Abstract In the aftermath of Hurricane Ike in 2008 in the United States, the “Ike Dike” was proposed as a coastal barrier system, featuring floodgates, to protect the Houston‐Galveston area (HGA) from future storm surges. Given its substantial costs, the feasibility and effectiveness of the Ike Dike have been subjects of investigation. In this study, we evaluated these aspects under both present and future climate conditions by simulating storm surges using a set of models. Delft3D Flexible Mesh Suite was utilized to simulate hydrodynamic and wave motions driven by hurricanes, with wind and pressure fields spatialized by the Holland model. The models were validated against data from Hurricane Ike and were used to simulate synthetic hurricane tracks downscaled from several general circulation models and based on different sea level rise projections, both with and without the Ike Dike. Flood maps for each simulation were generated, and probabilistic flood depths for specific annual exceedance probabilities were predicted using annual maxima flood maps. Building damage curves were applied to residential properties in the HGA to calculate flood damage for each exceedance probability, resulting in estimates of expected annual damage as a measure of quantified flood risk. Our findings indicate that the Ike Dike significantly mitigates storm surge risk in the HGA, demonstrating its feasibility and effectiveness. We also found that the flood risk estimates are sensitive to hurricane intensity, the choice of damage curve, and the properties included in the analysis, suggesting that careful consideration is needed in future studies.
more »
« less
Characterizing Continental US Hurricane Risk: Which Intensity Metric Is Best?
Abstract The damage potential of a hurricane is widely considered to depend more strongly on an integrated measure of the hurricane wind field, such as integrated kinetic energy (IKE), than a point‐based wind measure, such as maximum sustained wind speed (Vmax). Recent work has demonstrated that minimum sea level pressure (MSLP) is also an integrated measure of the wind field. This study investigates how well historical continental US hurricane damage is predicted by MSLP compared to bothVmaxand IKE for continental United States hurricane landfalls for the period 1988–2021. We first show for the entire North Atlantic basin that MSLP is much better correlated with IKE (rrank = 0.50) thanVmax(rrank = 0.26). We then show that continental US hurricane normalized damage is better predicted by MSLP (rrank = 0.83) than eitherVmax(rrank = 0.67) or IKE (rrank = 0.65). For Georgia to Maine hurricane landfalls specifically, MSLP and IKE show similar levels of skill at predicting damage, whereasVmaxprovides effectively no predictive power. Conclusions for IKE extend to power dissipation as well, as the two quantities are highly correlated because wind radii closely follow a Modified Rankine vortex. The physical relationship of MSLP to IKE and power dissipation is discussed. In addition to better representing damage, MSLP is also much easier to measure via aircraft or surface observations than eitherVmaxor IKE, and it is already routinely estimated operationally. We conclude that MSLP is an ideal metric for characterizing hurricane damage risk.
more »
« less
- Award ID(s):
- 1945113
- PAR ID:
- 10373242
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 127
- Issue:
- 18
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract The radius of maximum wind (Rmax) in a tropical cyclone governs the footprint of hazards, including damaging wind, surge, and rainfall. However,Rmaxis an inconstant quantity that is difficult to observe directly and is poorly resolved in reanalyses and climate models. In contrast, outer wind radii are much less sensitive to such issues. Here we present a simple empirical model for predictingRmaxfrom the radius of 34-kt (1 kt ≈ 0.51 m s−1) wind (R17.5 ms). The model only requires as input quantities that are routinely estimated operationally: maximum wind speed,R17.5 ms, and latitude. The form of the empirical model takes advantage of our physical understanding of tropical cyclone radial structure and is trained on the Extended Best Track database from the North Atlantic 2004–20. Results are similar for the TC-OBS database. The physics reduces the relationship between the two radii to a dependence on two physical parameters, while the observational data enables an optimal estimate of the quantitative dependence on those parameters. The model performs substantially better than existing operational methods for estimatingRmax. The model reproduces the observed statistical increase inRmaxwith latitude and demonstrates that this increase is driven by the increase inR17.5 mswith latitude. Overall, the model offers a simple and fast first-order prediction ofRmaxthat can be used operationally and in risk models. Significance StatementIf we can better predict the area of strong winds in a tropical cyclone, we can better prepare for its potential impacts. This work develops a simple model to predict the radius where the strongest winds in a tropical cyclone are located. The model is simple and fast and more accurate than existing models, and it also helps us to understand what causes this radius to vary in time, from storm to storm, and at different latitudes. It can be used in both operational forecasting and models of tropical cyclone hazard risk.more » « less
-
Abstract Minimum central pressure (Pmin) is an integrated measure of the tropical cyclone wind field and is known to be a useful indicator of storm damage potential. A simple model that predictsPminfrom routinely estimated quantities, including storm size, would be of great value. Here, we present a simple linear empirical model for predictingPminfrom maximum wind speed, a radius of 34-kt (1 kt ≈ 0.51 m s−1) winds (R34kt), storm center latitude, and the environmental pressure. An empirical model for the pressure deficit is first developed that takes as predictors specific combinations of these quantities that are derived directly from theory based on gradient wind balance and a modified Rankine-type wind profile known to capture storm structure inside ofR34kt. Model coefficients are estimated using data from the southwestern North Atlantic and eastern North Pacific from 2004 to 2022 using aircraft-based estimates ofPmin, extended best track data, and estimates of environmental pressure from Global Forecast System (GFS) analyses. The model has a near-zero conditional bias even for lowPmin, explaining 94.2% of the variance. Performance is superior to a variety of other model formulations, including a standard wind–pressure model that does not account for storm size or latitude (89.2% variance explained). Model performance is also strong when applied to high-latitude data and data near coastlines. Finally, the model is shown to perform comparably well in an operation-like setting based solely on routinely estimated variables, including the pressure of the outermost closed isobar. Case study applications to five impactful historical storms are discussed. Overall, the model offers a simple, fast, physically based prediction forPminfor practical use in operations and research. Significance StatementSea level pressure is lowest at the center of a hurricane and is routinely estimated in operational forecasting along with the maximum wind speed. While the latter is currently used to define hurricane intensity, the minimum pressure is also a viable measure of storm intensity that is known to better represent damage risk. A simple empirical model that predicts the minimum pressure from maximum wind speed and size, and based on the physics of the hurricane wind field, does not currently exist. This work develops such a model by using wind field physics to determine the important parameters and then uses a simple statistical model to make the final prediction. This model is quick and easy to use in weather forecasting and risk assessment applications.more » « less
-
Abstract The radius of maximum windRmax, an important parameter in tropical cyclone (TC) ocean surface wind structure, is currently resolved by only a few sensors so that, in most cases, it is estimated subjectively or via crude statistical models. Recently, a semiempirical model relying on an outer wind radius, intensity, and latitude was fit to best-track data. In this study we revise this semiempirical model and discuss its physical basis. While intensity and latitude are taken from best-track data,Rmaxobservations from high-resolution (3 km) spaceborne synthetic aperture radar (SAR) and wind radii from an intercalibrated dataset of medium-resolution radiometers and scatterometers are considered to revise the model coefficients. The new version of the model is then applied to the period 2010–20 and yieldsRmaxreanalyses and trends that are more accurate than best-track data. SAR measurements corroborate that fundamental conservation principles constrain the radial wind structure on average, endorsing the physical basis of the model. Observations highlight that departures from the average conservation situation are mainly explained by wind profile shape variations, confirming the model’s physical basis, which further shows that radial inflow, boundary layer depth, and drag coefficient also play roles. Physical understanding will benefit from improved observations of the near-core region from accumulated SAR observations and future missions. In the meantime, the revised model offers an efficient tool to provide guidance onRmaxwhen a radiometer or scatterometer observation is available, for either operations or reanalysis purposes.more » « less
-
Abstract Hurricane Ike, which struck the United States in September 2008, was the ninth most expensive hurricane in terms of damages. It caused nearly USD 30 billion in damage after making landfall on the Bolivar Peninsula, Texas. We used the Delft3d-FM/SWAN hydrodynamic and spectral wave model to simulate the storm surge inundation around Galveston Bay during Hurricane Ike. Damage curves were established through the relationship between eight hydrodynamic parameters (water depth, flow velocity, unit discharge, flow momentum flux, significant wave height, wave energy flux, total water depth (flow depth plus wave height), and total (flow plus wave) force) simulated by the model and National Flood Insurance Program (NFIP) insurance damage data. The NFIP insurance database contains a large amount of building damage data, building stories, and elevation, as well as other information from the Ike event. We found that the damage curves are sensitive to the model grid resolution, building elevation, and the number of stories. We also found that the resulting damage functions are steeper than those developed for residential structures in many other locations.more » « less
An official website of the United States government
