Search Results
Abstract
The recent development of the global positioning system (GPS) dropwindsonde has allowed the wind and thermodynamic structure of the hurricane eyewall to be documented with unprecedented accuracy and resolution. In an attempt to assist operational hurricane forecasters in their duties, dropwindsonde data have been used in this study to document, for the first time, the mean vertical profile of wind speed in the hurricane inner core from the surface to the 700-hPa level, the level typically flown by reconnaissance aircraft. The dropwindsonde-derived mean eyewall wind profile is characterized by a broad maximum centered 500 m above the surface. In the frictional boundary layer below this broad maximum, the wind decreases nearly linearly with the logarithm of the altitude. Above the maximum, the winds decrease because of the hurricane's warm core. These two effects combine to give a surface wind that is, on average, about 90% of the 700-hPa value. The dropwindsonde observations largely confirm recent operational practices at the National Hurricane Center for the interpretation of flight-level data. Hurricane wind profiles outside of the eyewall region are characterized by a higher level of maximum wind, near 1 km, and a more constant wind speed between 700 hPa and the top of the boundary layer. Two factors that likely affect the eyewall profile structure are wind speed and vertical motion. A minimum in surface wind adjustment factor (i.e., relatively low surface wind speeds) was found when the wind near the top of the boundary layer was between 40 and 60 m s−1. At higher wind speeds, the fraction of the boundary layer wind speed found at the surface increased, contrary to expectation. Low-level downdrafts, and enhanced vertical motion generally, were also associated with higher relative surface winds. These results may be of interest to engineers concerned with building codes, to emergency managers who may be tempted to use high-rise buildings as a “refuge of last resort” in coastal areas, and to those people on locally elevated terrain. The top of a 25-story coastal high-rise in the hurricane eyewall will experience a mean wind that is about 17% higher (or one Saffir–Simpson hurricane-scale category) than the surface or advisory value. For this reason, residents who must take refuge in coastal high-rises should generally do so at the lowest levels necessary to avoid storm surge.
Abstract
The recent development of the global positioning system (GPS) dropwindsonde has allowed the wind and thermodynamic structure of the hurricane eyewall to be documented with unprecedented accuracy and resolution. In an attempt to assist operational hurricane forecasters in their duties, dropwindsonde data have been used in this study to document, for the first time, the mean vertical profile of wind speed in the hurricane inner core from the surface to the 700-hPa level, the level typically flown by reconnaissance aircraft. The dropwindsonde-derived mean eyewall wind profile is characterized by a broad maximum centered 500 m above the surface. In the frictional boundary layer below this broad maximum, the wind decreases nearly linearly with the logarithm of the altitude. Above the maximum, the winds decrease because of the hurricane's warm core. These two effects combine to give a surface wind that is, on average, about 90% of the 700-hPa value. The dropwindsonde observations largely confirm recent operational practices at the National Hurricane Center for the interpretation of flight-level data. Hurricane wind profiles outside of the eyewall region are characterized by a higher level of maximum wind, near 1 km, and a more constant wind speed between 700 hPa and the top of the boundary layer. Two factors that likely affect the eyewall profile structure are wind speed and vertical motion. A minimum in surface wind adjustment factor (i.e., relatively low surface wind speeds) was found when the wind near the top of the boundary layer was between 40 and 60 m s−1. At higher wind speeds, the fraction of the boundary layer wind speed found at the surface increased, contrary to expectation. Low-level downdrafts, and enhanced vertical motion generally, were also associated with higher relative surface winds. These results may be of interest to engineers concerned with building codes, to emergency managers who may be tempted to use high-rise buildings as a “refuge of last resort” in coastal areas, and to those people on locally elevated terrain. The top of a 25-story coastal high-rise in the hurricane eyewall will experience a mean wind that is about 17% higher (or one Saffir–Simpson hurricane-scale category) than the surface or advisory value. For this reason, residents who must take refuge in coastal high-rises should generally do so at the lowest levels necessary to avoid storm surge.
Abstract
One hundred and thirty Omega dropwindsondes deployed within 500-km radius of the eye of six North Atlantic hurricanes are used to determine the magnitudes and trends in convective available potential energy, and 10–1500-m and 0–6-km shear of the horizontal wind as a function of radius, quadrant, and hurricane intensity.
The moist convective instability found at large radii (400–500 km) decreases to near neutral stability by 75 km from the eyewall. Vertical shears increase as radius decreases, but maximum shear values are only one-half of those found over land. Scatter for both the conditional instability and the shear is influenced chiefly by hurricane intensity, but proximity to reflectivity features does modulate the pattern. The ratio of the conditional instability to the shear (bulk Richardson number) indicates that supercell formation is favored within 250 km of the circulation center, but helicity values are below the threshold to support strong waterspouts.
The difference between these oceanic observations and those made over land by other researchers is evidence for significant modification of the vertical profile of the horizontal wind in a hurricane at landfall.
Abstract
One hundred and thirty Omega dropwindsondes deployed within 500-km radius of the eye of six North Atlantic hurricanes are used to determine the magnitudes and trends in convective available potential energy, and 10–1500-m and 0–6-km shear of the horizontal wind as a function of radius, quadrant, and hurricane intensity.
The moist convective instability found at large radii (400–500 km) decreases to near neutral stability by 75 km from the eyewall. Vertical shears increase as radius decreases, but maximum shear values are only one-half of those found over land. Scatter for both the conditional instability and the shear is influenced chiefly by hurricane intensity, but proximity to reflectivity features does modulate the pattern. The ratio of the conditional instability to the shear (bulk Richardson number) indicates that supercell formation is favored within 250 km of the circulation center, but helicity values are below the threshold to support strong waterspouts.
The difference between these oceanic observations and those made over land by other researchers is evidence for significant modification of the vertical profile of the horizontal wind in a hurricane at landfall.
Abstract
While qualitative information from meteorological satellites has long been recognized as critical for monitoring tropical cyclone activity, quantitative data are required to improve the objective analysis and numerical weather prediction of these events. In this paper, results are presented that show that the inclusion of high-density, multispectral, satellite-derived information into the analysis of tropical cyclone environmental wind fields can effectively reduce the error of objective track forecasts. Two independent analysis and barotropic track-forecast systems are utilized in order to examine the consistency of the results. Both systems yield a 10%–23% reduction in middle- to long-range track-forecast errors with the inclusion of the satellite wind observations.
Abstract
While qualitative information from meteorological satellites has long been recognized as critical for monitoring tropical cyclone activity, quantitative data are required to improve the objective analysis and numerical weather prediction of these events. In this paper, results are presented that show that the inclusion of high-density, multispectral, satellite-derived information into the analysis of tropical cyclone environmental wind fields can effectively reduce the error of objective track forecasts. Two independent analysis and barotropic track-forecast systems are utilized in order to examine the consistency of the results. Both systems yield a 10%–23% reduction in middle- to long-range track-forecast errors with the inclusion of the satellite wind observations.
Abstract
The Hurricane Forecast Improvement Project (HFIP; renamed the “Hurricane Forecast Improvement Program” in 2017) was established by the U.S. National Oceanic and Atmospheric Administration (NOAA) in 2007 with a goal of improving tropical cyclone (TC) track and intensity predictions. A major focus of HFIP has been to increase the quality of guidance products for these parameters that are available to forecasters at the National Weather Service National Hurricane Center (NWS/NHC). One HFIP effort involved the demonstration of an operational decision process, named Stream 1.5, in which promising experimental versions of numerical weather prediction models were selected for TC forecast guidance. The selection occurred every year from 2010 to 2014 in the period preceding the hurricane season (defined as August–October), and was based on an extensive verification exercise of retrospective TC forecasts from candidate experimental models run over previous hurricane seasons. As part of this process, user-responsive verification questions were identified via discussions between NHC staff and forecast verification experts, with additional questions considered each year. A suite of statistically meaningful verification approaches consisting of traditional and innovative methods was developed to respond to these questions. Two examples of the application of the Stream 1.5 evaluations are presented, and the benefits of this approach are discussed. These benefits include the ability to provide information to forecasters and others that is relevant for their decision-making processes, via the selection of models that meet forecast quality standards and are meaningful for demonstration to forecasters in the subsequent hurricane season; clarification of user-responsive strengths and weaknesses of the selected models; and identification of paths to model improvement.
Significance Statement
The Hurricane Forecast Improvement Project (HFIP) tropical cyclone (TC) forecast evaluation effort led to innovations in TC predictions as well as new capabilities to provide more meaningful and comprehensive information about model performance to forecast users. Such an effort—to clearly specify the needs of forecasters and clarify how forecast improvements should be measured in a “user-oriented” framework—is rare. This project provides a template for one approach to achieving that goal.
Abstract
The Hurricane Forecast Improvement Project (HFIP; renamed the “Hurricane Forecast Improvement Program” in 2017) was established by the U.S. National Oceanic and Atmospheric Administration (NOAA) in 2007 with a goal of improving tropical cyclone (TC) track and intensity predictions. A major focus of HFIP has been to increase the quality of guidance products for these parameters that are available to forecasters at the National Weather Service National Hurricane Center (NWS/NHC). One HFIP effort involved the demonstration of an operational decision process, named Stream 1.5, in which promising experimental versions of numerical weather prediction models were selected for TC forecast guidance. The selection occurred every year from 2010 to 2014 in the period preceding the hurricane season (defined as August–October), and was based on an extensive verification exercise of retrospective TC forecasts from candidate experimental models run over previous hurricane seasons. As part of this process, user-responsive verification questions were identified via discussions between NHC staff and forecast verification experts, with additional questions considered each year. A suite of statistically meaningful verification approaches consisting of traditional and innovative methods was developed to respond to these questions. Two examples of the application of the Stream 1.5 evaluations are presented, and the benefits of this approach are discussed. These benefits include the ability to provide information to forecasters and others that is relevant for their decision-making processes, via the selection of models that meet forecast quality standards and are meaningful for demonstration to forecasters in the subsequent hurricane season; clarification of user-responsive strengths and weaknesses of the selected models; and identification of paths to model improvement.
Significance Statement
The Hurricane Forecast Improvement Project (HFIP) tropical cyclone (TC) forecast evaluation effort led to innovations in TC predictions as well as new capabilities to provide more meaningful and comprehensive information about model performance to forecast users. Such an effort—to clearly specify the needs of forecasters and clarify how forecast improvements should be measured in a “user-oriented” framework—is rare. This project provides a template for one approach to achieving that goal.
Abstract
This study discusses the development of the Hurricane Forecast Improvement Program (HFIP) Corrected Consensus Approach (HCCA) for tropical cyclone track and intensity forecasts. The HCCA technique relies on the forecasts of separate input models for both track and intensity and assigns unequal weighting coefficients based on a set of training forecasts. The HCCA track and intensity forecasts for 2015 were competitive with some of the best-performing operational guidance at the National Hurricane Center (NHC); HCCA was the most skillful model for Atlantic track forecasts through 48 h. Average track input model coefficients for the 2015 forecasts in both the Atlantic and eastern North Pacific basins were largest for the European Centre for Medium-Range Weather Forecasts (ECMWF) deterministic model and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble mean, but the relative magnitudes of the intensity coefficients were more varied. Input model sensitivity experiments conducted using retrospective HCCA forecasts from 2011 to 2015 indicate that the ECMWF deterministic model had the largest positive impact on the skill of the HCCA track forecasts in both basins. The most important input models for HCCA intensity forecasts are the Hurricane Weather Research and Forecasting (HWRF) Model and the Coupled Ocean–Atmosphere Mesoscale Prediction System-Tropical Cyclone (COAMPS-TC) model initialized from the GFS. Several updates were incorporated into the HCCA formulation prior to the 2016 season. Verification results indicate HCCA continued to be a skillful model, especially for short-range (12–48 h) track forecasts in both basins.
Abstract
This study discusses the development of the Hurricane Forecast Improvement Program (HFIP) Corrected Consensus Approach (HCCA) for tropical cyclone track and intensity forecasts. The HCCA technique relies on the forecasts of separate input models for both track and intensity and assigns unequal weighting coefficients based on a set of training forecasts. The HCCA track and intensity forecasts for 2015 were competitive with some of the best-performing operational guidance at the National Hurricane Center (NHC); HCCA was the most skillful model for Atlantic track forecasts through 48 h. Average track input model coefficients for the 2015 forecasts in both the Atlantic and eastern North Pacific basins were largest for the European Centre for Medium-Range Weather Forecasts (ECMWF) deterministic model and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble mean, but the relative magnitudes of the intensity coefficients were more varied. Input model sensitivity experiments conducted using retrospective HCCA forecasts from 2011 to 2015 indicate that the ECMWF deterministic model had the largest positive impact on the skill of the HCCA track forecasts in both basins. The most important input models for HCCA intensity forecasts are the Hurricane Weather Research and Forecasting (HWRF) Model and the Coupled Ocean–Atmosphere Mesoscale Prediction System-Tropical Cyclone (COAMPS-TC) model initialized from the GFS. Several updates were incorporated into the HCCA formulation prior to the 2016 season. Verification results indicate HCCA continued to be a skillful model, especially for short-range (12–48 h) track forecasts in both basins.
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 National Hurricane Center issues analyses, forecasts, and warnings over large parts of the North Atlantic and Pacific Oceans, and in support of many nearby countries. Advances in observational capabilities, operational numerical weather prediction, and forecaster tools and support systems over the past 15–20 yr have enabled the center to make more accurate forecasts, extend forecast lead times, and provide new products and services. Important limitations, however, persist. This paper discusses the current workings and state of the nation’s hurricane warning program, and highlights recent improvements and the enabling science and technology. It concludes with a look ahead at opportunities to address challenges.
Abstract
The National Hurricane Center issues analyses, forecasts, and warnings over large parts of the North Atlantic and Pacific Oceans, and in support of many nearby countries. Advances in observational capabilities, operational numerical weather prediction, and forecaster tools and support systems over the past 15–20 yr have enabled the center to make more accurate forecasts, extend forecast lead times, and provide new products and services. Important limitations, however, persist. This paper discusses the current workings and state of the nation’s hurricane warning program, and highlights recent improvements and the enabling science and technology. It concludes with a look ahead at opportunities to address challenges.
