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- Author or Editor: Ethan J. Gibney x
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Abstract
Tropical cyclones pose a significant threat to life and property along coastal regions of the United States. As these systems move inland and dissipate, they can also pose a threat to life and property, through heavy rains, high winds, and other severe weather such as tornadoes. While many studies have focused on the impacts from tropical cyclones on coastal counties of the United States, this study goes beyond the coast and examines the impacts caused by tropical cyclones on inland locations. Using geographical information system software, historical track data are used in conjunction with the radial maximum extent of the maximum sustained winds at 34-, 50-, and 64-kt (1 kt ≈ 0.5 m s−1) thresholds for all intensities of tropical cyclones and overlaid on a 30-km equal-area grid that covers the eastern half of the United States. The result is a series of maps with frequency distributions and an estimation of return intervals for inland tropical storm– and hurricane-force winds. Knowing where the climatologically favored areas are for tropical cyclones, combined with a climatological expectation of the inland penetration frequency of these storms, can be of tremendous value to forecasters, emergency managers, and the public.
Abstract
Tropical cyclones pose a significant threat to life and property along coastal regions of the United States. As these systems move inland and dissipate, they can also pose a threat to life and property, through heavy rains, high winds, and other severe weather such as tornadoes. While many studies have focused on the impacts from tropical cyclones on coastal counties of the United States, this study goes beyond the coast and examines the impacts caused by tropical cyclones on inland locations. Using geographical information system software, historical track data are used in conjunction with the radial maximum extent of the maximum sustained winds at 34-, 50-, and 64-kt (1 kt ≈ 0.5 m s−1) thresholds for all intensities of tropical cyclones and overlaid on a 30-km equal-area grid that covers the eastern half of the United States. The result is a series of maps with frequency distributions and an estimation of return intervals for inland tropical storm– and hurricane-force winds. Knowing where the climatologically favored areas are for tropical cyclones, combined with a climatological expectation of the inland penetration frequency of these storms, can be of tremendous value to forecasters, emergency managers, and the public.
Abstract
The 1933 Atlantic hurricane season was extremely active, with 20 named storms and 11 hurricanes including 6 major (category 3+; 1-min maximum sustained winds ≥96 kt) hurricanes occurring. The 1933 hurricane season also generated the most accumulated cyclone energy (an integrated metric that accounts for frequency, intensity, and duration) of any Atlantic hurricane season on record. A total of 8 hurricanes tracked through the Caribbean in 1933—the most on record. In addition, two category 3 hurricanes made landfall in the United States just 23 h apart: the Treasure Coast hurricane in southeast Florida followed by the Cuba–Brownsville hurricane in south Texas. This manuscript examines large-scale atmospheric and oceanic conditions that likely led to such an active hurricane season. Extremely weak vertical wind shear was prevalent over both the Caribbean and the tropical Atlantic throughout the peak months of the hurricane season, likely in part due to a weak-to-moderate La Niña event. These favorable dynamic conditions, combined with above-normal tropical Atlantic sea surface temperatures, created a very conducive environment for hurricane formation and intensification. The Madden–Julian oscillation was relatively active during the summer and fall of 1933, providing subseasonal conditions that were quite favorable for tropical cyclogenesis during mid- to late August and late September to early October. The current early June and August statistical models used by Colorado State University would have predicted a very active 1933 hurricane season. A better understanding of these extremely active historical Atlantic hurricane seasons may aid in anticipation of future hyperactive seasons.
Abstract
The 1933 Atlantic hurricane season was extremely active, with 20 named storms and 11 hurricanes including 6 major (category 3+; 1-min maximum sustained winds ≥96 kt) hurricanes occurring. The 1933 hurricane season also generated the most accumulated cyclone energy (an integrated metric that accounts for frequency, intensity, and duration) of any Atlantic hurricane season on record. A total of 8 hurricanes tracked through the Caribbean in 1933—the most on record. In addition, two category 3 hurricanes made landfall in the United States just 23 h apart: the Treasure Coast hurricane in southeast Florida followed by the Cuba–Brownsville hurricane in south Texas. This manuscript examines large-scale atmospheric and oceanic conditions that likely led to such an active hurricane season. Extremely weak vertical wind shear was prevalent over both the Caribbean and the tropical Atlantic throughout the peak months of the hurricane season, likely in part due to a weak-to-moderate La Niña event. These favorable dynamic conditions, combined with above-normal tropical Atlantic sea surface temperatures, created a very conducive environment for hurricane formation and intensification. The Madden–Julian oscillation was relatively active during the summer and fall of 1933, providing subseasonal conditions that were quite favorable for tropical cyclogenesis during mid- to late August and late September to early October. The current early June and August statistical models used by Colorado State University would have predicted a very active 1933 hurricane season. A better understanding of these extremely active historical Atlantic hurricane seasons may aid in anticipation of future hyperactive seasons.
Abstract
Atlantic hurricane seasons have a long history of causing significant financial impacts, with Harvey, Irma, Maria, Florence, and Michael combining to incur more than 345 billion USD in direct economic damage during 2017–2018. While Michael’s damage was primarily wind and storm surge-driven, Florence’s and Harvey’s damage was predominantly rainfall and inland flood-driven. Several revised scales have been proposed to replace the Saffir–Simpson Hurricane Wind Scale (SSHWS), which currently only categorizes the hurricane wind threat, while not explicitly handling the totality of storm impacts including storm surge and rainfall. However, most of these newly-proposed scales are not easily calculated in real-time, nor can they be reliably calculated historically. In particular, they depend on storm wind radii, which remain very uncertain. Herein, we analyze the relationship between normalized historical damage caused by continental United States (CONUS) landfalling hurricanes from 1900–2018 with both maximum sustained wind speed (V max) and minimum sea level pressure (MSLP). We show that MSLP is a more skillful predictor of normalized damage than V max, with a significantly higher rank correlation between normalized damage and MSLP (r rank = 0.77) than between normalized damage and V max (r rank = 0.66) for all CONUS landfalling hurricanes. MSLP has served as a much better predictor of hurricane damage in recent years than V max, with large hurricanes such as Ike (2008) and Sandy (2012) causing much more damage than anticipated from their SSHWS ranking. MSLP is also a more accurately-measured quantity than is V max, making it an ideal quantity for evaluating a hurricane’s potential damage.
Abstract
Atlantic hurricane seasons have a long history of causing significant financial impacts, with Harvey, Irma, Maria, Florence, and Michael combining to incur more than 345 billion USD in direct economic damage during 2017–2018. While Michael’s damage was primarily wind and storm surge-driven, Florence’s and Harvey’s damage was predominantly rainfall and inland flood-driven. Several revised scales have been proposed to replace the Saffir–Simpson Hurricane Wind Scale (SSHWS), which currently only categorizes the hurricane wind threat, while not explicitly handling the totality of storm impacts including storm surge and rainfall. However, most of these newly-proposed scales are not easily calculated in real-time, nor can they be reliably calculated historically. In particular, they depend on storm wind radii, which remain very uncertain. Herein, we analyze the relationship between normalized historical damage caused by continental United States (CONUS) landfalling hurricanes from 1900–2018 with both maximum sustained wind speed (V max) and minimum sea level pressure (MSLP). We show that MSLP is a more skillful predictor of normalized damage than V max, with a significantly higher rank correlation between normalized damage and MSLP (r rank = 0.77) than between normalized damage and V max (r rank = 0.66) for all CONUS landfalling hurricanes. MSLP has served as a much better predictor of hurricane damage in recent years than V max, with large hurricanes such as Ike (2008) and Sandy (2012) causing much more damage than anticipated from their SSHWS ranking. MSLP is also a more accurately-measured quantity than is V max, making it an ideal quantity for evaluating a hurricane’s potential damage.
Abstract
Tropical cyclone intensity change remains a forecasting challenge with important implications for such vulnerable areas as the U.S. coast along the Gulf of Mexico. Analysis of 1979–2008 Gulf tropical cyclones during their final two days before U.S. landfall identifies patterns of behavior that are of interest to operational forecasters and researchers. Tropical storms and depressions strengthened on average by about 7 kt for every 12 h over the Gulf, except for little change during their final 12 h before landfall. Hurricanes underwent a different systematic evolution. In the net, category 1–2 hurricanes strengthened, while category 3–5 hurricanes weakened such that tropical cyclones approach the threshold of major hurricane status by U.S. landfall. This behavior can be partially explained by consideration of the maximum potential intensity modified by the environmental vertical wind shear and hurricane-induced sea surface temperature reduction near the storm center associated with relatively low oceanic heat content levels. Linear least squares regression equations based on initial intensity and time to landfall explain at least half the variance of the hurricane intensity change. Applied retrospectively, these simple equations yield relatively small forecast errors and biases for hurricanes. Characteristics of most of the significant outliers are explained and found to be identifiable a priori for hurricanes, suggesting that forecasters can adjust their forecast procedures accordingly.
Abstract
Tropical cyclone intensity change remains a forecasting challenge with important implications for such vulnerable areas as the U.S. coast along the Gulf of Mexico. Analysis of 1979–2008 Gulf tropical cyclones during their final two days before U.S. landfall identifies patterns of behavior that are of interest to operational forecasters and researchers. Tropical storms and depressions strengthened on average by about 7 kt for every 12 h over the Gulf, except for little change during their final 12 h before landfall. Hurricanes underwent a different systematic evolution. In the net, category 1–2 hurricanes strengthened, while category 3–5 hurricanes weakened such that tropical cyclones approach the threshold of major hurricane status by U.S. landfall. This behavior can be partially explained by consideration of the maximum potential intensity modified by the environmental vertical wind shear and hurricane-induced sea surface temperature reduction near the storm center associated with relatively low oceanic heat content levels. Linear least squares regression equations based on initial intensity and time to landfall explain at least half the variance of the hurricane intensity change. Applied retrospectively, these simple equations yield relatively small forecast errors and biases for hurricanes. Characteristics of most of the significant outliers are explained and found to be identifiable a priori for hurricanes, suggesting that forecasters can adjust their forecast procedures accordingly.
Abstract
The active 2020 Atlantic hurricane season produced 30 named storms, 14 hurricanes, and 7 major hurricanes (category 3+ on the Saffir–Simpson hurricane wind scale). Though the season was active overall, the final two months (October–November) raised 2020 into the upper echelon of Atlantic hurricane activity for integrated metrics such as accumulated cyclone energy (ACE). This study focuses on October–November 2020, when 7 named storms, 6 hurricanes, and 5 major hurricanes formed and produced ACE of 74 × 104 kt2 (1 kt ≈ 0.51 m s−1). Since 1950, October–November 2020 ranks tied for third for named storms, first for hurricanes and major hurricanes, and second for ACE. Six named storms also underwent rapid intensification (≥30 kt intensification in ≤24 h) in October–November 2020—the most on record. This manuscript includes a climatological analysis of October–November tropical cyclones (TCs) and their primary formation regions. In 2020, anomalously low wind shear in the western Caribbean and Gulf of Mexico, likely driven by a moderate-intensity La Niña event and anomalously high sea surface temperatures (SSTs) in the Caribbean, provided dynamic and thermodynamic conditions that were much more conducive than normal for late-season TC formation and rapid intensification. This study also highlights October–November 2020 landfalls, including Hurricanes Delta and Zeta in Louisiana and in Mexico and Hurricanes Eta and Iota in Nicaragua. The active late season in the Caribbean would have been anticipated by a statistical model using the July–September-averaged ENSO longitude index and Atlantic warm pool SSTs as predictors.
Abstract
The active 2020 Atlantic hurricane season produced 30 named storms, 14 hurricanes, and 7 major hurricanes (category 3+ on the Saffir–Simpson hurricane wind scale). Though the season was active overall, the final two months (October–November) raised 2020 into the upper echelon of Atlantic hurricane activity for integrated metrics such as accumulated cyclone energy (ACE). This study focuses on October–November 2020, when 7 named storms, 6 hurricanes, and 5 major hurricanes formed and produced ACE of 74 × 104 kt2 (1 kt ≈ 0.51 m s−1). Since 1950, October–November 2020 ranks tied for third for named storms, first for hurricanes and major hurricanes, and second for ACE. Six named storms also underwent rapid intensification (≥30 kt intensification in ≤24 h) in October–November 2020—the most on record. This manuscript includes a climatological analysis of October–November tropical cyclones (TCs) and their primary formation regions. In 2020, anomalously low wind shear in the western Caribbean and Gulf of Mexico, likely driven by a moderate-intensity La Niña event and anomalously high sea surface temperatures (SSTs) in the Caribbean, provided dynamic and thermodynamic conditions that were much more conducive than normal for late-season TC formation and rapid intensification. This study also highlights October–November 2020 landfalls, including Hurricanes Delta and Zeta in Louisiana and in Mexico and Hurricanes Eta and Iota in Nicaragua. The active late season in the Caribbean would have been anticipated by a statistical model using the July–September-averaged ENSO longitude index and Atlantic warm pool SSTs as predictors.
Abstract
The 2023 Atlantic hurricane season was above normal, producing 20 named storms, 7 hurricanes, 3 major hurricanes, and seasonal accumulated cyclone energy that exceeded the 1991–2020 average. Hurricane Idalia was the most damaging hurricane of the year, making landfall as a Category 3 hurricane in Florida, resulting in eight direct fatalities and 3.6 billion U.S. dollars in damage. The above-normal 2023 hurricane season occurred during a strong El Niño event. El Niño events tend to be associated with increased vertical wind shear across the Caribbean and tropical Atlantic, yet vertical wind shear during the peak hurricane season months of August–October was well below normal. The primary driver of the above-normal season was likely record warm tropical Atlantic sea surface temperatures (SSTs), which effectively counteracted some of the canonical impacts of El Niño. The extremely warm tropical Atlantic and Caribbean were associated with weaker-than-normal trade winds driven by an anomalously weak subtropical ridge, resulting in a positive wind–evaporation–SST feedback. We tested atmospheric circulation sensitivity to SSTs in both the tropical and subtropical Pacific and the Atlantic using the atmospheric component of the Community Earth System Model, version 2.3. We found that the extremely warm Atlantic was the primary driver of the reduced vertical wind shear relative to other moderate/strong El Niño events. The concentrated warmth in the eastern tropical Pacific in August–October may have contributed to increased levels of vertical wind shear than if the warming had been more evenly spread across the eastern and central tropical Pacific.
Abstract
The 2023 Atlantic hurricane season was above normal, producing 20 named storms, 7 hurricanes, 3 major hurricanes, and seasonal accumulated cyclone energy that exceeded the 1991–2020 average. Hurricane Idalia was the most damaging hurricane of the year, making landfall as a Category 3 hurricane in Florida, resulting in eight direct fatalities and 3.6 billion U.S. dollars in damage. The above-normal 2023 hurricane season occurred during a strong El Niño event. El Niño events tend to be associated with increased vertical wind shear across the Caribbean and tropical Atlantic, yet vertical wind shear during the peak hurricane season months of August–October was well below normal. The primary driver of the above-normal season was likely record warm tropical Atlantic sea surface temperatures (SSTs), which effectively counteracted some of the canonical impacts of El Niño. The extremely warm tropical Atlantic and Caribbean were associated with weaker-than-normal trade winds driven by an anomalously weak subtropical ridge, resulting in a positive wind–evaporation–SST feedback. We tested atmospheric circulation sensitivity to SSTs in both the tropical and subtropical Pacific and the Atlantic using the atmospheric component of the Community Earth System Model, version 2.3. We found that the extremely warm Atlantic was the primary driver of the reduced vertical wind shear relative to other moderate/strong El Niño events. The concentrated warmth in the eastern tropical Pacific in August–October may have contributed to increased levels of vertical wind shear than if the warming had been more evenly spread across the eastern and central tropical Pacific.
