Risk assessment of hurricane winds for Eglin Air Force Base in northwestern Florida, USA

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Scheitlin, K. N., J. B. Elsner, S. W. Lewers, J. C. Malmstadt, and T. H. Jagger, 2011: Risk assessment of hurricane winds for Eglin Air Force Base in northwestern Florida, USA, Theoretical and Applied Climatology, DOI: 10.1007/s00704-010-0386-4

Hurricane winds present a significant hazard for coastal infrastructure. An estimate of the local risk of extreme wind speeds is made using a new method that combines historical hurricane records with a deterministic wind field model. The method is applied to Santa Rosa, Island located in the northwestern panhandle region of Florida, USA. First, a hurricane track is created for a landfall location on the island that represents the worst-case scenario for Eglin Air Force Base (EAFB). The track is based on averaging the paths of historical
hurricanes in the vicinity of the landfall location. Second, an extreme-value statistical model is used to estimate 100-year wind speeds at locations along the average track based again on historical hurricanes in the vicinity of the track locations. Third, the 100-year wind speeds together with information about hurricane size and forward speed are used as input to the HAZUS hurricane wind field model to produce a wind swath across EAFB. Results show a 100-year hurricane wind gust on Santa Rosa Island of 58 (± 5) m s−1 (90% CI).

Hurricanes and Climate Change, Volume 2

James B. Elsner, Robert E. Hodges, Jill C. Malmstadt, Kelsey N. Scheitlin, Eds. (2010)

Diurnal temperature range variability due to land cover and air mass types in the Southeast

Scheitlin, Kelsey N., P. Grady Dixon, 2010: Diurnal Temperature Range Variability due to Land Cover and Airmass Types in the Southeast. J. Appl. Meteor. Climatol., 49, 879-888, doi: 10.1175/2009JAMC2322.1

This study examines the relationship between diurnal temperature range (DTR) and land use/land cover (LULC) in a portion of the southeast United States. Temperature data for all synoptically-weak days within a ten-year period are gathered from the National Climatic Data Center for 144 weather stations. Each station is classified as one of the following LULC types: urban, agriculture, evergreen forest, deciduous forest, pine forest or mixed forest. A three-way analysis of variance and paired samples t tests are used to test for significant DTR differences due to LULC, month, and air mass type. The LULC types display two clear groups according to their DTR, with agricultural and urban areas consistently experiencing the smallest DTRs, and the forest types experiencing greater DTRs. The dry air masses seem to enhance the DTR differences between vegetated LULC types by emphasizing the differences in evapotranspiration. Meanwhile, the high moisture content of moist air masses prohibits extensive evapotranspirational cooling in the vegetated areas. This lessens the DTR differences between vegetated LULC types, while enhancing the differences between vegetated land and urban areas. All of the LULC types exhibit an annual bimodal DTR pattern with peaks in April and October. Since both vegetated and non-vegetated areas experience the bimodal pattern, this may conflict with previous research that names seasonal changes in evapotranspiration as the most probable cause for the annual trend. These findings suggest that air mass type has a larger and more consistent influence on the DTR of an area than LULC type, and therefore may play a role in causing the bimodal DTR pattern, altering DTR with the seasonal distribution of air mass occurrence.

Toward increased utilization of historical hurricane chronologies

Scheitlin, K. N., J. B. Elsner, J. C. Malmstadt, R. E. Hodges, and T. H. Jagger, 2010: Toward increased utilization of historical hurricane chronologies, J. Geophys. Res., 115, D03108, doi:10.1029/2009JD012424

The record of past tropical cyclones provides an important means to evaluate the hurricane hazard. Historical chronologies are a source of information about tropical cyclones prior to the modern era. Chenoweth [2006] describes an archive of 383 tropical cyclones occurring during the 18th and 19th centuries, largely before the official hurricane record. The present study demonstrates a novel way this archive can be used to articulate historical tropical cyclone activity across space. First, an event in the archive is assigned a series of latitude/longitude coordinates approximating the descriptive locations of the cyclone’s affect. Second, tropical cyclones from the modern record that approach these locations (modern analogs) are mapped. Third, a probable pathway and a realistic track of the archived event is created by averaging the modern analog tracks. As an example, the procedure is used to generate a map showing the tracks of the Atlantic tropical cyclones of 1766. Sensitivity of the methodology to changes in event location and event timing are considered. The study shows that historical hurricane chronologies when combined with a history of cyclone tracks can provide useful information about the older events that is not directly related to where the original information was gathered. When this information is available for all cyclones it should help climatologists better understand long-term variations in tropical cyclone activity.

Florida hurricanes and damage costs

Malmstadt, J., K. Scheitlin, J. Elsner, 2009: Florida hurricanes and damage costs. Southeastern Geographer, 49, 108–131

Florida has been visited by some of the most destructive and devastating hurricanes on record in the United States causing well over $450 billion in damage since the early 20th century. The value of insured property in Florida against windstorm damage is the highest in the nation and on the rise. The frequency and severity of hurricanes affecting Florida are examined from the best set of available data and the damages are related to characteristics of the storms at landfall. Results show that normalized losses are increasing over time consistent with small increases in hurricane intensity and hurricane size. The best predictor of potential losses is minimum central pressure. Hurricane size alone or in combination with hurricane intensity does not improve on the simpler relationship. An estimate of potential losses from hurricanes can be obtained using a formula involving only a forecast of the minimum pressure at landfall. The ability to estimate potential losses in Florida will increase the ability to estimate losses in other areas of the United States, and will also allow policy makers and insurance companies to provide relevant information to the concerned public.

Predicting Atlantic hurricane paths using monthly surface pressure data

Dixon, P. G., M. E. Brown, M. C. Carter, W. S. Gunter, J. S. Allen, A. M. Hayes, L. E. Becker, H. S. Eschete, R. P. Aylward, and K. N. Scheitlin, 2008: Predicting Atlantic hurricane paths using monthly surface pressure data, The Geographical Bulletin,  49, 77–86

Previous research has had some success in predicting likely tracks of tropical cyclones in the Atlantic basin using North Atlantic Oscillation (NAO) anomalies (above or below average values) during preceding months. This paper expands on this research by incorporating other surface pressure values as independent variables as alluded to by some of the earliest NAO research. We examine monthly sea-level-pressure (SLP) data from Reykjavik (Iceland), Cape Hatteras (North Carolina), and Nassau (Bahamas), along with NAO index anomalies, to see if they can be used to predict future paths and landfall locations of Atlantic tropical cyclones during the period 1970–2005. Average SLP from Nassau during the preceding May and June shows the strongest correlations with tropical cyclone tracks, with increased values correlated with more cyclones impacting the southeastern United States, but fewer landfalls along the Gulf of Mexico. Results also show virtually no relationship between the storm variables tested and the NAO index.

Effects of temperature variation on suicide in five U.S. counties, 1991–2001

Dixon, P. G.,  A. N. McDonald, K. N. Scheitlin, J. E. Stapleton, J. S. Allen, W. M. Carter, M. R. Holley, D. D. Inman, and J. B. Roberts, 2007: Effects of temperature variation on suicide in five U.S. counties, 1991-2001. International Journal of Biometeorology,  51, 395–403

Effects of weather variables on suicide are well-documented, but there is still little consistency among the results of most studies. Nevertheless, most studies show a peak in suicides during the spring season, and this is often attributed to increased temperatures. The purpose of this study is to test the relationship between monthly temperature and monthly suicide, independent of months or seasons, for five counties located across the United States. Harmonic analysis shows that four of the five counties display some seasonal components in the suicide data. However, simple linear regression shows no correlation between suicide and temperature, and discriminant analysis shows that monthly departure from mean annual suicide rates is not a useful tool for identifying months with temperatures that are colder or warmer than the annual average. Therefore, it appears that the seasonality of suicides is due to factors other than temperature.