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During the 2019 peak hurricane season, two gliders operated by Texas A&M University (TAMU) and the University of Southern Mississippi (USM) and funded by Shell Exploration & Production Company were deployed as part of the National Oceanic and Atmospheric Administration Hurricane Glider Program to collect near-real time subsurface ocean temperature and salinity measurements for data assimilation into global ocean and hurricane models. The missions were designed to resolve regional ocean features that can contribute to hurricane intensity and provide spatial coverage in the event of a tropical cyclone with the intent to capture potential intensification prior to landfall. For the Gulf of Mexico, the Mississippi River plume, Loop Current, and Loop Current Eddies are areas of interest that can contribute to hurricane intensity. Tropical Storms Nester and Olga were named storms during the 2019 season in the Atlantic Basin, and their trajectories passed by the USM and TAMU gliders, respectively. While changes in the sea surface temperature were more likely due to the presence of seasonal fronts rather than the passing of these tropical storms, the data did indicate pockets of subsurface warm water under a freshwater plume from the Mississippi River. Currently, multiple hurricane glider missions are underway in the Gulf of Mexico during a record breaking 2020 season with Hurricane Laura anticipated to make landfall early morning (local time) on Thursday, August 27, 2020 near the Texas/Louisiana border.

The Atlantic hurricane season brings devastation to Small Island Developing States (SIDS) each year. SIDS, as designated by the United Nations, are developing countries with specific vulnerabilities due to their small size and susceptibility to environmental disasters [1]. These disasters have led to episodic food insecurity and disruption of agricultural livelihoods. In order to address this problem, a 3-Cavaliers research group at the University of Virginia partnered with Babylon Micro-Farms (BMF), a company in Charlottesville, VA, to develop a hydroponic crop cultivation (HCC) system for use in the Caribbean as a test case for SIDS. Hydroponics refers to the cultivation of plants through a nutrient rich solution without the need for soil. The research team worked with previous Capstone teams to develop and test a low-cost HCC system in the island of Dominica after Hurricane Maria. The current Capstone project aims to enhance this design by strengthening its resilience to storms and hurricanes. The resulting hydroponics system design for SIDS has four main parts: the plant growth unit, the nutrient water system, the solar power unit, and the structure. The plant growth unit is made up of PVC pipes that are on a top base and covered by an agricultural fabric to protect from insects. This base is angled to initiate the gravitational flow of the nutrient enriched water that is pumped in by the system. The solar power unit provides power to the system of pumps that move the water and nutrients throughout the system. The plant growth unit is supported by a collapsible wooden frame to reduce wind loading on the structure. Once the structure is collapsed, a durable plastic cover can be pulled over the unit to further protect the plants from wind. Both the plant growth unit and the base of the structure are designed to be easily transportable so users can safely store the unit inside during intense storms.Ultimately, we will create blueprints of the structure and design plans for a prototype that will be used and monitored in Abaco, Bahamas. We will also deliver a conditional recommendation on which crops to grow with respect to five specific criteria: harvest period, yield, seed price, market price, and nutritional value. This will allow the farmer to determine his particular crop species based on his own unique goals for hydroponic farming.

Rain and temperature retrievals from a common algorithm based on microwave sensors onboard five polar orbiting satellites are included to study tropical cyclone (TC) rain rate characteristics and warm core structure. The retrieval algorithm used here is NOAA’s operational Microwave Integrated Retrieval System (MiRS). The five satellites/sensors are S-NPP/ATMS, NOAA-20/ATMS, Metop-B/AMSUA-MHS, Metop-C/AMSUA-MHS, and GPM/GMI. Hurricane Florence occurred, which occured in the Atlantic basin in 2018, is chosen as the study case. Hurricane Matthew in 2016 (before NOAA-20 and Metop-C were launched) is also included to illustrate warm core structure retrieved by MiRS.

Based on 12 years (2004-2015) of GOES-East satellite infrared (IR) imagery over the North Atlantic basin, the diurnal cycle of the tropical cyclone (TC) Deviation Angle Variation (DAV) value is analysed, and a backward 24-hr time average DAV is selected to filter the noise in the DAV-TC intensity estimation. The effect of satellite observation angle on the DAV-TC intensity estimation is analysed in theory, in a case study, and in the longer-term statistics. Based on these results, an improvement to the DAV-TC intensity estimation is presented and evaluated in this study. The results show that, after taking the observation angle into account, the new DAV-TC intensity estimation is shown to produce smaller errors and higher correlations than the previous versions, especially for major hurricanes.

The flight operations of the Cyclone Global Navigation Satellite System (CYGNSS), a constellation of eight microsatellites built and operated by Southwest Research Institute (SwRI), designed to improve the intensity forecasts of Tropical Cyclones, has seen a litany of changes to its concept of operations, software, processes, and personnel. In this paper, we detail how the operations team responded to several challenges such as the reduction in personnel after the Launch and Early Orbit Operations phase, the addition of a downlink antenna in Japan, high-fidelity collection requests during the unusually active 2017 Atlantic hurricane season, and the increased demands of team members from other projects. These pressures forced the CYGNSS operations team to innovate their way to efficient operations. These innovations were enabled by embracing modern open-source tools such as Django, Bokeh, Git, the various libraries available in the Python programming language, and the capabilities that come with all of our operations engineers being competent in software development. The CYGNSS team took the approach of automating the most time-intensive tasks first, which freed up time to carefully design and test more elaborate automation solutions. We utilized the spirit of the Agile Methodology to make incremental improvements to our software suite which further enabled more sophisticated automation. Finally, we chart a path forward to fully closing the automation loop between our mission planning, and real-time Command and Control.

The intensity, frequency, and duration of North Atlantic hurricanes have increased since the early 1980s. Every year these storms impact the Mid-Atlantic Bight (MAB), a region that includes the coastline with the highest US coastal population density, important commercial and naval ports, and commercial and recreational fisheries. The interaction between the storms and the surface currents, including tides and coastal trapped waves (CTWs), have a large economic and destructive impact as well as great implications on marine debris transport before, during, and after storms. The effect of storms on CTWs is the least understood of these interactions. Observations of CTWs from high-frequency radar (HFR) SeaSonde data indicate typical surface velocity amplitudes of 10–20 cm s−1, while maximum velocities can reach as high as 100 cm s−1 during strong storms. This suggests that storm-induced CTWs are capable of transporting marine debris farther than typical, non-storm conditions. Focusing on 2012 Hurricane Sandy, which had a major impact in the MAB, the study area is seeded with 100 artificial Lagrangian particles just before Hurricane Sandy made landfall in New Jersey and we calculate their trajectories over five days using observed HFR velocities. The distance traveled and particle paths for full velocity are compared to a CTW-only velocity case during Hurricane Sandy, as well as for a five day non-storm period. In all cases, particles are transported farther under Hurricane Sandy storm conditions than non-storm conditions, with percentage increases between 150–250 %. CTWs have a larger contribution to the total distance traveled using full velocity under storm conditions (47 %) than non-storm conditions (33 %) although CTW increases in distance traveled is directly proportional to increases in wind strength. Furthermore, particle trajectories suggest estuaries disrupt theoretical CTW propagation patterns.

Every Atlantic Hurricane season since July 2014, an array of underwater gliders is deployed off Puerto Rico by NOAA’s Atlantic Oceanographic & Meteorological Laboratory (AOML) and the Caribbean Coastal Ocean Observing System (CARICOOS) as part of a multi-institutional effort. The goal of this work is to enhance our knowledge on the role of the ocean on the intensification of tropical cyclones (TC) in the Atlantic Ocean. Sustained and targeted upper-ocean profile observations from underwater gliders are carried out to assess the upper ocean response to hurricane force winds and to evaluate the impact of these observations on tropical cyclone intensity forecasts. Glider observations provide valuable data on the ocean’s thermal and haline structure prior to a storm’s arrival, during the storm, and after the storm has passed. Initial findings from this study have shown that assimilation of glider data into coupled tropical cyclone forecast models, specifically the Hurricane Weather Research and Forecasting (HWRF) Model-Hybrid Coordinate Ocean Model (HYCOM), significantly improved the initial upper ocean thermal and haline conditions near the glider locations and beyond. Another finding from these studies was that salinity plays an important role in suppressing the hurricane induced upper ocean cooling by creating a nearsurface barrier layer, causing temperature changes to be less than expected, which helps sustain the TC intensification.

The Macaronesia is a vast area playing a key role in the East boundary of the Central North-Atlantic Ocean-circulation system. Despite a significant research activity in ocean monitoring for decades using a wide range of observing systems and methodologies, the area is still under-sampled, mainly due access and coverage constrains, as well as the observation sustainability. Ocean gliders offer a new approach in terms of capacity and sustainability, allowing undertake ocean-monitoring in spatiotemporal scales hitherto unavailable. The present work shows preliminary results from the latest mission with buoyancy-driven and surface ocean gliders in the area, whose main goal focuses on to improve and expand ocean observation capabilities strengthening glider endurance lines between archipelagos, as part of the global ocean-observation strategy conducted by the Marine & Maritime Network (R3M), as contributing party aligned with the European and international efforts in the North Atlantic basin.

The active 2017 Atlantic hurricane season saw the passage of two powerful Category 5 storms, Hurricanes Irma and Maria, that caused widespread damage in the US Caribbean region. These storms passed across the Caribbean Coastal Ocean Observing System (CARICOOS), a network of observing assets, including data oceanographic buoys, coastal meteorological stations and high-frequency (HF) radar arrays capable of monitoring real-time oceanographic and meteorological conditions. However, due to storm damage on land and the loss of shoreside power and local communication network most of the land-based observing assets were unable to operate. The four real-time oceanographic data buoys, located in the coastal waters of Puerto Rico and US Virgin Islands, were able to measure oceanographic data from these storms, providing real-time data via satellite of winds, surface waves, air and water temperature, salinity, and currents. The acquired data provides useful information to validate and fine-tune numerical forecasting models and provides the opportunity to assess the impact of the storms on coastal ocean processes in the region. Moreover, the buoys performance during the storms also confirms the adequacy of the mooring design. Key design features of the buoys that allowed continuous operation during the storms were (1) significant reserve buoyancy, allowing the buoys to avoid submergence, at the expense of increased risk of anchor motion during the storm, (2) robust construction of welded structural aluminum (3) dual real-time communication systems, (4) dual wind sensors, (5) site placement, (6) attention to details such as the use of stainless-steel hardware and Delrin isolators for dissimilar metals.

The Advanced Baseline Imager (ABI) on GOES-16 meteorological satellite successfully completed one year in orbit and scientists at NOAA and NASA have been conducting extensive calibration and validation activities since data collection began in January 2017. The results look impressive and the sensor is performing as expected. ABI imagery has been extensively used to detect monitor and track numerous significant meteorological and environmental events such as Atlantic hurricanes in 2017. This presentation will highlights analysis of sensor data during the first year and showcase the impact of ABI on operational decision making in the United States during the first year.

The CYGNSS constellation of eight smallsats was successfully launched in low Earth orbit on December 15, 2016. Each satellite carries a four channel bistatic radar receiver which measures GPS signals scattered from the Earth surface, from which ocean surface wind speed is determined. The use of a constellation, and the way their orbits are configured relative to one another, enable critical sampling properties. In particular, short time scale physical processes like the rapid intensification phase of a tropical cyclone can be resolved. Results from the 2017 Atlantic hurricane season will be used to demonstrate this.

Hurricane Irma, landed Florida on September 9th, 2017, was the most intense Atlantic hurricane striking the United States since Hurricane Katrina in 2005. The evolution of Irma was well observed on September 9h–11th by an S-band EEC dual-pol radar deployed in Miami, FL. The radar applied a high temporal and spatial resolution (0.5 minute, 62.5∼125m range

In 2005, the National Data Buoy Center (NDBC) Weather Buoy network was expanded with 15 additional buoys in the Caribbean Sea in support of early detection and improved forecasts of Atlantic Hurricanes. These buoys have now become a standard and highly valuable asset to the Weather Buoy network, and as such, some will be upgraded with the modular Self Contained Ocean Observing Payload (SCOOP) to add new capabilities and value. One of these new capabilities includes real-time observations of subsurface temperature and salinity measurements. With this new ability, the enhanced Weather Buoys located in “hurricane alley” will be better positioned to support the real-time analyses of ocean heat content and high frequency weather phenomena linked to hurricanes. As part of this effort, NDBC assessed the utility of adding a low-cost thermistor string in lieu of traditional oceanographic sensors and deployed two SCOOP stations 13 km apart in the Caribbean Sea at Weather Buoy station 42058. One station was equipped with standard oceanographic sensors used as a reference, while the other station was equipped with a thermistor string. The purpose of the field test was verify the thermistor string observations meet NDBC accuracy requirements and to evaluate the ease of operation and durability within the field environment. The results indicate the thermistor string is acceptable within ±0.1°C greater than 80% of the time in the upper layer, yet when using the observations to calculate ocean heat content, there is an average error of 11%, Lastly, our results show the sensor response time, ease of deployment and durability of the thermistor string are not suitable for hurricane observations.

Catastrophes have caused tremendous damages in human history and triggered record high post-disaster relief from the governments. The research of catastrophic modeling can help estimate the effects of natural disasters like hurricanes, floods, surges, and earthquakes. In every Atlantic hurricane season, the state of Florida in the United States has the potential to suffer economic and human losses from hurricanes. The Florida Public Hurricane Loss Model (FPHLM), funded by the Florida Office of Insurance Regulation, has assisted Florida and the residential insurance industry for more than a decade. How to process big data for historical hurricanes and insurance companies remains a challenging research topic for cat models. In this paper, the FPHLM's novel integrated domain knowledge assisted big data processing system is introduced and its effectiveness of data processing error prevention is presented.

Integrated ocean observations from Hurricane Irene (2011) reveal widespread and significant ahead-of-eye cooling (at least 5°C and up to 11°C) as it crossed the seasonally stratified continental shelf of the Mid-Atlantic Bight of North America. Buoys and gliders deployed in the storm allow the detailed evolution of the surface temperature to be examined at select points, revealing 76%–94% of the total cooling occurs before eye passage. A range of ocean models were used to diagnose the processes responsible for the observed cooling. In Irene, 1D vertical mixing models generate only 17% of the total cooling ahead of eye, while deepwater 3-D models forced by Irene's nearly symmetrical offshore windfield produce an approximately 50–50 split in the cooling between the front and back side. A 3-D coastal ocean model (ROMS) generates a wind-forced two-layer circulation in the stratified MidAtlantic not present in the 1-D and 3-D deepwater models. The resultant shearinduced mixing more accurately reproduces both the magnitude and timing of the surface cooling with respect to eye passage. Atmospheric simulations establish that this cooling was the missing contribution required to reproduce Irene's accelerated reduction in intensity over the Mid Atlantic Bight. Historical buoys from 1985 to present show that ahead-of-eye cooling occurred beneath all 11 tropical cyclones that traversed along the Mid Atlantic Bight continental shelf during stratified summer conditions. The buoys also reveal that an average of about 75% of the cooling in these 11 hurricanes occurs ahead of eye, indicating a robust process in the Mid Atlantic. Similar to the Mid Atlantic Bight, the Yellow Sea have had 26 typhoons cross its shallow highly stratified waters in summer before making landfall in China or Korea. Typhoon Muifa (2011), whose intensity was also overpredicted, generated significant SST cooling (up to 7C) in the Yellow Sea, and a Yellow Sea buoy array similarly revealed 85% of the cooling was ahead of eye. These findings establish that including realistic 3D coastal ocean processes in forecasts of landfalling storm intensity and impacts will be increasingly critical to mid-latitude population centers as sea levels rise and tropical cyclone maximum intensities migrate poleward.

The Mid Atlantic Bight continental shelf has one of the largest summer temperature gradients in the world, with near bottom temperatures below 8C and peak surface temperatures over 28C. This is largely due to the summer Cold Pool, remnant winter water that is generated on the northern MAB and transported southward along the continental shelf in spring and early summer. During tropical cyclones that impact the MAB continental shelf, such as Hurricane Irene in 2011, shear driven mixing of Cold Pool water across the thermocline has the potential to cool the oceans surface and reduce storm intensity. In this study we compare coastal ocean advection and mixing processes during Hurricane Sandy and Hurricane Arthur, an offshore tracking tropical cyclone in the summer of 2014, to demonstrate the range of potential storm impacts on the coastal ocean of the MAB. To perform this analysis we use data from advanced Slocum autonomous underwater glider deployments in each storm as well as the Regional Ocean Modeling System (ROMS).

With the growing trend of extreme weather events in the Northeast U.S., a region of dense vegetation, evaluating hazard effects of wind storms on power distribution systems becomes increasingly important for disaster preparedness and fast responses in utilities. In this paper, probabilistic wind storm models for the study region have been built by mining 160-year storm events recorded in the National Oceanic and Atmospheric Administration's Atlantic basin hurricane database (HURDAT). Further, wind storms are classified into six categories according to NOAA criteria and IEEE standard to facilitate the evaluation of distribution system responses under different levels of hazards. The impacts of wind storms in all categories are accurately evaluated through a Sequential Monte Carlo method enhanced by a temporal wind storm sampling strategy. Extensive studies for the selected typical distribution system indicate that our models and methods effectively reveal the hazardous effects of wind storms in the study region, leading to useful insights towards building better system hardening schemes.

Hurricane Irene followed a track that curved northward over the Bahamas and ran directly over the U.S. east coast from Cape Hatteras to New England in August of 2011, causing severe storm surges, intense inland flooding, loss of life and over $8 billon in storm damage. While the ensemble of atmospheric forecast models accurately predicted the hurricane timing and track, the hurricane intensity was consistently over-predicted. Data from the U.S. Integrated Ocean Observing System (IOOS) were used to better understand the potential impact of the Mid-Atlantic Bight's coastal ocean on the Hurricane Irene intensity forecast.

This work examines the potential value of the U.S. Federal Communications Commission “Katrina order” and discusses benefits and practicality of technology alternatives. The analysis is based on the effects of 2008 hurricanes Dolly, Gustav, and Ike through extensive supportive photographic evidence from on-site surveys. This information is compared with Hurricane Katrina's data. The analysis seems to indicate that the “Katrina Order” may not address some important issues, and that other technical approaches may provide a better solution.

In August and September 2008, three hurricanes (Gustav, Hanna, and Ike) formed in the western Atlantic, one right after the other, and headed for the U.S. Three-day composites of Sea Surface Temperature (SST) from The Tropical Rainfall Measuring Mission's (TRMM) Microwave Imager (TMI) of the Gulf of Mexico and the western Atlantic during the time of these hurricanes show cold wakes for all three hurricanes: SST after each hurricane is less than SST before each hurricane along and around the hurricane's path (especially to the right of the path) thus creating a cold wake. The cold wake for Ike in the Gulf of Mexico in mid-September has an area where the temperature difference is particularly great. Katrina, the hurricane that devastated New Orleans and parts of the Gulf Coast in August 2005, also has a pronounced cold wake.

The objective of our research is to develop a framework to perform a systematic and comprehensive analysis of land use, land cover (LULC) change along the historical record of the terrestrial tracks of hurricanes and tropical storms since the beginning of the earth observation satellite era. Here we present a phenological disturbance filter based on MODIS vegetation indices to detect and characterize the impact of Hurricane Isabel, which made landfall on the Outer Banks in North Carolina on 18th September 2003. The results show that woody wetland areas have a pronounced and localized decrease in phenological activity in the two following years, likely due to the disturbance created by flooding, erosion and wind damage. At the regional scale, we identify a relationship between vegetation stress measured by the persistence of below average EVI anomalies, and the frequency of hurricane and tropical storm in the coastal plain of North Carolina. This analysis also shows a direct link between hurricanes and tropical storms (TS) and drought relief in this region.

The Canadian Space Agency's Hurricane Watch program monitors tropical cyclones worldwide and acquires RADARSAT-1 Synthetic Aperture Radar imagery to provide experimental datasets to the scientific research community interested in surface wind field studies. The current HW archives spans from 1999 to 2006 and contain a variety of tropical cyclones from around the world. The images show various storm development stages, and morphological characteristics. To further promote the initiative, CSA is about to provide processed images to the scientific community through an Announcement of Opportunity. In this paper, we will demonstrate how simulations of extensive acquisition plans over the Atlantic basin can provide an improved planning strategy to increase the number of valuable images.

The large waves caused by Hurricane Ivan have received considerable media coverage because of the extensive damage they wrought on the offshore oil industry and on the coastal areas of the Gulf of Mexico. It has been speculated that the associated wave conditions correspond to the 1000-year event and that criteria for designing offshore structures in the Gulf of Mexico may need revision. Here, we describe one analysis of all of the measurements from NDBC buoys in the Gulf of Mexico and elsewhere in US waters, with a view to placing Hurricane Ivan's waves in the context of other measurements. The largest significant wave heights (SWH's) measured during Hurricane Ivan in the Gulf of Mexico rival the largest waves ever recorded in all US waters. This is noteworthy because, on a return period basis, the Gulf of Mexico has the smallest wave climate compared with all other regions around the US. At four locations in the Gulf of Mexico, the SWH's were the largest ever recorded at those locations, and exceeded the previous biggest waves by a significant margin. Wave-induced velocities are estimated to be as high as 3.5 m/s at some locations, which may have contributed to the extensive mud, sediment, and pipeline movements that have been reported. Calculations based on the admittedly short-duration datasets suggest that the some SWH's measured during Hurricane Ivan may correspond to recurrence intervals of the order of several thousand years.

Under the NASA/FAR Program, a study has been established to investigate air-sea interactions associated with the formation and development of Hurricane Gordon in the Gulf of Mexico. Hurricane Gordon first began as a weak disturbance off the eastern shore of the Yucatan Peninsula on September 10th, 2000. The area of disturbed weather moved onshore then offshore again on the northern coast of the Yucatan Peninsula. The convection developed a surface low and was named Tropical depression number 11. It then strengthened, becoming a named tropical storm, Gordon, on September 15th and then a minimal hurricane on September 16th as it neared the Florida Panhandle. It weakened to tropical storm status late on September 17th, a few hours before it made landfall. NOAA buoy data from the National Data Buoy Center are used in this study. Remote Sensing GOES and AVHRR satellite data from NOAA are used as well. These data were used in the calculation of heat, momentum, and moisture fluxes. The study indicated that (a) average sea-surface temperatures over the Gulf of Mexico were about 29/spl deg/C, and (b) the air-sea inter phase was a maximum 3-4 days before the storm developed. We further investigate to development of predictive models including (i) a regression model, and (ii) a Hurricane Predictive Index, for forecasting the formation and development of Hurricane Gordon that occurred during September 11-20, 2000.

Whenever a hurricane threatens to strike a coast, it is desirable to have an estimate of the height of the peak storm surge. Jelesnianski combined empirical data from Conner, et al., and Harris with his theoretical calculations to produce a set of nomograms that permit the estimation of peak surge for any geographical location when a few parameters characterizing a storm are known. Russo has used these nomograms to develop a simple formula for estimating the potential storm surge. The data from 52 storms that entered land during the period from 1893 to 1957 are used to develop the formula. Consideration is given to such factors as: (1) radius to maximum winds; (2) hurricane forward speed; (3) angle of approach to the coastline; (4) bathymetry (bottom topography); and (5) central pressure. Predictions using the formula are compared to measured data for numerous storms. A table is presented depicting worst case scenarios for selected coastal cities.