A Preliminary Impact Study of CYGNSS Ocean Surface Wind Speeds on Numerical Simulations of Hurricanes

The NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016, providing an unprecedented opportunity to obtain ocean surface wind speeds including wind estimates over the hurricane inner‐core region. This study demonstrates the influence of assimilating an early version of CYGNSS observations of ocean surface wind speeds on numerical simulations of two notable landfalling hurricanes, Harvey and Irma (2017). A research version of the National Centers for Environmental Prediction operational Hurricane Weather Research and Forecasting model and the Gridpoint Statistical Interpolation‐based hybrid ensemble three‐dimensional variational data assimilation system are used. It is found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for both hurricane cases, especially for the weak phase of a hurricane, implying potential benefits of using such data for future research and operational applications.Plain Language SummaryThe NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016. It provides an unprecedented opportunity to obtain ocean surface wind speeds over a hurricane inner‐core region. In this study, we combined the early version of CYGNSS data with all other observations that are currently available for operational forecasts to form initial conditions (inputs data) for a numerical weather prediction model. A research version of the National Oceanic and Atmospheric Administration operational hurricane forecast model named the Hurricane Weather Research and Forecast (HWRF) model is used. Results show that adding CYGNSS data into HWRF model results in improved track, intensity, and structure forecasts for two notable landfalling hurricanes, Harvey and Irma (2017), demonstrating the potential benefits of using CYGNSS data for future research and operational applications.Key PointsThe NASA Cyclone Global Navigation Satellite System (CYGNSS) provides an unprecedented opportunity to obtain ocean surface wind data over a hurricane inner‐core regionThis study found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for two notable landfalling hurricanes, Harvey and Irma (2017)Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148339/1/grl58695.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148339/2/grl58695_am.pd

How Skillful are the Multiannual Forecasts of Atlantic Hurricane Activity?

The recent emergence of near-term climate prediction, wherein climate models are initialized with the contemporaneous state of the Earth system and integrated up to 10 years into the future, has prompted the development of three different multiannual forecasting techniques of North Atlantic hurricane frequency. Descriptions of these three different approaches, as well as their respective skill, are available in the peer-reviewed literature, but because these various studies are sufficiently different in their details (e.g., period covered, metric used to compute the skill, measure of hurricane activity), it is nearly impossible to compare them. Using the latest decadal reforecasts currently available, we present a direct comparison of these three multiannual forecasting techniques with a combination of simple statistical models, with the hope of offering a perspective on the current state-of-the-art research in this field and the skill level currently reached by these forecasts. Using both deterministic and probabilistic approaches, we show that these forecast systems have a significant level of skill and can improve on simple alternatives, such as climatological and persistence forecasts.The first author would like to thank Isadora Jimenez for providing the necessary material for Fig. 2. The first author would like to acknowledge the financial support from the Ministerio de Economía, Industria y Competitividad (MINECO; Project CGL2014- 55764-R), the Risk Prediction Initiative at BIOS (Grant RPI2.0-2013-CARON), and the EU [Seventh Framework Programme (FP7); Grant Agreement GA603521]. We additionally acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. LPC's contract is cofinanced by the MINECO under the Juan de la Cierva Incorporacion postdoctoral fellowship number IJCI-2015-23367. Finally, we thank the National Hurricane Center for making the HURDAT2 data available. All climate model data are available at https://esgf-index1.ceda.ac.uk/projects/esgf-ceda/.Peer ReviewedPostprint (published version

Barrier Layer Impact on Rapid Intensification of Hurricanes (2000-2018) in the Atlantic Ocean

Hurricane prediction is an evolving challenge that has seen much improvement over the years. While hurricane models have improved in predicting the path of storms, forecasts of hurricane intensity are unreliable due to the complexity of environmental data, lack of understanding of how relative humidity, vertical wind shear, hurricane structure and other possible factors affect intensity. Rapid Intensification (RI), which is a wind speed increase of +30 kts over a 24-hr period, can contribute to major destruction and loss of life to coastal communities affected by hurricanes, and is especially difficult to predict. Given the continued development of coastal regions and the threat of RI occurring without warning, it is imperative to better examine all possible factors that might influence hurricane RI to better understand and predict RI. The need for more research into RI was underscored by the devastation caused by rapidly intensifying hurricanes in the Caribbean and the east and gulf coast regions of the U.S. during the 2017 and 2018 hurricane seasons, which included the first landfall of a Category 5 hurricane (Hurricane Michael, 2018) since Hurricane Andrew in 1992. Recent studies examining the barrier layer (BL) of the water column and its relationship to hurricane intensification have shown that BLs favor RI, and that barrier layer thickness (BLT) may influence the storm’s intensity. To determine if BLs might improve the prediction of hurricane intensity, this study examined all hurricanes in the Atlantic Ocean, Caribbean, and Gulf of Mexico spanning the years 2000-2018. Using relevant HYCOM data, daily temperature (T), salinity (S), mixed layer thickness (mlp), isothermal layer thickness (mld), and BLT were examined to determine each factor’s horizontal distribution and possible influence on RI events occurring during the 139 hurricanes. Additional analysis was conducted on 12 randomly selected hurricanes (six of which had RI events and six of which did not) to determine if these factors, specifically BLT, act as significant predictors for RI events. Although no known link has been shown in previous research, this study also sought to determine if there is a correlation between RI and the horizontal variability of BLT and other key factors near the center of a hurricane (within 1 degree lat/lon).Though BLs can exist in any ocean, they are constantly changing and not always present. In this study, however, it was observed that BLs were present during all hurricanes in the Atlantic (2000-2018), whether they experienced a period of RI or not. Using an untested horizontal statistical analysis, this study shows that barrier layer thickness (BLT) does not appear to be a significant predictor of the probability of an RI event to occur, with no clear relationship shown between BLT and the magnitude of intensification, but these results cannot be taken as definitive. Given the limitations of this study, future research on hurricane RI should incorporate all known factors that impact hurricane intensity, testing each using multiple intensity models across all ocean basins

Numerical and experimental studies on coastal marsh erosion under hurricane induced wave and current

Considering the past history and future risks of hurricanes in the USA, well understood storm protection plans are needed to shelter the important areas of the population and economy, especially within southeastern Louisiana. It is extensively assumed that marshes offer protection from hurricane though the degree of this protection is not well measured or understood due to the complex physics involved in this overall system. Moreover, marshes experience significant erosion while serving as a barrier for important areas. Consequently, a particular method to quantify the effects on marshes during a coastal hurricane period is necessary to mitigate major marsh loss. A study comprised of experimental work and numerical simulation was undertaken to evaluate the effect of marsh vegetation on resisting hurricane induced erosion and erosion of the marsh itself. Local vegetation Spartina alterniflora was selected as principal marsh vegetation for this study. Contribution from Spartina alterniflora had been analyzed from two different directions such as contribution of roots and contribution of shoots. The overall research was divided into three different phases. The first phase was the laboratory experiments of collected soil samples with and without roots of Spartina from the study area (Cycle-1 of CS-28 project). Direct shear tests were perfouned on the samples to study the effect of roots on soil shear strength. Tensile strength of the roots was also studied. In the second phase, Delft3D wave flow coupled model was applied on the Louisiana coastal marsh near Calcasieu Lake to assess the contribution of marsh vegetation in reducing hurricane induced wave and current actions. The objective of this phase was to develop an integrated wind, current, wave modeling system for the Louisiana coast under hurricane conditions. Hurricane Ike in 2008 was chosen as an example to study the marsh\u27s contribution during hurricane. The wave flow coupled model was generated covering a significant part of Calcasieu Lake, surrounding marshes and a part of the Gulf of Mexico. The coupled model was calibrated and validated against observed data gathered from NOAA and CPRA observation stations. Later after validation, Hurricane Ike forcing condition was introduced to the wave flow coupled model. Moreover, to originate the extreme scenario, the hurricane was introduced by excluding the precipitation and flooding effect of a previous hurricane named Gustav that made landfall 13 days prior to Hurricane Ike. Delft3D vegetation model was also analyzed to investigate the effect of a hurricane on vegetated mud bed. In the third phase, based on the experimental results from the tensile and direct shear tests and hurricane stress results from Delft3D analysis, slope stability analyses were performed for 16 different scenarios by utilizing Slope/W to predict erosion of vegetated and non-vegetated mud surface during different phases of a hurricane. Experimental results suggested that the marshes do have the potential to enhance soil shear strength. Results suggested that the additional cohesion developed from plant roots played a vital role in enhancing shear strength of marsh soil, especially near the surface. A correlation between Spartina alterniflora root tensile strength and root cohesion was proposed for dredged soil. The validation of the coupled wave flow model showed that the water level computed by Delft3D agrees fairly well with the measured data. Results from Delft3D vegetation model study indicated a major reduction in the current velocity in presence of the Spartina alterniflorashoot system. Results from the hurricane induced wave flow model showed that the wave induced bed shear stress up to 90 Pa can be the result while hurricane reached its peak time. It was found that the edge and flat soil mass of the marsh reacted differently under hurricane induced wave and current action especially when time dependent analysis is considered. It was also observed that the presence of a shoot system around the weak spot reduces bed shear stress significantly, especially while the marsh bed is submerged or under a low wave energy field. Yet, completely exposed vegetation during the peak of a hurricanes was found to be most vulnerable and supposed to experience severe mass erosion/marsh shears. It was also noticed from the erosion prediction analysis that the hurricane damage could have been severe if there was no prior hurricane before Hurricane Ike. From the summary of erosion prediction analysis output, it was observed that the uprooting or mass erosion only occurred during two scenarios among sixteen scenarios. Near the marsh edge, mass erosion occurred during the hurricane landfall with the condition that the marsh edge was above water prior to hurricane impact. On marsh flat, mass erosion occurred during the peak of the hurricane when analyzed with drought condition prior to the hurricane. The combined experimental and numerical analysis of Louisiana coastal marsh under hurricane-induced waves and currents provided useful insights of actual scenarios and probable cases. The findings could be used effectively in the design and construction of future marsh creation projects in Louisiana