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Previous research has shown that people use a benchmark hurricane as part of their preparation and evacuation decision-making process. While hurricanes are a common occurrence along the Gulf Coast, research on personal memories of past storms is lacking. Particularly, how well do people remember the track and geophysical hazards (wind speed, storm surge, and total rainfall) of past storms? The accurate or inaccurate recollection and perception of previous storm details can influence personal responses to future storms, such as the decision to evacuate or take other life-saving actions. Survey responses of residents in Alabama and Mississippi were studied to determine if people were accurately able to recall a notable storm's name when seeing an image of the storm's track. Those who were able to identify the storm by its track were also asked if they could remember the storm's maximum reported rainfall, maximum sustained winds, and storm surge at landfall. Results showed that there were statistically significant differences between the levels of accurate recall for different storms, with Hurricanes Katrina and Michael having the most correct responses. Regardless of the storm, most people struggled to remember geophysical hazards. The results of this study are important as they can inform broadcast meteorologists and emergency managers on forecast elements of the storm to better emphasize in future communication in comparison to the actual values from historical benchmark storms. [ABSTRACT FROM AUTHOR]

Previous research has shown that people use a benchmark hurricane as part of their preparation and evacuation decision-making process. While hurricanes are a common occurrence along the Gulf Coast, research on personal memories of past storms is lacking. Particularly, how well do people remember the track and geophysical hazards (wind speed, storm surge, and total rainfall) of past storms? The accurate or inaccurate recollection and perception of previous storm details can influence personal responses to future storms, such as the decision to evacuate or take other life-saving actions. Survey responses of residents in Alabama and Mississippi were studied to determine if people were accurately able to recall a notable storm’s name when seeing an image of the storm’s track. Those who were able to identify the storm by its track were also asked if they could remember the storm’s maximum reported rainfall, maximum sustained winds, and storm surge at landfall. Results showed that there were statistically significant differences between the levels of accurate recall for different storms, with Hurricanes Katrina and Michael having the most correct responses. Regardless of the storm, most people struggled to remember geophysical hazards. The results of this study are important as they can inform broadcast meteorologists and emergency managers on forecast elements of the storm to better emphasize in future communication in comparison to the actual values from historical benchmark storms.

ABSTRACT Pan, Y.; Chen, Y.-P.; Yuan, J.-Y.; Liu, Y., and Xu, Z.-S., 2018. Error-Estimation Ensemble method in the forecasting of tropical cyclone tracks. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 771–775. Coconut Creek (Florida), ISSN 0749-0208. Tropical cyclones pose a great threat to coastal areas and accurate forecasting of their tracks is important for reducing and preventing coastal disasters. Multi-mode super-ensemble method was proposed to make full use of the forecasted tracks from different forecasting institutes. This paper proposed a modified multi-mode super-ensemble method, namely Error-Estimation Ensemble method, to overcome the shortcomings of traditional multi-mode super-ensemble method. The hypothesis, methodology and implementation of Error-Estimation Ensemble method are described. The EEE hindcast results of two typical tropical cyclones and all tropical cyclones that affects China coast are compared to those of four forecasting institutes. The comparison show that the EEE method reduces both the mean error and root-mean-square error of tropical cyclone track forecast, indicating that EEE method has better prediction accuracy and reliability. Discussions on present performance of EEE method and future works are present at last. [ABSTRACT FROM AUTHOR]

The article offers information on the hurricane season in Atlantic region in 2015. Among the topics discussed include the accumulated cyclone energy (ACE) value of hurricanes, the impact of Main Development Region (MDR) for hurricanes in Atlantic, and the significance of tracking hurricane activities and landfall.

US coastal cities are regularly subjected to destruction by tropical cyclones. The risk of tropical cyclone winds varies along the length of the coastline. We analyze landfalling North Atlantic basin tropical cyclones whose intensities are considered extreme relative to their landfall location. To be considered extreme, a tropical cyclone's wind speed must exceed the 50-year return level for a given city. Of interest is the spatial and temporal patterns of these extreme hurricane wind events for fifteen coastal cities, which are organized into four coastal regions: Northeast Atlantic, Southeast Atlantic, Florida, and Gulf. Findings suggest that extreme hurricanes along the Florida and Atlantic coasts cluster in time, specifically decades, while there is no temporal clustering detected along the Gulf. Atlantic coast hurricane clusters are in part due to the likelihood of one intense hurricane impacting multiple coastal cities, which is unlikely to happen along the Gulf due to the alignment of the coast. It is also unlikely for an intense hurricane to impact multiple Florida cities as an extreme hurricane, suggesting a physical mechanism enables the temporal clustering seen here. The results of this work advocate for annual and decadal hurricane risk to include: (1) the likelihood of temporal clusters of extreme hurricanes along the Atlantic and Florida coasts and (2) extreme hurricanes impacting multiple cities along the Atlantic coast. [ABSTRACT FROM AUTHOR]

A statistical procedure for estimating the risk of strong winds from hurricanes, known as the Hurricane Risk Calculator, is demonstrated and applied to several major cities in Louisiana. The procedure provides an estimate of wind risk over different length periods and can be applied to any location experiencing this hazard. Results show that an area 100 km around the city of New Orleans can expect to see hurricane winds blowing at 49 ms (44.3-53.7) [90 % confidence interval (CI)] or stronger, on average, once every 20 years. In comparison, for the same time period, the capital city of Baton Rouge and the surrounding area can expect to see hurricane winds of 43 ms (38.2-47.8) (90 % CI) or stronger. Hurricane track direction is also analyzed at the cities of interest. For Morgan City, Lafayette, Lake Charles, and Alexandria, tropical cyclones with winds at least 18 ms travel from the southeast to northwest. New Orleans and Baton Rouge tropical cyclones have a greater tendency to turn toward the east while within 100 km of the city, historically giving them a southwesterly approach. Tropical cyclones within 350 km off the south-central Louisiana coast occur most often in September, and the most extreme of these events are becoming stronger through time as shown with quantile regression. [ABSTRACT FROM AUTHOR]

In the present investigation the atmospheric model MM5 in its version 3 has been used as platform to obtain the winds produced by meteorological phenomena, more specifically, by hurricanes. In order to establish this model, several simulations with different implementation variants were carried out. Also, four of the strongest hurricanes that have ever come close or across the Cuban island were selected as study cases. Based on a statistical analysis for each one of the variants and comparisons made against two NOAA buoys located in the gulf of Mexico, the best option to establish the model MM5v3 was decided, taking into account the need to obtain reliable results in the least possible computational time. [ABSTRACT FROM AUTHOR]

Synthetic hurricane track data generated from a downscaling approach are compared to best-track (observed) data to analyze differences in regional frequency, intensity, and sensitivity of limiting intensity to sea surface temperature (SST). Overall, the spatial distributions of observed and simulated hurricane counts match well, although there are relatively fewer synthetic storms in the eastern quarter of the basin. Additionally, regions of intense synthetic hurricanes tend to coincide with regions of intense observed hurricanes. The sensitivity of limiting hurricane intensity to SST computed from synthetic data is slightly lower than sensitivity computed from observed data (5.5 ± 1.31 m s−1 (standard error, SE) and 8.6 ± 1.57 m s−1 (SE), respectively); however, the synthetic data produce sensitivity values that are much closer to the observed values than those obtained from two global climate models (GCMs) in a previous study. Despite a close match in the magnitude of basin wide sensitivities, the spatial variability of sensitivities do not match. These values tend to be highest in the western portion of the basin for the observed data, while the opposite is true for the synthetic data. [ABSTRACT FROM AUTHOR]

The article focuses on the meteorological study and impact of Hurricane Sandy in the U.S. It mentions that Sandy's tropical phase spanned in a five days storm which incubated from a tropical easterly wave of Africa and on October 29-30, 2012 the storm invaded an extratropical transition and declared as an extra tropical system in October 30, 2012 with a 90 minute per hour movement. It adds that the superstorm Sandy has left a wide range of damage in U.S. establishments and houses.

The article discusses advances in computer power and the development of novel methods of observation in weather prediction. The author notes that computer models have outperformed humans in forecasting weather since the 1990s, but that humans are better at forecasting the beginnings of hurricanes. Topics include the challenges of hurricane forecasting, the development of increasingly accurate computer models, and the track record of the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England. Also discussed are the computing power of the U.S. National Weather Service (NWS) and hurricane tracking errors of the National Hurricane Center (NHC) in Miami, Florida.

An investigation is conducted to determine how improvements in observing capabilities and technology may have affected scientists' ability to detect and monitor Saffir-Simpson Hurricane Wind Scale Category 5 hurricanes in the Atlantic Ocean basin during the mid-twentieth century. Previous studies state that there has been an increase in the number of intense hurricanes and attribute this increase to anthropogenic global warming. Other studies claim that the apparent increased hurricane activity is an artifact of better observational capabilities and improved technology for detecting these intense hurricanes. The present study focuses on the 10 most recent Category 5 hurricanes recorded in the Atlantic, from Hurricane Andrew (1992) through Hurricane Felix (2007). These 10 hurricanes are placed into the context of the technology available in the period of 1944-53, the first decade of aircraft reconnaissance. A methodology is created to determine how many of these 10 recent Category 5 hurricanes likely would have been recorded as Category 5 if they had occurred during this period using only the observations that likely would have been available with existing technology and observational networks. Late-1940s and early-1950s best-track intensities are determined for the entire lifetime of these 10 recent Category 5 hurricanes. It is found that likely only 2 of these 10-both Category 5 landfalling hurricanes-would have been recorded as Category 5 hurricanes if they had occurred during the late-1940s period. The results suggest that intensity estimates for extreme tropical cyclones prior to the satellite era are unreliable for trend and variability analysis. [ABSTRACT FROM AUTHOR]

The meteorological conditions of hurricanes passing near Puerto Rico (18N, 68W) are analyzed using composite daily reanalysis and satellite data. When an intense hurricane is present, the regional circulation is dominated by upper easterly flow over the Caribbean and central Atlantic and a surge of low-level westerly anomalies across the tropics. Warm SST anomalies extend along the coast of Venezuela, doubling the convective energy available to Caribbean hurricanes. Intensifying hurricanes tend to propagate westward with an atmospheric ridge over the Gulf Stream, in an environment with aerosol optical depth <0.6. Hurricanes form and strengthen in the east-shear phase of the Madden Julian Oscillation. Sinking motions and dry air appear in an anti-cyclonic gyre behind intensifying hurricanes. Numerical model 48-h forecasts of Caribbean hurricane tracks are analyzed over the period 2000-2010. A 'slow right' bias is found east of Puerto Rico in comparison with observed. [ABSTRACT FROM AUTHOR]

This letter evaluated the use of Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m Enhanced Vegetation Index (EVI) standard product data (MOD/MYD13Q1 C5) to map the damage caused by Hurricane Dean (August 2007) to the forests in the Yucatan Peninsula of Mexico using a two-step vetting procedure. Sequences of MODIS EVI 16-day composite products captured before and after the hurricane were compared against 93 field damage plots to select an appropriate set of pre- and post-damage data. Aqua pairwise combinations produced the highest damage detection overall accuracy compared with Terra (82.4% vs. 73.8%, respectively) because of advantageous timing of the Aqua EVI compositing, relative to the hurricane event. The most accurate EVI damage map (91.4% overall) revealed highest damage detection in Saffir-Simpson hurricane wind scale zone 5 (i.e. wind speed >248 km h-1, i.e. 95%), followed by 93% in zone 4 (210-249 km h-1) and 87% in zone 3 (178-209 km h-1). Results indicate that MODIS EVI products provide timely and accurate maps of hurricane damage in subtropical forests. [ABSTRACT FROM AUTHOR]

Two freely available, searchable databases that track the normalized interest in specific search queries, Google Trends and Google Insights, were used to illustrate spatial and temporal patterns in hurricane information seeking. Searches for the word 'hurricane' showed a seasonal pattern with spikes in hurricane searches that corresponded to the severity of the storms making landfall. Regional variation in 'hurricane' searches was largely driven by the location and magnitude of hurricane landfalls. Catastrophic hurricanes such as Hurricane Katrina captured national attention. A great deal of regional variation in search volume existed prior to Hurricane Ike's landfall. Not as much variation was seen before Hurricane Gustav and Tropical Storm Fay. This variation appeared to be related to changes in the 5-day track forecast as well as other factors such as issuance of watches and warnings. Searches from Louisiana experienced a sharp decrease after the 5-day track forecast shifted away from the state, but before Ike made landfall. Normalized daily visits to Weather Underground during August/September 2008 followed the same pattern as the Google searches. The most popular hurricane-related search terms at the national level prior to landfall dealt with forecast track and evacuation information while searches after landfall included terms related to hurricane damage. There are limitations to using this free data source, but the study has implications for the literature as well as practical applications. This study provides new information about online search behavior before a hurricane that can be utilized by those who provide weather information to the public. [ABSTRACT FROM AUTHOR]

Links between hurricane track changes and upper atmospheric potential vorticity (PV) anomaly patterns were identified qualitatively and analytically between 1990 and 2005 in the Western Atlantic. Strong track changes of hurricanes, particularly the constellations that triggered northward acceleration of the storm systems, were associated with upper-air PV patterns characterized by strongly positive anomalies to the northeast in combination with weak PV to the north of the system center. Constellations that triggered eventual eastward acceleration were associated with strongly positive PV anomalies to the northwest in combination with weak PV to the northeast of the system center. These results may assist hurricane forecasters and modelers in identifying possible signatures of future tropical cyclone tracks. [ABSTRACT FROM AUTHOR]

Evidence is provided that the global distribution of tropical hurricanes is principally determined by a universal function H of a single variable z that in turn is expressible in terms of the local sea surface temperature and latitude. The data-driven model presented here carries stark implications for the large increased numbers of hurricanes which it predicts for a warmer world. Moreover, the rise in recent decades in the numbers of hurricanes in the Atlantic, but not the Pacific basin, is shown to have a simple explanation in terms of the specific form of H(z), which yields larger percentage increases when a fixed increase in sea surface temperature occurs at higher latitudes and lower temperatures. [ABSTRACT FROM AUTHOR]

The article presents the European Centre for Medium-Range Weather Forecasts (ECMWF) model as the world's only major forecast simulation to pinpoint Hurricane Joaquin's track and predicted the left hook that brought Hurricane Sandy ashore in New Jersey. It notes that ECMWF is recognised as being at the forefront of how do data assimilation to get the most from worldwide weather observations as it uses a mathematical method called 4-dimensional variational data assimilation.

Subtropical cyclones (ST) have only recently gained attention as damaging weather systems. A set of criteria for identifying and classifying these systems is introduced here and employed to identify 18 ST cases forming in the 1999–2004 hurricane seasons. To be classified as an ST, these systems must have near-surface gale-force winds and show hybrid structure for more than one diurnal cycle. The 18 ST cases are partitioned into four classes based upon their genesis environments. Genesis over waters with SST in excess of 25°C is observed in almost 80% of warm-season cases, in contrast with only 55% in an ST climatology presented in a companion study. The low-shear magnitude constraint recognized for tropical cyclogenesis is less apparent for ST formation with over 50% forming in the two partitions characterized by shear in excess of 10 m s-1. This relatively high-shear environment corresponds to equatorward intrusion of upper troughs over the relatively warm SST present in the mid–late hurricane season. Anomaly composites confirm that ST genesis is associated with the intrusion of an upper trough in the westerlies into a region of relatively warm SST and weak static stability, with a corresponding reduction in the environmental shear near the time of ST genesis. These conditions correspond well with the conditions for tropical transition identified by Davis and Bosart. Indeed, these systems exhibit a propensity to continue development into a tropical cyclone; 80% eventually became named tropical systems. This result is consistent with a recent ST climatology but had not been widely recognized previously. This raises the possibility that tropical storms evolving from ST may have been overlooked or their tracks truncated in the National Hurricane Center Hurricane Database (HURDAT). [ABSTRACT FROM AUTHOR]

Under strong ocean surface wind conditions, the normalized radar cross section of synthetic aperture radar (SAR) is dampened at certain incident angles, compared with the signals under moderate winds. This causes a wind speed ambiguity problem in wind speed retrievals from SAR, because two solutions may exist for each backscattered signal. This study shows that the problem is ubiquitous in the images acquired by operational space-borne SAR sensors. Moreover, the problem is more severe for the near range and range travelling winds. To remove this ambiguity, a method was developed based on characteristics of the hurricane wind structure. A SAR image of Hurricane Rita (2005) was analysed to demonstrate the wind speed ambiguity problem and the method to improve the wind speed retrievals. Our conclusions suggest that a speed ambiguity removal algorithm must be used for wind retrievals from SAR in intense storms and hurricanes. [ABSTRACT FROM AUTHOR]

The hurricane season of 2006 in the eastern North Pacific basin is summarized, and the individual tropical cyclones are described. Also, the official track and intensity forecasts of these cyclones are verified and evaluated. The 2006 eastern North Pacific season was an active one, in which 18 tropical storms formed. Of these, 10 became hurricanes and 5 became major hurricanes. A total of 2 hurricanes and 1 tropical depression made landfall in Mexico, causing 13 direct deaths in that country along with significant property damage. On average, the official track forecasts in the eastern Pacific for 2006 were quite skillful. No appreciable improvement in mean intensity forecasts was noted, however. [ABSTRACT FROM AUTHOR]

A simplified dynamical system for tropical cyclone intensity prediction based on a logistic growth equation (LGE) is developed. The time tendency of the maximum sustained surface winds is proportional to the sum of two terms: a growth term and a term that limits the maximum wind to an upper bound. The maximum wind evolution over land is determined by an empirical inland wind decay formula. The LGE contains four free parameters, which are the time-dependent growth rate and maximum potential intensity (MPI), and two constants that determine how quickly the intensity relaxes toward the MPI. The MPI is estimated from an empirical formula as a function of sea surface temperature and storm translational speed. The adjoint of the LGE provides a method for finding the other three free parameters to make the predictions as close as possible to the National Hurricane Center best-track intensities. The growth rate is assumed to be a linear function of the vertical shear (S), a convective instability parameter (C) determined from an entraining plume, and their product, where both S and C use global model fields as input. This assumption reduces the parameter estimation problem to the selection of six constants. Results show that the LGE optimized for the full life cycle of individual storms can very accurately simulate the intensity variations out to as long as 15 days. For intensity prediction, single values of the six constants are found by fitting the model to more than 2400 Atlantic forecasts from 2001 to 2006. Results show that the observed intensity variations can be fit more accurately with the LGE than with the linear Statistical Hurricane Intensity Prediction Scheme (SHIPS) formulation, and with a much smaller number of constants. Results also show that LGE model solution (and some properties of real storms) can be explained by the evolution in the two-dimensional S–C phase space. Forecast and other applications of the LGE model are discussed. [ABSTRACT FROM AUTHOR]

Hurricane wind speeds at a given site are related to the intensity of the storm and the distance and direction from the storm center. As a result, forest damage is expected to vary predictably with respect to location relative to the storm track. To determine whether patterns of forest response along the track of a major hurricane in coastal New England were consistent with the expected patterns of wind damage, we investigated tree growth responses to the storm in several study sites that are similar with respect to site conditions, vegetation, and disturbance history. Growth responses to a severe hurricane in 1944 varied predictably among study sites with respect to distance from the storm track. Sites closest to the storm track experienced lesser wind damage and exhibited minimal growth responses, whereas sites farther east of the storm track and closer to the area of maximum estimated wind speed were characterized by greater wind damage and growth changes. Variation in estimated wind speed among our study sites (5–10 m/s) is not much greater than anticipated increases in hurricane intensity predicted under future climate scenarios (3–7 m/s). Thus, our results suggest that the magnitude of anticipated increases in wind speeds associated with Atlantic hurricanes may be sufficient to cause changes in forest response. [ABSTRACT FROM AUTHOR]

Atmospheric gravity waves are known to influence global circulations. Understanding these waves and their sources help to develop parameterizations that include their effects in climate and weather forecasting models. Deep convection is believed to be a major source for these waves and hurricanes may be particularly intense sources. Simulations of Hurricane Humberto (2001) are studied using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5). Humberto is simulated at both tropical storm and hurricane stages. Fourier transform and wavelet analysis are employed to investigate wave characteristics and their behavior in the lower stratosphere. The Fourier analysis gives a regional view of storm affects, whereas wavelet analysis gives a local picture of isolated events. Analysis of the movement of convective sources and local winds gives further insight into the mechanisms that can cause gravity waves. Convectively generated gravity waves are observed in the lower stratosphere of this model with horizontal scales of 15–300 km, vertical scales of 4–8 km, and intrinsic periods of approximately 20–100 min. [ABSTRACT FROM AUTHOR]

Using an idealized landfalling model hurricane, the impact of different land surface characteristics on hurricane rainfall distribution before, during, and after landfall is investigated. Before landfall, maximum rainfall occurs on the right side of the storm track as a result of dry air intrusion from both the environmental flow behind the vortex and the land surface ahead of the vortex. These sources of dry air combine to destabilize the right side and stabilize the left side of the storm. Upon landfall, the rainfall maximum shifts to the left of the storm track over land, near the coast. Increased friction over land drives a region of convergence in the entire front half of the storm. While mean rainfall rates decrease, localized areas of large rainfall accumulations may occur as a result of this frictional forcing. Over land, the rainfall area broadens and mean rainfall rates decrease. No differences are detected in inner-core rainfall rates between cases, but outer-core rainfall rates and rainfall coverage increase with moister land surfaces. Hence, significant differences in rainfall accumulations occur depending on moisture availability of the land surface. Since reconnaissance planes cannot fly over land, forecasters are often forced to make extrapolations from reconnaissance data over water. They should take extreme caution in doing so, since rainfall distributions may change suddenly upon landfall as different forcing mechanisms take over. [ABSTRACT FROM AUTHOR]

The article presents a study to improve the capability of hurricane intensity and structure forecasts by radar data assimilation using the landfall data of Hurricane Isabel in the U.S. on September 18, 2003. It says that tropical cyclone (TC) track improves well over the past years, but TC intensity forecasts have been recorded for its errors. This study will prove that the use of land-based Doppler radar observations in a mesoscale numerical weather prediction (NWP) model can improve TC intensity forecasts. An overview of the landfall data of hurricane Isabel is offered, along with the conducted radar observations. Meanwhile, the study finds out that the use of radar data assimilation has a potential for improving hurricane intensity and structure forecasts.

The article focuses on observations and findings on the implementation of mathematics tasks based on data about hurricanes. It demonstrates how mathematics teachers can take advantage of the interest of students about these real-life situations in developing their understanding of mathematical ideas. Topics including finding patterns and relationships, creating and interpreting graphs and examining rates of change are also discussed.

The eye of Hurricane Katrina passed within 49 n mi of an oceanographic observing system buoy in the Mississippi Bight that is part of the Central Gulf of Mexico Ocean Observing System. Although a mechanical anemometer failed on the buoy during the hurricane, a two-axis sonic anemometer survived and provided a complete record of the hurricane’s passage. This is the first reported case of a sonic anemometer surviving a hurricane and reporting validated data, and it demonstrates that this type of anemometer is a viable alternative to the mechanical anemometers traditionally used in marine applications. The buoy pitch and roll record during the storm show the importance of compensating the anemometer records for winds oblique to the horizontal plane of the anemometers. This is made apparent in the comparison between the two wind records from the anemometers during the hurricane. [ABSTRACT FROM AUTHOR]

Public officials with the authority to order hurricane evacuations face a difficult trade-off between risks to life and costly false alarms. Evacuation decisions must be made on the basis of imperfect information, in the form of forecasts. The quality of these decisions can be improved if they are also informed by measures of uncertainty about the forecast, including estimates of the value of waiting for updated, more accurate, forecasts. Using a stochastic model of storm motion derived from historic tracks, this paper explores the relationship between lead time and track uncertainty for Atlantic hurricanes and the implications of this relationship for evacuation decisions. Typical evacuation clearance times and track uncertainty imply that public officials who require no more than a 10% probability of failing to evacuate before a striking hurricane (a false negative) must accept that at least 76%--and for some locations over 90%--of evacuations will be false alarms. Reducing decision lead times from 72 to 48 hours for major population centers could save an average of hundreds of millions of dollars in evacuation costs annually, with substantial geographic variation in savings. [ABSTRACT FROM AUTHOR]

This study performs a set of Observing System Simulation Experiments (OSSEs) using Geostationary Operational Environmental Satellite (GOES) soundings. The primary objective of the OSSEs is to demonstrate that targeted observations can improve forecast accuracy by enhancing the initial conditions and mitigating their uncertainties. Hurricane Floyd (1999) is chosen as a study case. The main reason for choosing hurricane Floyd as a test case is that the movement of the storm was dictated by a mid-level complex polar jet steering flow region. This well-defined feature allowed us to examine the inaccuracy of analysis over the steering flow area using GOES soundings as targeted observations and its impact on the forecast track error. The set of experiments starts from a baseline forecast of hurricane Floyd using the Operational Multiscale Environment model with Grid Adaptivity (OMEGA). From GOES satellite soundings, atmospheric vertical profiles were extracted to simulate targeted observations. These data extracts were assimilated in the initial conditions to simulate new forecasts of hurricane Floyd which were then compared against both the baseline track and observed track. It was found that targeted observations in a forecast sensitive area can help to reduce hurricane forecast track error. Assimilation of only the subset of data (about 50 soundings) from the subjectively chosen fully sampled target region produced a considerable reduction of the track forecast errors (about 30%) within the first critical three days of the forecast. [ABSTRACT FROM AUTHOR]

The first part of the paper comprises of a control experiment and its forecasts validations with the observed. The PSU-NCAR mesoscale model MM5 was utilized at a horizontal resolution of 4 km using the data sets for hurricane Charley of 2004. The model configures some of the best available versions for physics and microphysical parameterizations schemes to produce forecasts which are close to the observed trend of hurricane Charley. The basic validations of the control run were carried out in terms of track, intensity (sea-level pressure and surface wind speed), storm propagation speed, precipitation and radar reflectivity with that of observed. The validations were necessary because this control experiment will be considered as a benchmark forecast for comparison with other microphysics sensitive experiments forecasts in the second part of this paper. In general, the control run forecasts closely comply with that of observed track and intensity of the hurricane Charley. We also note that control run manage to reproduce much of the important structural characteristics features of the hurricane as observed. [ABSTRACT FROM AUTHOR]

The 2004 and 2005 hurricane seasons dramatically demonstrated the magnitude of the societal significance of hurricanes, negatively impacting on all scales from the personal to the national. Although definitive identification of the forcing mechanisms controlling hurricane tracks and landfall patterns remains elusive, increasing evidence supports the hypothesis that the increase in hurricane activity along the Gulf Coast is due to a southwestward shift in the position of the Bermuda High. This research uses multiple visualization techniques to explore the spatial correlation between Bermuda High strengths - as interpreted from the North Atlantic Oscillation (NAO) index - and hurricane tracks. Using hurricane vector data from the National Oceanic and Atmospheric Administration (NOAA) Hurricane Data set (HURRDAT) and NAO index data since 1947, the hypothesized spatial relationships were investigated. Due to the vast number of storm track segments (more than 17,000), displaying all segments in the same map failed to reveal any coherent spatial pattern. For this reason, storm track segments were converted into a point coverage, each point representing the mid-point of an original storm segment. Other visualization methods were applied to this new point coverage, including choropleth mapping and continuous 2-D and enhanced 3-D surface displays. The latter two methods were novel approaches for the visualization of large numbers of hurricane tracks and can be applied to any large data sets consisting of linear features. Results visually support a spatial relationship between hurricane tracks and Bermuda High strengths. [ABSTRACT FROM AUTHOR]

This study is an observational analysis of the inner-core structure, sea surface temperature, outflow layer, and atmospheric boundary layer of an intense tropical cyclone whose intensity and structure is consistent with recent numerical and theoretical predictions of superintense storms. The findings suggest new scientific challenges for the current understanding of hurricanes. Unprecedented observations of the category-5 Hurricane Isabel (2003) were collected during 12–14 September. This two-part article reports novel dynamic and thermodynamic aspects of the inner-core structure of Isabel on 13 September that were made possible by analysis of these data. Here, a composite of the axisymmetric structure of the inner core and environment of Isabel is estimated using global positioning system dropwindsondes and in situ aircraft data. In Part II, an extreme wind speed observation on the same day is discussed in the context of this work. The axisymmetric data composite suggests a reservoir of high-entropy air inside the low-level eye and significant penetration of inflowing near-surface air from outside. The analysis suggests that the low-level air penetrating the eye is enhanced thermodynamically by acquiring additional entropy through interaction with the ocean and replaces air mixed out of the eye. The results support the hypothesis that this high-entropy eye air “turboboosts” the hurricane engine upon its injection into the eyewall clouds. Recent estimates of the ratio of sea-to-air enthalpy and momentum exchange at high wind speeds are used to suggest that Isabel utilized this extra power to exceed the previously assumed intensity upper bound by 10–35 m s-1 for the given environmental conditions. Additional study with other datasets is encouraged to further test the superintensity hypothesis. [ABSTRACT FROM AUTHOR]

The 2004 Atlantic basin hurricane season was one of the most active on record with nine hurricanes and six major hurricanes (maximum sustained winds > 49 m s 1) forming during the season. All six major hurricanes formed during August and September, causing this two-month period to be the most active on record. The primary reason the 2004 hurricane season will be remembered, however, is because of the four hurricanes that devastated the Caribbean and the southeastern United States (Hurricanes Charley, Frances, Ivan, and Jeanne). Estimated total U.S. hurricane damage was between $40 and $50 billion, and much additional damage was sustained in the Caribbean. It is shown that a very strong central Atlantic equatorial trough, associated with anomalously warm tropical Atlantic sea surface temperatures and anomalously weak tropospheric vertical wind shear, combined with extremely favorable midlatitude steering conditions to allow many of the Africa-spawned easterly waves to develop into major hurricanes in the central Atlantic. These major hurricanes then moved on long west-northwest tracks that brought them through the Caribbean and across the southeastern U.S. coastline. The very active and destructive 2004 Atlantic basin hurricane season is attributed to two primary features: a strong Atlantic equatorial trough and steering currents that caused hurricanes to track westward across the U.S. coastline. [ABSTRACT FROM AUTHOR]

The decision to prepare for an oncoming hurricane is typically framed as a static cost:loss problem, based on a strike-probability forecast. The value of waiting for updated forecasts is therefore neglected. In this paper, the problem is reframed as a sequence of interrelated decisions that more accurately represents the situation faced by a decision maker monitoring an evolving tropical cyclone. A key feature of the decision model is that the decision maker explicitly anticipates and plans for future forecasts whose accuracy improves as lead time declines. A discrete Markov model of hurricane travel is derived from historical tropical cyclone tracks and combined with the dynamic decision model to estimate the additional value that can be extracted from existing forecasts by anticipating updated forecasts, rather than incurring an irreversible preparation cost based on the instantaneous strike probability. The value of anticipating forecasts depends on the specific alternatives and cost profile of each decision maker, but conceptual examples for targets at Norfolk, Virginia, and Galveston, Texas, yield expected savings ranging up to 8% relative to repeated static decisions. In real-time decision making, forecasts of improving information quality could be used in combination with strike-probability forecasts to evaluate the trade-off between lead time and forecast accuracy, estimate the value of waiting for improving forecasts, and thereby reduce the frequency of false alarms. [ABSTRACT FROM AUTHOR]

From 1994 to 2003, fifty-five tropical cyclones entered the Canadian Hurricane Centre (CHC) Response Zone, or about 42% of all named Atlantic tropical cyclones in this ten-year period, and 2003 was the fourth consecutive year for a tropical cyclone to make landfall in Canada. The CHC forecasts all tropical cyclones that enter the CHC Response Zone and assumes the lead in forecasting once the cyclone enters its area of forecast responsibility. This study acknowledges the challenges of forecasting such tropical cyclones at extratropical latitudes. If a tropical cyclone has been declared extratropical, global models may no longer use vortex bogussing to carry the cyclone, and even if it is modeled, large model errors often result. The purpose of this study is to develop a new version of the Florida State University (FSU) hurricane superensemble with greater skill in tracking tropical cyclones, especially at extratropical latitudes. This has been achieved from the development of the synthetic superensemble, which is similar to the operational version of the multi-model superensemble that is used at FSU. The synthetic superensemble differs in that is has a larger set of member models consisting of regular member models, synthetic versions of these models, and the operational superensemble and its synthetic version. This synthetic superensemble is being used here to forecast hurricane tracks from the 2001, 2002, and 2003 hurricane seasons. The track forecasts from this method have generally less error than those of the member models, the operational superensemble, and the ensemble mean. This study shows that the synthetic superensemble performs consistently well and would be an asset to operational hurricane track forecasting. [ABSTRACT FROM AUTHOR]

Hurricanes are lethal and costly phenomena, and it is therefore of great importance to assess the long-term risk they pose to society. Among the greatest threats are those associated with high winds and related phenomena, such as storm surges. Here we assess the probability that hurricane winds will affect any given point in space by combining an estimate of the probability that a hurricane will pass within some given radius of the point in question with an estimate of the spatial probability density of storm winds. To assess the probability that storms will pass close enough to a point of interest to affect it, we apply two largely independent techniques for generating large numbers of synthetic hurricane tracks. The first treats each track as a Markov chain, using statistics derived from observed hurricanetrack data. The second technique begins by generating a large class of synthetic, time-varying wind fields at 850 and 250 hPa whose variance, covariance, and monthly means match NCEP-NCAR reanalysis data and whose kinetic energy follows an ω-3 geostrophic turbulence spectral frequency distribution. Hurricanes are assumed to move with a weighted mean of the 850- and 250-hPa flow plus a “beta drift” correction, after originating at points determined from historical genesis data. The statistical characteristics of tracks generated by these two means are compared. For a given point in space, many (∼104) synthetic tracks are generated that pass within a specified distance of a point of interest, using both track generation methods. For each of these tracks, a deterministic, coupled, numerical simulation of the storm's intensity is carried out, using monthly mean upper-ocean and potential intensity climatologies, together with time-varying vertical wind shear generated from the synthetic time series of 850- and 250-hPa winds, as described above. For the case in which the tracks are generated using the synthetic environmental flow, the tracks and the shear are generated using the same wind fields and are therefore mutually consistent. The track and intensity data are finally used together with a vortex structure model to construct probability distributions of wind speed at fixed points in space. These are compared to similar estimates based directly on historical hurricane data for two coastal cities. [ABSTRACT FROM AUTHOR]

The article discusses the steps use in Marcov chain synthetic track generation in statistical deterministic approach to hurricane risk assessment. It states that track propagation and genesis were use in the study. It also mentioned that in genesis, variable-resolution smoothing outweighs fixed-resolution smoothing. It is because under and overestimation of genesis frequency occurs in smoothing at a fixed resolution. In propagating tracks, several track integration methods was discussed as well as problems encountered with each methods.

Horizontal winds at 850 hPa from tropical cyclones retrieved using the nonlinear balance equation, where the mass field was determined from Advanced Microwave Sounding Unit (AMSU) temperature soundings, are compared with the surface wind fields derived from NASA's Quick Scatterometer (QuikSCAT) and Hurricane Research Division H*Wind analyses. It was found that the AMSU-derived wind speeds at 850 hPa have linear relations with the surface wind speeds from QuikSCAT or H*Wind. There are also characteristic biases of wind direction between AMSU and QuikSCAT or H*Wind. Using this information to adjust the speed and correct for the directional bias, a new algorithm was developed for estimation of the tropical cyclone surface wind field from the AMSU-derived 850-hPa winds. The algorithm was evaluated in two independent cases from Hurricanes Floyd (1999) and Michelle (2001), which were observed simultaneously by AMSU, QuikSCAT, and H*Wind. In this evaluation the AMSU adjustment algorithm for wind speed worked well. Results also showed that the bias correction algorithm for wind direction has room for improvement. [ABSTRACT FROM AUTHOR]

Puerto Rico is subject to frequent and severe impacts from hurricanes, whose long-term ecological role must be assessed on a scale of centuries. In this study we applied a method for reconstructing hurricane disturbance regimes developed in an earlier study of hurricanes in New England. Patterns of actual wind damage from historical records were analyzed for 85 hurricanes since European settlement in 1508. A simple meteorological model (HURRECON) was used to reconstruct the impacts of 43 hurricanes since I 851. Long-term effects of topography on a landscape scale in the Luquillo Experimental Forest (LEF) were simulated with a simple topographic exposure model (EXPOS). Average return intervals across Puerto Rico for F0 damage (loss of leaves and branches) and F! damage (scattered blowdowns, small gaps) on the Fujita scale were 4 and 6 years, respectively. At higher damage levels, a gradient was created by the direction of the storm tracks and the weakening of hurricanes over the interior mountains. Average return intervals for F2 damage (extensive blowdowns) and F3 damage (forests leveled) ranged from 15 to 33 years and 50 to 150 years, respectively, from east to west. In the LEF, the combination of steep topography and constrained peak wind directions created a complex mosaic of topographic exposure and protection, with average return intervals for F3 damage ranging from 50 years to >150 years. Actual forest damage was strongly dependent on land-use history and the effects of recent hurricanes. Annual and decadal timing of hunicanes varied widely. There was no clear centennial-scale trend in the number of major hurricanes over the historical period. [ABSTRACT FROM AUTHOR]

Evaluates the impact of enhanced satellite-derived winds on numerical hurricane track predictions through a series of experiments. Description of the forecast model, observational data and assimilation method; Impact of Geostationary Operational Environmental Satellites winds on Geophysical Fluid Dynamics Laboratory track forecasts; Challenges in the prediction of hurricane tracks.

Evaluates vertical motions of seven Atlantic tropical cyclones through use of data recorded by Doppler radars on research aircraft. Divisions of radial flight legs; Reflectivity patterns and profiles; Analysis of the vertical mass flux; Spatial correlations between typical vertical and horizontal velocities.