Difference between revisions of "2018 CSDMS meeting-061"

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|CSDMS_meeting_select_clinics1_2018=2) BMI Live!
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|CSDMS_meeting_select_clinics1_2018=4) Sediment Experimentalist Network
 
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|CSDMS_meeting_select_clinics2_2018=1) Structure from Motion (SfM)
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|CSDMS_meeting_select_clinics2_2018=3) Data for natural hazards
 
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{{CSDMS meeting select clinics3 2018
|CSDMS_meeting_select_clinics3_2018=1) Downscaling climate models for regional applications
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|CSDMS_meeting_select_clinics3_2018=4) Artificial Intelligence & Machine Learning
 
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{{CSDMS meeting abstract yes no 2018
 
{{CSDMS meeting abstract yes no 2018

Latest revision as of 13:29, 21 February 2018





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A Sensitivity Analysis of the Effect of Parametric Wind Model Inputs on Hurricane Storm Surge Simulations

Huda Qureshi, Columbia University New York New York, United States. hq2152@columbia.edu
Kyle Mandli, Columbia University New York New York, United States. ktm2132@columbia.edu


The high speed winds of a hurricane account for 95% of a hurricane’s storm surge. Thus, parametric wind models are vital components of numerical storm surge modeling. These parametric hurricane wind models are used as inputs for a storm surge computation to hindcast and forecast hurricane surge heights. These wind models are dependent on several input parameters including but not limited to the radius at which the maximum wind speed of the hurricane occurs and the speed of the maximum winds. The impact of these input parameters on the final surge computation is not well known. Our study is a sensitivity analysis of the effect of uncertainty in the input parameters on the uncertainty in the final computation of the storm surge model. This study will help us to understand the robustness of a parametric wind model, the parameters that must be precise in order to reduce model error, and can aid in model simplification.