留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

气候动力诊断和分析系统设计与应用

张正秋 祝从文 苏京志 刘伯奇 蒋宁 陈昊明

张正秋, 祝从文, 苏京志, 等. 气候动力诊断和分析系统设计与应用. 应用气象学报, 2021, 32(5): 542-552. DOI:  10.11898/1001-7313.20210503..
引用本文: 张正秋, 祝从文, 苏京志, 等. 气候动力诊断和分析系统设计与应用. 应用气象学报, 2021, 32(5): 542-552. DOI:  10.11898/1001-7313.20210503.
Zhang Zhengqiu, Zhu Congwen, Su Jingzhi, et al. Designing and implementation of Climate Dynamic Diagnosis and Analysis System. J Appl Meteor Sci, 2021, 32(5): 542-552. DOI:  10.11898/1001-7313.20210503.
Citation: Zhang Zhengqiu, Zhu Congwen, Su Jingzhi, et al. Designing and implementation of Climate Dynamic Diagnosis and Analysis System. J Appl Meteor Sci, 2021, 32(5): 542-552. DOI:  10.11898/1001-7313.20210503.

气候动力诊断和分析系统设计与应用

DOI: 10.11898/1001-7313.20210503
资助项目: 

国家自然科学基金项目 41830969

公益性行业(气象)科研专项 GYHY201406019

中国气象科学研究院基本科研业务专项 2021Z04

详细信息
    通信作者:

    祝从文, 邮箱: zhucw@cma.gov.cn

Designing and Implementation of Climate Dynamic Diagnosis and Analysis System

  • 摘要: 气候动力诊断和数值模拟是认识气候变化规律、提高短期气候预测与科学决策服务水平的重要手段。但基于气候模拟的动力诊断技术在气候预测业务中还未得到广泛应用,缺乏支撑科研成果转化为业务应用的中试平台。为此,通过集成多种现代计算机通信协议、可视化编辑和气象数值计算等技术,研发可视化交互气候动力诊断和分析系统(Climate Dynamic Diagnosis and Analysis System,CDDAS),以促进气候模拟的动力诊断技术在气候业务中的广泛应用。该系统具有结构开放、诊断方法集成度高、方便易用等特点,包括数据更新备份、气候动力诊断、多模式数值模拟、结果分析4个功能模块,并设计了一种远程交互控制脚本语言,为用户二次开发提供语言环境,可实现本地客户端、服务器端和超级计算机三者交互通信控制可视化管理。该系统使用便捷,目前已在国家级业务和科研单位获得应用,在气候异常成因分析、气候预测和气候决策服务中可显著提高工作效率。
  • 图  1  系统架构和模块

    Fig. 1  System structure and modules

    图  2  大气动力和热力诊断交互界面

    Fig. 2  Interface of atmospheric dynamic and thermal diagnosis

    图  3  多试验区域选择设置对话框

    Fig. 3  Multiple experimental area selection settings

    图  4  用于显示数值模拟结果的远程交互对话页面

    Fig. 4  Remote interactive dialogue page for displaying numerical modeling results

    图  5  数值模式动力诊断流程

    Fig. 5  Flow of numerical model dynamic diagnosis

    图  6  可视化交互界面编辑窗口

    ①控制工具栏  ②交互页面略图  ③当前编辑脚本控件略图  ④交互页面编辑窗口  ⑤脚本编辑窗口  ⑥可视化工具窗口  ⑦控件标识窗口

    Fig. 6  Windows for visual interface editing

    图  7  交互系统搭建流程

    Fig. 7  Interactive system of building process

    图  8  CDDAS系统客户端

    ①图像管理窗口  ②交互界面窗口  ③图形显示窗口  ④区域选择窗口

    Fig. 8  CDDAS client

    图  9  2018年7月北大西洋海温异常

    Fig. 9  Sea surface temperature anomalies in the North Atlantic during Jul 2018

    图  10  2018年5—7月北大西洋海温异常强迫下大气环流模式(ECHAM5)模拟的7月2 m气温异常(a)和200 hPa位势高度场异常(b)

    Fig. 10  Temperature anomalies of 2 m(a) and geopotential height anomalies of 200 hPa(b) in Jul 2018 simulated by ECHAM5 with the forcing of sea surface temperature anomalies in the North Atlantic from May to Jul in 2018

  • [1] 魏凤英.气候统计诊断与预测方法研究进展——纪念中国气象科学研究院成立50周年.应用气象学报, 2006, 17(6):736-742. doi:  10.3969/j.issn.1001-7313.2006.06.011

    Wei F Y. Progresses on climatological statistical diagnosis and prediction methods-In commemoration of the 50 anniversaries of CAMS establishment. J Appl Meteor Sci, 2006, 17(6): 736-742. doi:  10.3969/j.issn.1001-7313.2006.06.011
    [2] 李清泉, 孙丞虎, 袁媛, 等. 近20年我国气候监测诊断业务技术的主要进展. 应用气象学报, 2013, 24(6): 666-676. doi:  10.3969/j.issn.1001-7313.2013.06.003

    Li Q Q, Sun C H, Yuan Y, et al. Major advances of China climate monitoring and diagnosis operation in recent 20 years. J Appl Meteor Sci, 2013, 24(6): 666-676. doi:  10.3969/j.issn.1001-7313.2013.06.003
    [3] 陈丽娟, 赵俊虎, 顾薇, 等. 汛期我国主要雨季进程成因及预测应用进展. 应用气象学报, 2019, 30(4): 385-400. doi:  10.11898/1001-7313.20190401

    Chen L J, Zhao J H, Gu W, et al. Advances of research and application on major rainy seasons in China. J Appl Meteor Sci, 2019, 30(4): 385-400. doi:  10.11898/1001-7313.20190401
    [4] Jiang N, Zhu C. Asymmetric changes of ENSO diversity modulated by the cold tongue mode under recent global warming. Geophys Res Lett, 2018. DOI:  10.1029/2018GL079494.
    [5] Guo L, Zhu C, Liu B. Possible causes of the flooding over south China during the 2015/2016 winter. Int J Climatol, 2019, 39: 3218-3230. doi:  10.1002/joc.6013
    [6] Yu M, Zhu C, Jiang N. Subseasonal mode of cold and wet climate in South China during the cold season: A climatological view. Atmos Oceanic Sci Lett, 2019. DOI:  10.1080/16742834.2019.1568164.
    [7] 祝从文, 刘伯奇, 左志燕, 等. 东亚夏季风次季节变化研究进展. 应用气象学报, 2019, 30(4): 401-415. doi:  10.11898/1001-7313.20190402

    Zhu C W, Liu B Q, Zuo Z Y, et al. Recent advances on sub-seasonal variability of East Asian summer monsoon. J Appl Meteor Sci, 2019, 30(4): 401-415. doi:  10.11898/1001-7313.20190402
    [8] Sonuc E, Sen B. Verifying regional climate model results with web-based expert-system. Procedia Technology, 2012, 1: 24-30. doi:  10.1016/j.protcy.2012.02.007
    [9] Mehrotra R, Johnson F, Sharma A. A software toolkit for correcting systematic biases in climate model simulations. Environmental Modelling and Software, 2018, 104: 130-152. doi:  10.1016/j.envsoft.2018.02.010
    [10] 宋艳玲, 王建林, 田靳峰, 等. 气象干旱指数在东北春玉米干旱监测中的改进. 应用气象学报, 2019, 30(1): 25-34. doi:  10.11898/1001-7313.20190103

    Song Y L, Wang J L, Tian J F, et al. The spring maize drought index in Northeast China based on meteorological drought index. J Appl Meteor Sci, 2019, 30(1): 25-34. doi:  10.11898/1001-7313.20190103
    [11] 伍红雨, 邹燕, 刘尉. 广东区域性暴雨过程的定量化评估及气候特征. 应用气象学报, 2019, 30(2): 233-244. doi:  10.11898/1001-7313.20190210

    Wu H Y, Zou Y, Liu W. Quantitative assessment of regional heavy rainfall process in Guangdong and its climatological characteristics. J Appl Meteor Sci, 2019, 30(2): 233-244. doi:  10.11898/1001-7313.20190210
    [12] 刘伯奇, 祝从文. 中国夏季降水预测因子潜在技巧分布图及应用. 应用气象学报, 2020, 31(5): 570-582. doi:  10.11898/1001-7313.20200505

    Liu B Q, Zhu C W. Potential skill map of predictors applied to the seasonal forecast of summer rainfall in China. J Appl Meteor Sci, 2020, 31(5): 570-582. doi:  10.11898/1001-7313.20200505
    [13] 危国飞, 刘会军, 吴启树, 等. 多模式降水分级最优化权重集成预报技术. 应用气象学报, 2020, 31(6): 668-680. doi:  10.11898/1001-7313.20200603

    Wei G F, Liu H J, Wu Q S, et al. Multi-model consensus forecasting technology with optimal weight for precipitation intensity levels. J Appl Meteor Sci, 2020, 31(6): 668-680. doi:  10.11898/1001-7313.20200603
    [14] Kieran Healy. Data Visualization: A Practical Introduction. Princeton: Princeton University Press, 2019.
    [15] 韦青, 李伟, 彭颂, 等. 国家级天气预报检验分析系统建设与应用. 应用气象学报, 2019, 30(2): 245-256. doi:  10.11898/1001-7313.20190211

    Wei Q, Li W, Peng S, et al. Development and application of national verification system in CMA. J Appl Meteor Sci, 2019, 30(2): 245-256. doi:  10.11898/1001-7313.20190211
    [16] 吴门新, 庄立伟, 侯英雨, 等. 中国农业气象业务系统(CAgMSS)设计与实现. 应用气象学报, 2019, 30(5): 513-527. doi:  10.11898/1001-7313.20190501

    Wu M X, Zhuang L W, Hou Y Y, et al. The design and implementation of China agricultural meteorological service system(CAgMSS). J Appl Meteor Sci, 2019, 30(5): 513-527. doi:  10.11898/1001-7313.20190501
    [17] 李德泉, 李抗抗, 李宏宇, 等. 飞机作业监测移动应用系统的设计与实现. 应用气象学报, 2019, 30(6): 745-758. doi:  10.11898/1001-7313.20190610

    Li D Q, Li K K, Li H Y, et al. Design and implementation of mobile application for real-time monitoring of weather-modification aircraft operations. J Appl Meteor Sci, 2019, 30(6): 745-758. doi:  10.11898/1001-7313.20190610
    [18] 王旻燕, 姚爽, 姜立鹏, 等. 我国全球大气再分析(CRA-40)卫星遥感资料的收集和预处理. 气象科技进展, 2018, 8(1): 158-163. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKZ201801038.htm

    Wang M Y, Yao S, Jiang L P, et al. Collection and pre-processing of satellite remote sensing data in CRA-40(CMA's Global Atmospheric ReAnalysis). Advances in Meteorological Science and Technology, 2018, 8(1): 158-163. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKZ201801038.htm
    [19] Wu T, Yu R, Zhang F, et al. The Beijing Climate Center atmospheric general circulation model: Description and its performance for the present-day climate. Climate Dyn, 2010, 34: 123-147. doi:  10.1007/s00382-008-0487-2
    [20] Roeckner E. The Atmospheric General Circulation Model ECH-AM5. Part 1: Model Description. Report No. 349, Max-Planck-Institute für Meteorologie, 2003: 1-127.
    [21] Eaton B. User's Guide to the Community Atmosphere Model CAM-5.0. NCAR, 2020.
    [22] Borse G J. Numerical Methods with MATLAB. Boston: PWS Publishing Company, 1997.
    [23] Tsai P, Doty B E. A Prototype Java Interface for the Grid Analysis and Display System (GrADS). Fourteenth International Conference on Interactive Information and Processing Systems, 1998.
    [24] NCAR. The NCAR Command Language (Version 6.6.2). Colorado: UCAR/NCAR/CISL/TDD, 2019.
    [25] Chun W J. Core Python Applications Programming(Third Edition). Upper Saddle River, New Jersey 07458: Pear Education, Inc, 2012.
    [26] 张正秋, 祝从文, 苏京志. 气象应用可视化远程交互系统使用指南. 北京: 气象出版社, 2018.

    Zhang Z Q, Zhu C W, Su J Z. A Guide to the Use of Visual Remote Interactive Platform for Meteorological Applications. Beijing: China Meteorological Press, 2018.
    [27] 刘伯奇, 苏京志, 马双梅, 等. 2018年夏季我国华北持续性高温的成因和未来趋势展望//2018年全国优秀决策气象服务材料汇编. 北京: 气象出版社, 2019: 48-49.

    Liu B Q, Su J Z, Ma S M, et al. Causes and Future Trend of Persistent High Temperature in North China in the Summer of 2018//Compilation of National Excellent Meteorological Service Materials for Decision Making in 2018. Beijing: China Meteorological Press, 2019: 48-49.
  • 加载中
图(10)
计量
  • 摘要浏览量:  2215
  • HTML全文浏览量:  338
  • PDF下载量:  105
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-05-10
  • 修回日期:  2021-07-16
  • 刊出日期:  2021-09-30

目录

    /

    返回文章
    返回