The Impact of Verification Area Design on Tropical Cyclone Targeted Observations Based on the CNOP Method

被引:0
|
作者
周菲凡 [1 ]
穆穆 [2 ]
机构
[1] Laboratory of Cloud-Precipitation Physics and Severe Storms,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029
[2] State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029
基金
中国国家自然科学基金;
关键词
sensitive area; verification area; CNOP; FSV;
D O I
暂无
中图分类号
P444 [热带气象];
学科分类号
0706 ; 070601 ;
摘要
This study investigated the impact of different verification-area designs on the sensitive areas identified using the conditional nonlinear optimal perturbation (CNOP) method for tropical cyclone targeted observations.The sensitive areas identified using the first singular vector (FSV) method,which is the linear approximation of CNOP,were also investigated for comparison.By analyzing the validity of the sensitive areas,the proper design of a verification area was developed.Tropical cyclone Rananim,which occurred in August 2004 in the northwest Pacific Ocean,was studied.Two sets of verification areas were designed;one changed position,and the other changed both size and position.The CNOP and its identified sensitive areas were found to be less sensitive to small variations of the verification areas than those of the FSV and its sensitive areas.With larger variations of the verification area,the CNOP and the FSV as well as their identified sensitive areas changed substantially.In terms of reducing forecast errors in the verification area,the CNOP-identified sensitive areas were more beneficial than those identified using FSV.The design of the verification area is important for cyclone prediction.The verification area should be designed with a proper size according to the possible locations of the cyclone obtained from the ensemble forecast results.In addition,the development trend of the cyclone analyzed from its dynamic mechanisms was another reference.When the general position of the verification area was determined,a small variation in size or position had little influence on the results of CNOP.
引用
收藏
页码:997 / 1010
页数:14
相关论文
共 50 条
  • [31] A Tropical Cyclone Center Location Method Based on Satellite Image
    You, Qingxiang
    Li, Zhenqing
    Qian, Cheng
    Wang, Tian
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [32] Verification of Ensemble-Based Uncertainty Circles around Tropical Cyclone Track Forecasts
    Dupont, Thierry
    Plu, Matthieu
    Caroff, Philippe
    Faure, Ghislain
    WEATHER AND FORECASTING, 2011, 26 (05) : 664 - 676
  • [33] An Adjoint-Free CNOP–4DVar Hybrid Method for Identifying Sensitive Areas in Targeted Observations: Method Formulation and Preliminary Evaluation
    Xiangjun TIAN
    Xiaobing FENG
    Advances in Atmospheric Sciences, 2019, 36 (07) : 721 - 732
  • [34] An Adjoint-Free CNOP–4DVar Hybrid Method for Identifying Sensitive Areas Targeted Observations: Method Formulation and Preliminary Evaluation
    Xiangjun Tian
    Xiaobing Feng
    Advances in Atmospheric Sciences, 2019, 36 : 721 - 732
  • [35] An Adjoint-Free CNOP-4DVar Hybrid Method for Identifying Sensitive Areas Targeted Observations: Method Formulation and Preliminary Evaluation
    Tian, Xiangjun
    Feng, Xiaobing
    ADVANCES IN ATMOSPHERIC SCIENCES, 2019, 36 (07) : 721 - 732
  • [36] The impact of spatial and temporal distribution of satellite observations on tropical cyclone data assimilation: Preliminary results
    LeMarshall, JF
    Leslie, LM
    Spinoso, C
    METEOROLOGY AND ATMOSPHERIC PHYSICS, 1996, 60 (1-3) : 157 - 163
  • [37] Pattern Recognition of Tropical Cyclone Damages based on Fuzzy Cluster Method
    Guo, Chonglan
    Xu, Xiaoxia
    Zhou, Xianxin
    Gong, Zaiwu
    INNOVATIVE THEORIES AND METHODS FOR RISK ANALYSIS AND CRISIS RESPONSE, 2012, 21 : 90 - 95
  • [38] A tropical cyclone similarity search algorithm based on deep learning method
    Wang, Yu
    Han, Lei
    Lin, Yin-Jing
    Shen, Yue
    Zhang, Wei
    ATMOSPHERIC RESEARCH, 2018, 214 : 386 - 398
  • [39] The characterization and impact of Aeolus wind profile observations in NOAA's regional tropical cyclone model (HWRF)
    Marinescu, Peter J.
    Cucurull, Lidia
    Apodaca, Karina
    Bucci, Lisa
    Genkova, Iliana
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2022, 148 (749) : 3491 - 3508
  • [40] Impact of Satellite Observations on the Tropical Cyclone Track Forecasts of the Navy Operational Global Atmospheric Prediction System
    Goerss, James S.
    MONTHLY WEATHER REVIEW, 2009, 137 (01) : 41 - 50