日期: 2019-07-26
- 网络出版日期: 2020-04-27
- 刊出日期: 2020-10-20

Experiments on Simulation of Typhoon Soudelor with GRAPES Hybrid-3DVar System

Zhaorong ZHUANG^{1, 2
,},
Xingliang LI^{1, 2
, ,},
Jing CHEN^{1, 2},
Jian SUN^{1, 2}

1.
National Meteorological Center, Beijing 100081
2.
Numerical Weather Prediction Center of China Meteorological Administration, Beijing 100081

Funds: National Key Research and Development Program of China (Grants 2017YFA0603901, 2018YFC1507502, 2017YFC1502001)

摘要

摘要: 为了把反映天气形势变化的背景误差协方差引入到变分分析系统中来提高分析质量，本文在GRAPES区域三维变分框架的基础上通过扩展控制变量方法实现动态与静态背景误差协方差耦合，建立混合三维变分分析系统（GRAPES Hybrid-3DVar）。通过控制变量扰动产生的集合样本进行单点观测分析试验验证Hybrid-3DVar及其局地化方案的合理性，并针对台风苏迪罗进行实际观测资料同化和数值预报试验，结果表明：用集合样本描述的背景误差协方差是随着天气流型变化的，动力场和质量场的离散度在台风中心处最大，因而混合同化的分析增量包含更多细微结构和中小尺度信息；其分析和24 h内预报要素质量优于3DVar，24 h内降水强度和落区预报也更准确，混合同化分析改善了3DVar分析的降水空报问题;同时混合同化分析的24 h内台风路径预报也最接近实况，台风强度预报在48 h之内都比3DVar更接近观测。
- Hybrid-3DVar /
- 3DVar /
- GRAPES /
- 局地化 /
- 台风苏迪罗
Abstract: To improve the analysis quality by incorporating the flow-dependent ensemble covariance into the variational data assimilation system, the new GRAPES (global/regional assimilation and prediction system) hybrid-3Dvar system was built. The new system is based on the GRAPES regional 3DVar system, which uses the statistic covariance, and was built by augmenting the state vectors with another set of control variables preconditioned upon the ensemble dynamic covariance. The new hybrid-3DVar system and the localization method were verified through a single-observation assimilation experiment with ensemble samples produced by the 3D-Var’s control variable perturbation method. The real observation assimilation and forecast experiment for Typhoon Soudelor yielded the following conclusions: (1) The background covariance, which is represented by ensemble samples, is flow-dependent, and the root mean square spread in the ensemble of momentum field and mass field is largest near the typhoon center. (2) The analysis increments of the new hybrid-3DVar have a more detailed structure and more medium- and small-scale information. (3) The analysis and 24 h prediction qualities of model variables in the new hybrid-3DVar are significantly improved compared with the 3DVar system, and the precipitation position predictions are more accurate. (4) The 24 h forecast track of Typhoon Soudelor is closer to the observational one, and the 48 h-predicted intensity also approaches the real observation.
- Hybrid-3DVar /
- 3DVar /
- GRAPES /
- Localization /
- Typhoon Soudelor

HTML全文

图 1 三组理想实验单点气压观测的无量纲气压（PI；左列）、纬向风场分量（U，单位：m s^‒1；中间列）、经向风场分量（V，单位：m s^‒1；右列）的水平分析增量：（a1–a3）三维变分试验（3DVar）；（b1–b3）背景误差采用全动态的混合分析试验（Hybrid_NoVertloc）；（c1–c3）采用垂直相关的局地化方案的混合分析试验（Hybrid_Vertloc）

Figure 1. Non-dimensional pressure (PI; left column), U-component (U, units: m s^‒1, middle column), V-component (V, units: m s^‒1, right column) of horizontal analysis increments with one pressure observation of three ideal experiments: （a1–a3）3DVar; （b1–b3） full hybrid without vertical localization; （c1–c3）hybrid with vertical localization

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图 2 同图1，但为垂直分析增量

Figure 2. Same as Fig. 1, but for the vertical analysis increments

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图 3 第20层95°E剖面处的（a）无量纲气压分析增量随纬度的变化、（b）格点（40°N，95°E）处的无量纲气压分析增量随高度的变化

Figure 3. Non-dimensional pressure analysis increments changed with latitude at 95°E section on level 20; (b) Non-dimensional pressure analysis increments changed with height at point of (40°N, 95°E)

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图 4 第23层观察点A（黑点所示）与其他格点的（a）无量纲气压PI、（b）比湿Q、（c）U和（d）V风场的水平相关系数（填色）及背景风场（矢量箭头）分布

Figure 4. Horizontal correlation fields (shaded) with respect to point A (black dot) for (a) PI, (b) specific humidity Q, (c) U, (d) V and background wind field (vector arrow) on level 23

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图 5 观察点A（黑点所示）与其他格点在剖面26°N处的（a）PI、（b）Q（单位：kg kg^‒1）、（c）U（单位：m s^‒1）和（d）V（单位：m s^‒1）的离散度（廓线）以及垂直相关系数（填色）的垂直分布

Figure 5. Vertical correlation (shaded) and ensemble spread (contours) with respect to point A (black dot) at 26°N section for (a) PI, (b) Q (units: kg kg^‒1), (c) U (units: m s^‒1), and (d) V (units: m s^‒1)

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图 6 3DVar试验第10层模式面的分析增量分布：（a）PI；（b）Q（单位：kg kg^‒1）；（c）U（单位：m s^‒1）；（d）V（单位：m s^‒1）。图中黑点为台风中心位置，矢量箭头为背景风场。

Figure 6. Horizontal analysis increments of 3DVar on level 10: (a) PI, (b) Q (units: kg kg^‒1), (c) U (units: m s^‒1), and (d) V (units: m s^‒1). Black dot is location of super typhoon Soudelor, vector arrow is background wind field

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图 7 同图6，但为Hybrid试验

Figure 7. Same as Fig. 6, but for hybrid test

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图 17 2015年8月8日12:00至10日12:00 3DVar与Hybrid试验苏迪罗台风的强度预报以及实况观测

Figure 17. Intensity forecast of super typhoon Soudelor of 3DVar and hybrid test, observation intensity from 1200 UTC 8 to 1200 UTC 10 August

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图 8 925 hPa 3DVar与Hybrid分析的绝对误差差别（填色）（a）PI；（b）Q（单位：kg kg^‒1）；（c）U（单位：m s^‒1）；（d）V（单位：m s^‒1）。图中黑点为台风中心位置, 矢量箭头为背景风场

Figure 8. Differences in absolute errors between the analysis of 3DVar and hybrid (shaded) (a) PI, (b) Q (units: kg kg^‒1), (c) U (units: m s^‒1), and (d) V (units: m s^‒1). Black dot is location of super typhoon Soudelor, vector arrow is background wind field

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图 10 3DVar（3dv）与Hybrid（HF）试验的各要素分析偏差与均方根误差：（a）位势高度（H,单位：gpm）；（b）Q（单位：g kg^‒1）；（c）U （单位：m s^‒1）；（d）V（单位：m s^‒1）

Figure 10. Bias and root mean square error of analyses (a) geopotential height (H,units: gpm), (b) Q (units: g kg^‒1), (c) U (units: m s^‒1), and (d) V (units: m s^‒1) with the 3DVar/hybrid test

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图 9 3DVar和Hybrid试验第10层模式面（a）PI、（b）Q、（c）U和（d）V分析增量的谱密度（单位：m³ s^‒2）随波长的变化

Figure 9. Variation in the spectral density of analysis increment in 3DVar and Hybrid test for (a) PI, (b)Q, (c) U and (d) V changed with wavelength on level 10 (units: m³ s^‒2)

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图 11 同图10，但为12 h预报

Figure 11. Same as Fig. 10, but for 12-h forecast

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图 12 同图10，但为24 h预报

Figure 12. Same as Fig. 10, but for 24-h forecast

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图 13 2015年8月（a‒c）8日12:00～18:00和（d‒f）8日18:00至9日00:00的累积降水量（单位：mm）分布：（a、d）实况观测；（b、e）3DVar预报结果；（c、f）Hybrid预报结果

Figure 13. The distribution of accumulated precipitation (a‒c) f from 1200 UTC to 1800 UTC 8 August and (d‒f) from 1800 UTC 8 to 0000 UTC 9 August, 2015: (a, d) Observation; (b, e) 3DVar forecast; (c, f) hybrid forecast

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图 14 2015年8月9日（a‒c）00:00～06:00和（d‒f）9日06:00～12:00的累积降水量（单位：mm）分布：（a、d）实况观测；（b、e）3DVar预报结果；（c、f）Hybrid预报结果

Figure 14. The distribution of accumulated precipitation (a‒c) from 0000 UTC to 0600 UTC and (d‒f) from 0600 UTC to 1200 UTC 9 August, 2015: (a, d) Observation; (b, e) 3DVar forecast; (c, f) hybrid forecast

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图 15 2015年8月8日12:00至10日12:00苏迪罗台风的路径。图中日期为时/日

Figure 15. Track of super typhoon Soudelor from 1200 UTC 8 to 1200 UTC 10 August, 2015. Date showed in picture as hour/day

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图 16 2015年8月8日12:00至10日12:00 3DVar与Hybrid试验预报的台风路径误差

Figure 16. Track errors of 3DVar and hybrid test from 1200 UTC 8 to 1200 UTC 10 August

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