A model-based diagnostic study of "99.6" Meiyu front rainstorm

被引:0
|
作者
Wang, Wen [1 ]
Cai, Xiaojun [1 ]
Long, Xiao [2 ]
机构
[1] NUIST, Key Lab Meteorol Disaster, Minist Educ, Nanjing, Jiangsu, Peoples R China
[2] Lanzhou Univ, Coll Atmospher Sci, Lanzhou 730000, Gansu, Peoples R China
来源
关键词
TOGA COARE IOP;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The long-lasting rainy season over East Asia in early summer is called Meiyu in China and Baiu in Japan. In June 1999, the precipitation in middle and low basin of Yangzi River is twice the average in normal years. A model simulation of "99.6" Meiyu Front rainstorm by nonhydrostatic mesoscale model MM5V3 is analyzed in an effort to study the mechanism of the Meiyu front. The diagnosis of Convective Momentum Transport (CMT) shows that, the budget residual X of the horizontal momentum has different effects in different periods of the low vortex with the shear line: On low levels, X strengthened the southwest flow to north on the occurring stage, on middle levels, X accelerated northwest flow behind East Asia Trough to north and also accelerated northwest flow ahead of East Asia Trough to the south. All these were in favor of deepening the East Asia Trough and mingling cold and warm air, and gave favorable conditions to produce rainstorm.
引用
收藏
页码:221 / 224
页数:4
相关论文
共 50 条
  • [31] A Simulation Study on the Characteristics of Cloud Microphysics of Heavy Rainfall in the Meiyu Front
    鞠永茂
    王汉杰
    钟中
    宋帅
    Journal of Meteorological Research, 2009, 23 (02) : 206 - 222
  • [32] Model-Based Synthesis for Diagnostic Neuro-Classifiers
    Korniak, Jacek
    2014 19TH INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN AUTOMATION AND ROBOTICS (MMAR), 2014, : 754 - 757
  • [33] Diagnostic tools for multivariable model-based control systems
    Kesavan, P
    Lee, JH
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 1997, 36 (07) : 2725 - 2738
  • [34] Diagnostic tools for multivariable model-based control systems
    Kesavan, Parthasarathy
    Lee, Jay H.
    Industrial and Engineering Chemistry Research, 1997, 36 (07): : 2725 - 2738
  • [35] Improved Fault Recognition for Model-Based Diagnostic Systems
    Koetter, Matthias
    Pungs, Andreas
    Wolkenar, Bernd
    INTERNATIONALER MOTORENKONGRESS 2015: MIT NUTZFAHRZEUGMOTOREN - SPEZIAL, 2015, : 499 - 514
  • [36] A decentralized model-based diagnostic tool for complex systems
    Pencolé, Y
    Cordier, MO
    Rozé, L
    ICTAI 2001: 13TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2001, : 95 - 102
  • [37] Constraint Programming for Constructive Abduction. A Case Study in Diagnostic Model-Based Reasoning
    Ligeza, Antoni
    ADVANCED SOLUTIONS IN DIAGNOSTICS AND FAULT TOLERANT CONTROL, 2018, 635 : 94 - 105
  • [38] Model-based registration of front- and backviews of rotationally symmetric objects
    Sablatnig, R
    Kampel, M
    COMPUTER VISION AND IMAGE UNDERSTANDING, 2002, 87 (1-3) : 90 - 103
  • [39] A comparison of model-based and neural network-based diagnostic methods
    Rengaswamy, R
    Mylaraswamy, D
    Årzén, KE
    Venkatasubramanian, V
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2001, 14 (06) : 805 - 818
  • [40] A model-based method for an online diagnostic knowledge-based system
    Angeli, C
    Atherton, D
    EXPERT SYSTEMS, 2001, 18 (03) : 150 - 158