Transition of the Coastal and Estuarine Storm Tide Model to an Operational Storm Surge Forecast Model: A Case Study of the Florida Coast

被引:24
|
作者
Zhang, Keqi [1 ,2 ]
Li, Yuepeng [2 ]
Liu, Huiqing [2 ]
Rhome, Jamie [3 ]
Forbes, Cristina [3 ]
机构
[1] Florida Int Univ, Dept Earth & Environm, Miami, FL 33199 USA
[2] Florida Int Univ, Int Hurricane Res Ctr, Miami, FL 33199 USA
[3] NOAA, Natl Weather Serv, Natl Ctr Environm Predict, Natl Hurricane Ctr, Miami, FL USA
关键词
BOTTOM STRESS; REAL-TIME; INUNDATION; EQUATIONS; SCHEME; OCEAN;
D O I
10.1175/WAF-D-12-00076.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The operational forecast demands and constraints of the National Hurricane Center require that a storm surge model in research mode be tested against a benchmark model such as Sea, Lake, and Overland Surges from Hurricanes (SLOSH) for accuracy, computation time, and numerical stability before the model is used for operational forecasts. Additionally, the simulated results must be in a geographic information system format to facilitate the usage of computed storm surge for various applications. This paper presents results from a demonstration project to explore the pathway for the transition of the Coastal and Estuarine Storm Tide (CEST) model to an operational forecast model by testing CEST over SLOSH basins in Florida. The performance and stability of CEST were examined by conducting simulations for Hurricane Andrew (1992) and more than 100 000 synthetic hurricanes for nine SLOSH basins covering the Florida coast and Lake Okeechobee. The results show that CEST produces peak surge heights similar to those from SLOSH. Additionally, CEST has proven to be numerically stable against all synthetic hurricanes and the computation time of CEST is comparable to that of SLOSH. Therefore, CEST has the potential to be used for operational forecasts of storm surge. The potential of producing more detailed real-time surge inundation forecasts was also investigated through the simulations of Andrew's surge on various grids with different cell sizes. The results indicate that CEST can produce 48-h forecasts using a single processor in about 40 min over a grid generated by reducing the cell edge size of the SLOSH grid by 4 times.
引用
收藏
页码:1019 / 1037
页数:19
相关论文
共 50 条
  • [41] A storm surge projection and disaster risk assessment model for China coastal areas
    Yang, Shuo
    Liu, Xin
    Liu, Qiang
    NATURAL HAZARDS, 2016, 84 (01) : 649 - 667
  • [43] APPLICATION OF A LINEAR SURGE MODEL FOR THE EVALUATION OF STORM SURGES ALONG THE COASTAL WATERS OF KALPAKKAM, EAST-COAST OF INDIA
    ABROL, V
    INDIAN JOURNAL OF MARINE SCIENCES, 1987, 16 (01): : 1 - 4
  • [44] Storm Surge Forecast Using an Encoder-Decoder Recurrent Neural Network Model
    Wei, Zhangping
    Nguyen, Hai Cong
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2022, 10 (12)
  • [45] Study on Storm Surge Using Parametric Model with Geographical Characteristics
    Kim, Yeon-joong
    Kim, Tea-woo
    Yoon, Jong-sung
    WATER, 2020, 12 (08)
  • [46] Extreme water level determination based on coupling model integrating storm surge and astronomic tide
    Tai Jia'ai
    Chu Ao
    SECOND SINO-GERMAN JOINT SYMPOSIUM ON COASTAL AND OCEAN ENGINEERING, 2006, : 336 - +
  • [47] Storm surge computations for the west coast of Britain using a finite element model (TELEMAC)
    Jones, John Eric
    Davies, Alan M.
    OCEAN DYNAMICS, 2008, 58 (5-6) : 337 - 363
  • [48] Development of a cylindrical polar coordinates shallow water storm surge model for the coast of Bangladesh
    G. C. Paul
    M. M. Murshed
    M. R. Haque
    M. M. Rahman
    A. Hoque
    Journal of Coastal Conservation, 2017, 21 : 951 - 966
  • [49] A Bay–River Coupled Model for Storm Surge Prediction Along the Andhra Coast of India
    Neetu Agnihotri
    P. Chittibabu
    Indu Jain
    P. C. Sinha
    A. D. Rao
    S. K. Dube
    Natural Hazards, 2006, 39 : 83 - 101
  • [50] Storm surge computations for the west coast of Britain using a finite element model (TELEMAC)
    John Eric Jones
    Alan M. Davies
    Ocean Dynamics, 2008, 58 : 337 - 363