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A historical hurricane database for Coastal Louisiana. Development and population of a historical hurricane database, to validate the rapid surge forecasting model

Joustra, Rinse/R. (2010) A historical hurricane database for Coastal Louisiana. Development and population of a historical hurricane database, to validate the rapid surge forecasting model.

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Abstract:Since hurricane Katrina (2005) flooded large parts of New Orleans and coastal Louisiana, a high demand for fast and accurate hurricane surge forecasting models and tools has been developed. Van den Berg (2008) developed the beta version of a rapid hurricane surge forecasting model eSURF. Furthermore, during hurricane Ike in 2008 eSURF predicted lower maximum water levels then were actually observed in coastal Louisiana. Therefore Lin (2009) adjusted eSURF by adding the Integrated Kinetic Energy parameter to improve eSURF predictions for hurricanes with a large wind span. The main objective of this thesis was to develop an organized historical hurricane database that can give quick insight in maximum water levels that occurred during historical hurricanes. Another objective of this thesis was to validate the rapid hurricane surge forecasting model eSURF with the water level observations stored in the historical hurricane database. The main research question of this thesis is: How accurate are the predicted maximum water levels of eSURF for historical hurricanes passing coastal Louisiana or near coastal Louisiana? The first result of this thesis is a historical hurricane database that contains meteorological and water level data for coastal Louisiana observed during hurricanes. The hurricanes included in the database: Lili (2002), Ivan (2004), Cindy (2005), Dennis (2005), Katrina (2005), Rita (2005), Humberto (2007), Gustav (2008), Ike (2008 and Ida (2009). The following hurricanes are selected based upon criteria: (1) a hurricane should have at least category 1 strength on the Saffir-Simpson-Hurricane-Windscale, (2) have a track within 200 Nautical Miles of the state Louisiana and (3) occurred between 1999 and 2009. The basic hurricane characteristics, water level observations, total daily precipitation and wind speed vector grids have been stored. The data quality of information stored in the historical hurricane database is discussed in this report. The second result of this thesis is that the maximum water levels predicted by eSURF have a mean relative error of 37.2%. This error exceeds the mean error of the SLOSH model with 17.2%. The report includes validation of the historical hurricanes: Ida (2009), Ike (2008), Gustav (2008), Rita (2005) and Katrina (2005). eSURF has been validated based on 25 eSURF prediction points and 25 observations stations. Table 0-1 illustrates the overview on eSURF’s accuracy. eSURF best predicted hurricane Ike (28.2%) and Ida (29.8%), based upon mean error. The most in-accurate predictions were made for hurricane Rita (48.7%). Although, Katrina (44.8%) and Gustav had similar mean relative errors (45.4%). Only 2.4% of the stations of eSURF are validated, due to limited amount of available maximum water level observations. When using the results of this validation, some care has to be taken into account as the results may not be representative for eSURF’s general accuracy. The results of this thesis are only representative for the available and suitable 2.4% of the prediction points. A high need for fast and accurate hurricane surge forecasting models and tools has been developed, since the deadly hurricane Katrina (2005) flooded large parts of New Orleans and coastal Louisiana. Therefore Van den Berg (2008) and Lin (2009) developed a rapid hurricane surge forecasting model eSURF. A validation of the model was needed to evaluate eSURF maximum surge level prediction capabilities. This report describes the development and filling of a historical hurricane database. Furthermore, it describes the method and results of the validation of the model eSURF. Both the database and the validation method and results are discussed.
Item Type:Essay (Bachelor)
Clients:
Royal Haskoning, Nijmegen, Nederland
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering BSc (56952)
Keywords:Hurricane forecasting, eSURF, Hurricane Katrina
Link to this item:http://purl.utwente.nl/essays/59769
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