RELOCATABLE TIDE PREDICTION AND STORM SURGE FORECASTING

被引:0
|
作者
Prime, Thomas [1 ]
机构
[1] Natl Oceanog Ctr, Liverpool, Merseyside, England
关键词
SHELF; OCEAN;
D O I
暂无
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
The marine environment represents a large and important resource for communities around the world. However, the marine environment increasingly presents hazards that can have a large negative impact. One important marine hazard results from storms and their accompanying surges. This can lead to coastal flooding, particularly when surge and astronomical high tides align, with resultant impacts such as destruction of property, saline degradation of agricultural land and coastal erosion. Where tide and storm surge information are provided and accessed in a timely, accurate and understandable way, the data can provide: 1. Evidence for planning: Statistics of past conditions such as the probability of extreme event occurrence can be used to help plan improvements to coastal infrastructure that are able to withstand and mitigate the hazard from a given extreme event. 2. Early warning systems: Short term forecasts of storm surge allow provide early warnings to coastal communities enabling them to take actions to allow them to withstand extreme events, e.g. deploy flood prevention measures or mobilise emergency response measures. Data regarding sea level height can be provided from various in-situ observations such as tide gauges and remote observations such as satellite altimetry. However, to provide a forecast at high spatial and temporal resolution a dynamic ocean model is used. Over recent decades the National Oceanography Centre has been a world leading in developing coastal ocean models. This paper will present our progress on a current project to develop an information system for the Madagascan Met Office. The project, C-RISC, being executed in partnership with Sea Level Research Ltd, is translating the current modelling capability of NOC in storm surge forecasting and tidal prediction into a system that will provide information that can be easily transferred to other regions and is scalable to include other hazard types The outcome, an operational high-resolution storm surge warning system that is easy to relocate, will directly benefit coastal communities, giving them information they need to make effective decisions before and during extreme storm surge events.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] Validation of the global relocatable tide/surge model PCTides
    Posey, Pamela G.
    Allard, Richard A.
    Preller, Ruth H.
    Dawson, Gretchen M.
    JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2008, 25 (05) : 755 - 775
  • [2] Uncertainty in storm surge forecasting
    Lin, Mei-Ying
    Chiou, Ming-Da
    Liu, Wen-Chen
    Chen, Chih-Ying
    Chen, Hao-Yuan
    Taiwan Water Conservancy, 2016, 64 (03): : 23 - 42
  • [3] The tide forecasting system for China coastal seas: A case study on the effect of tides on storm surge
    Zhao, Yifei
    Deng, Zengan
    Zhai, Jingsheng
    Yu, Ting
    Wang, Hu
    Cao, Yu
    Tong, Yanbin
    KUWAIT JOURNAL OF SCIENCE, 2019, 46 (04) : 104 - 111
  • [4] Development and Application of An Operational Tide and Storm Surge Prediction Model for the Seas around Taiwan
    尤皓正
    于嘉顺
    China Ocean Engineering, 2011, 25 (04) : 591 - 608
  • [5] Development and application of an operational tide and storm surge prediction model for the seas around Taiwan
    Hao-cheng Yu
    Chia-shun Yu
    China Ocean Engineering, 2011, 25 : 591 - 608
  • [6] Development and application of an operational tide and storm surge prediction model for the seas around Taiwan
    Yu Hao-cheng
    Yu Chia-shun
    CHINA OCEAN ENGINEERING, 2011, 25 (04) : 591 - 608
  • [7] Genetic Programming for storm surge forecasting
    Nguyen Thi Hien
    Cao Truong Tran
    Xuan Hoai Nguyen
    Kim, Sooyoul
    Vu Dinh Phai
    Nguyen Ba Thuy
    Ngo Van Manh
    OCEAN ENGINEERING, 2020, 215
  • [8] Short term storm surge forecasting
    Walton, TL
    JOURNAL OF COASTAL RESEARCH, 2005, 21 (03) : 421 - 429
  • [9] RECENT PROGRESS IN STORM SURGE FORECASTING
    NADAO KOHNO
    SHISHIR K.DUBE
    MIKHAIL ENTEL
    S.H.M.FAKHRUDDIN
    DIANA GREENSLADE
    MARIE-DOMINIQUE LEROUX
    JAMIE RHOME
    NGUYEN BA THUY
    Tropical Cyclone Research and Review, 2018, (02) : 128 - 139
  • [10] Verification of RiCOM for Storm Surge Forecasting
    Lane, Emily M.
    Walters, Roy A.
    MARINE GEODESY, 2009, 32 (02) : 118 - 132