CMA-BJ 2.0版逐时快速更新追赶循环同化预报系统研发及应用Ⅰ：资料同化及系统构建

陈敏; 仲跻芹; 卢冰; 童文雪; 冯琎; 张舒婷; 黄向宇; 范水勇

doi:10.11676/qxxb2023.20220172

CMA-BJ 2.0版逐时快速更新追赶循环同化预报系统研发及应用Ⅰ：资料同化及系统构建

doi: 10.11676/qxxb2023.20220172

1.
北京城市气象研究院，北京，100089
2.
中国气象局城市气象重点开放实验室，北京，100089

基金项目: 国家重点研发计划课题（2022YFC3004003、2018YFC1506804）、中国气象局重点创新团队（CMA2022ZD09）。

详细信息

作者简介:
陈敏，主要从事资料同化、数值预报业务系统研发。E-mail：mchen@ium.cn

中图分类号: P456.7
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- 文章访问数: 132
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- 被引次数: 0
出版历程
- 收稿日期: 2022-10-27
- 修回日期: 2023-06-25
- 网络出版日期: 2023-06-27

CMA-BJ v2.0 hourly rapid update catch-up cycling assimilation and forecast system, Part Ⅰ: Data assimilation and system overview

1.
Institute of Urban Meteorology，CMA，Beijing 100089，China
2.
Key Laboratory of Urban Meteorology，China Meteorological Administration，Beijing 100089，China

摘要

摘要: 介绍了CMA-BJ 2.0版区域逐时快速更新循环同化分析及短时预报业务系统在逐时更新循环和资料同化方面的关键技术特点。该系统采用分析增量更新作为初始化方案，有效抑制了初始噪声累积问题；通过充分考虑各类观测资料实际到报截断时长的差异，发展了包括循环分析和更新预报两个部分耦合的逐时追赶循环运行框架，实现了对各类观测资料充分高效的利用，也较好地兼顾了短临预报服务对逐时更新循环预报产品的时效性要求；通过在分析循环的同化背景场部分应用动态混合方案，实现了全球模式大尺度场对区域模式中小尺度热动力场发展的动态约束，有效抑制了快速更新循环预报误差累积导致的大尺度预报场变形的问题；在资料同化方面，实现了中国全国雷达反射率因子拼图资料的同化应用，并通过仅在更新预报部分开展雷达反射率资料同化以规避连续循环同化造成的水汽正向过量累积、调整雷达同化时的背景场误差的方差和长度尺度两方面的策略优化有效提升了雷达同化的应用效果；此外，在CMA-BJ 2.0版系统中实现了中国全国风廓线雷达观测资料的实时同化应用。
- 快速更新循环 /
- 初始化 /
- 雷达资料同化 /
- 风廓线同化 /
- 分析增量更新
Abstract: In this paper, the key technical features of CMA-BJ v2.0, the Hourly Rapid Catch-up Cycling Assimilation and Forecast System, are introduced in detail. This system uses IAU (Incremental Analysis Update) as the initialization scheme, which effectively suppresses the initial noise accumulation problem. By fully considering the actual truncated time of all kinds of observations' arrival, the two coupling parts, e.g., the cycle analysis and forecast update implementing data with different cut-off times, run in turn within each hourly cycling to meet the high demands of nowcasting and short-term forecast services. By applying the dynamic forecast hybrid scheme to the assimilated background field, the dynamic constraint of large-scale fields from global models on the development of micro- and meso-scale thermal and dynamic fields in the regional model is realized, and the deformation of large-scale prediction fields caused by the accumulation of rapid update cycle prediction errors is effectively suppressed. In terms of data assimilation, the national-wide mosaic radar reflectivity is only assimilated at the stage of forecast update to avoid continuous accumulation of water vapor. The radar assimilation background field error variance and length scale strategy optimization effectively promote the application of radar assimilation effect. In addition, real-time assimilation of national wind profile radar observations is realized in the CMA-BJ v2.0 system.
- Rapid updated cycling /
- Initialization /
- Radar data assimilation /
- Wind profile data assimilation /
- Incremental analysis update

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图 1 CMA-BJ 2.0版系统预报区域（D01为9 km分辨率，D02为3 km分辨率；色阶为地形高度，单位：m）

Figure 1. Forecast domains of the CMA-BJ v2.0 system（D01：9 km，D02：3 km；the shadow is the altitude，unit：m ）

下载: 全尺寸图片幻灯片

图 2 各类GTS观测资料不同截断时间到报情况

Figure 2. Data arrival reporting of various GTS observations at different cut-off times

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图 3 逐时快速更新追赶循环运行时间线

Figure 3. The running timeline of the hourly catch-up cycle

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图 4 CMA-BJ 2.0版系统的循环分析和更新预报流程（内圈黑色框内数字为循环分析起报时间，黑色虚线指示该次循环分析的启动时间；外圈蓝色框内为更新预报起报时间，蓝色虚线指示该次更新预报的启动时间；红色实线表示箭头所指的运行时次以箭尾所指的运行时次的1 h预报为背景场）

Figure 4. Flowchart of cycle analysis and forecast update of the CMA-BJ v2.0 system （the number in the black box in the inner circle is the start time of the cycle analysis，and the black dotted line indicates the start time of cycle analysis；the blue box indicates the start time of forecast update and the blue dashed line indicates the start time of forecast update；the solid red line indicates the running time denoted by the arrow，and the 1-hour forecast of the running time used as the background field is denoted by the arrow tail）

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图 5 CMA-BJ 2.0版同化应用的观测及其分布（a. 常规地面（红点）、高空（蓝点）、飞机报（绿点）、浮标（橙点）和船舶（粉点），b. 地基GNSS/ZTD，c. 天气雷达，d. 风廓线雷达）

Figure 5. Observations assimilated by the CMA-BJ v2.0 system （a. SYNOP （red），TEMP （blue），AMDAR （green），BUOY （orange），and SHIP （pink），b. Ground-based GNSS/ZTD，c. Weather radar，d. Wind profiler radar）

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图 6 2019 年1月1—31日12时起报预报的不同高度温度（a、d，单位：K）、比湿（b、e，单位：kg/kg）和风速（c、f，单位：m/s）平均偏差（BIAS）和均方根误差（RMSE）评分对比（黑线：对照试验，红线：DFB试验）（a—c. 12 h预报，d—f. 24 h预报）

Figure 6. Upper air temperature （a，d，unit：K），specific humidity （b，e，unit：kg/kg） and wind speed （c，f，unit： m/s） scores of forecasts initialized at 12:00 UTC in January 2019 （black line：CTL，red line：DFB）（a—c. 12 h forecasts，d—f. 24 h forecasts）

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图 7 2019年6月4日09—12时、12—15时3 h累积降水观测（a、d）和试验RadarC （b、e）、RadarS （c、f）于4日09时开始0—3 h （b、c）和3—6 h （e、f）的3 h累积降水预报

Figure 7. 3-h accumulated precipitation valid during 09:00—12:00 UTC 4 June 2019 （a，d. observations，b，e. RadarC，c，f. RadarS；b，c are the 0—3 h forecasts，e，f are the 3—6 h forecasts）

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图 8 2019年6—8月CMA-BJ 2.0版系统9 km分辨率逐3 h累积降水预报的客观检验评分（a. TS， b. BIAS）

Figure 8. 3-hour accumulative precipitation forecast scores of CMA-BJ v2.0 verified against rain gauge observations in the 9 km domain from June to August 2019 （a. TS，b. BIAS）

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图 9 风廓线观测资料质量控制流程

Figure 9. Quality control process of wind profile observation data

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图 10 2018年6月10日00时—2018年7月1日00时经过质量控制后的风廓线观测进入同化应用的记录数和u、v同化吸收率

Figure 10. Record number and u，v assimilation absorption rate of wind profiler observations entering the assimilation after quality control from 00:00 UTC 10 June to 00:00 UTC 1 July 2018

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表 1 CMA-BJ 2.0版主要设置

Table 1. Configuration of the CMA-BJ v2.0

系统设置	模式版本	WRF/ARW v4.1.2
	预报区域中心点	35°N，110°E
	网格点数	D01：649×500；D02：550×424
	网格距	D01：9 km；D02：3 km
	垂直层数/模式层顶	59/10 hPa
	更新频次	1 h
	侧边界条件	ECMWF全球预报
	预报时长	24 h/96 h（北京时08,、12时起报）
物理方案	辐射方案	RRTMG v3.6 （Iacono，et al，2008）
	边界层方案	YSU
	对流参数化方案	New Tiedtke（仅9 km区域）
	云微物理方案	Thompson
	陆面过程	Noah LSM
资料同化	资料同化模块及版本	WRFDA v4.1.2
	同化方法	3DVar
	控制变量	风分量（u、v），温度（T），假相对湿度（RH_s），地面气压（P_s ）
	同化资料	地面、探空、小球测风、飞机报、风廓线雷达、GNSS天顶总延迟、天气雷达反射率和径向风
	初始化方案	分析增量更新（IAU）

下载: 导出CSV

表 2 雷达资料同化策略

Table 2. The radar data assimilation strategy

试验方案	是否循环同化	雷达同化的背景场误差尺度因子
RadarC	是，在循环分析步骤连续同化雷达	Var_scaling=0.5 Len_scaling=0.5
RadarS	否，仅在更新预报步骤同化雷达	Var_scaling=1.0 Len_scaling=0.25

下载: 导出CSV

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