Search Results
You are looking at 11 - 20 of 80 items for
- Author or Editor: John A. Knaff x
- Refine by Access: All Content x
Abstract
The 48-h intensity forecasts for Hurricane Pamela (2021) from numerical weather prediction models, statistical–dynamical aids, and forecasters were a major forecast bust with Pamela making landfall as a minor rather than major hurricane. From the satellite presentation, Pamela exhibited a symmetric pattern referred to as central cold cover (CCC) in the subjective Dvorak intensity technique. Per the technique, the CCC pattern is accompanied by arrested development in intensity despite the seemingly favorable convective signature. To understand forecast uncertainty during occurrences, central cold cover frequency from 2011 to 2021 is documented. From these cases, composites of longwave infrared brightness temperatures from geostationary satellites for CCC cases are presented, and the surrounding tropical cyclone large-scale environment is quantified and compared with other tropical cyclones at similar latitudes and intensities. These composites show that central cold cover has a consistent presentation, but varies in the preceding hours for storms that eventually intensify or weaken. And, the synoptic-scale environment surrounding the tropical cyclone thermodynamically supports the vigorous deep convection associated with CCC. Finally, intensity forecast errors from numerical weather prediction models and statistical–dynamical aids are examined in comparison to similar tropical cyclones. This work shows that guidance struggles during CCC cases with intensity errors from these models being in the lowest percentiles of performance, particularly for 24- and 36-h forecasts.
Significance Statement
The appearance of symmetric cold clouds near the center of developing tropical cyclones is most often associated with future intensification. This simple relationship is widely used by statistical tropical cyclone intensity forecast models. Here, we reexamine and confirm that one subjectively determined nighttime cold cyclone cloud pattern termed the “central cold cover” pattern in Vern Dvorak’s seminal technique for estimating tropical cyclone intensity from infrared satellite images is indeed related to slow or arrested development, and represents a failure mode for these simple forecast models.
Abstract
The 48-h intensity forecasts for Hurricane Pamela (2021) from numerical weather prediction models, statistical–dynamical aids, and forecasters were a major forecast bust with Pamela making landfall as a minor rather than major hurricane. From the satellite presentation, Pamela exhibited a symmetric pattern referred to as central cold cover (CCC) in the subjective Dvorak intensity technique. Per the technique, the CCC pattern is accompanied by arrested development in intensity despite the seemingly favorable convective signature. To understand forecast uncertainty during occurrences, central cold cover frequency from 2011 to 2021 is documented. From these cases, composites of longwave infrared brightness temperatures from geostationary satellites for CCC cases are presented, and the surrounding tropical cyclone large-scale environment is quantified and compared with other tropical cyclones at similar latitudes and intensities. These composites show that central cold cover has a consistent presentation, but varies in the preceding hours for storms that eventually intensify or weaken. And, the synoptic-scale environment surrounding the tropical cyclone thermodynamically supports the vigorous deep convection associated with CCC. Finally, intensity forecast errors from numerical weather prediction models and statistical–dynamical aids are examined in comparison to similar tropical cyclones. This work shows that guidance struggles during CCC cases with intensity errors from these models being in the lowest percentiles of performance, particularly for 24- and 36-h forecasts.
Significance Statement
The appearance of symmetric cold clouds near the center of developing tropical cyclones is most often associated with future intensification. This simple relationship is widely used by statistical tropical cyclone intensity forecast models. Here, we reexamine and confirm that one subjectively determined nighttime cold cyclone cloud pattern termed the “central cold cover” pattern in Vern Dvorak’s seminal technique for estimating tropical cyclone intensity from infrared satellite images is indeed related to slow or arrested development, and represents a failure mode for these simple forecast models.
Abstract
Tropical cyclone wind–pressure relationships are reexamined using 15 yr of minimum sea level pressure estimates, numerical analysis fields, and best-track intensities. Minimum sea level pressure is estimated from aircraft reconnaissance or measured from dropwindsondes, and maximum wind speeds are interpolated from best-track maximum 1-min wind speed estimates. The aircraft data were collected primarily in the Atlantic but also include eastern and central North Pacific cases. Global numerical analyses were used to estimate tropical cyclone size and environmental pressure associated with each observation. Using this dataset (3801 points), the influences of latitude, tropical cyclone size, environmental pressure, and intensification trend on the tropical cyclone wind–pressure relationships were examined. Findings suggest that latitude, size, and environmental pressure, which all can be quantified in an operational and postanalysis setting, are related to predictable changes in the wind–pressure relationships. These factors can be combined into equations that estimate winds given pressure and estimate pressure given winds with greater accuracy than current methodologies. In independent testing during the 2005 hurricane season (524 cases), these new wind–pressure relationships resulted in mean absolute errors of 5.3 hPa and 6.2 kt compared with the 7.7 hPa and 9.0 kt that resulted from using the standard Atlantic Dvorak wind–pressure relationship. These new wind–pressure relationships are then used to evaluate several operational wind–pressure relationships. These intercomparisons have led to several recommendations for operational tropical cyclone centers and those interested in reanalyzing past tropical cyclone events.
Abstract
Tropical cyclone wind–pressure relationships are reexamined using 15 yr of minimum sea level pressure estimates, numerical analysis fields, and best-track intensities. Minimum sea level pressure is estimated from aircraft reconnaissance or measured from dropwindsondes, and maximum wind speeds are interpolated from best-track maximum 1-min wind speed estimates. The aircraft data were collected primarily in the Atlantic but also include eastern and central North Pacific cases. Global numerical analyses were used to estimate tropical cyclone size and environmental pressure associated with each observation. Using this dataset (3801 points), the influences of latitude, tropical cyclone size, environmental pressure, and intensification trend on the tropical cyclone wind–pressure relationships were examined. Findings suggest that latitude, size, and environmental pressure, which all can be quantified in an operational and postanalysis setting, are related to predictable changes in the wind–pressure relationships. These factors can be combined into equations that estimate winds given pressure and estimate pressure given winds with greater accuracy than current methodologies. In independent testing during the 2005 hurricane season (524 cases), these new wind–pressure relationships resulted in mean absolute errors of 5.3 hPa and 6.2 kt compared with the 7.7 hPa and 9.0 kt that resulted from using the standard Atlantic Dvorak wind–pressure relationship. These new wind–pressure relationships are then used to evaluate several operational wind–pressure relationships. These intercomparisons have led to several recommendations for operational tropical cyclone centers and those interested in reanalyzing past tropical cyclone events.
Abstract
Veerasamy has made several comments concerning the results and methods presented in a recent article by the authors titled “Reexamination of Tropical Cyclone Wind–Pressure Relationships.” One comment concerns the terminology and definition of the environmental pressure. Another comment suggests the merits of a simpler approach developed by Veerasamy in 2005 that utilizes the radius of 1004 hPa to determine the “proper” wind–pressure relationship. The third comment concerns the performance of the Knaff and Zehr wind–pressure relationship [their Eq. (7)] during the well-observed North Atlantic Hurricanes Katrina, Rita, and Wilma during 2005. The final comment suggests that the techniques discussed in Knaff and Zehr are more difficult to apply than an operational method developed by Veerasamy and used in Mauritius. These comments are addressed individually along with some of the lessons learned since the publication of the Knaff and Zehr methodology that are important to the tropical cyclone community.
Abstract
Veerasamy has made several comments concerning the results and methods presented in a recent article by the authors titled “Reexamination of Tropical Cyclone Wind–Pressure Relationships.” One comment concerns the terminology and definition of the environmental pressure. Another comment suggests the merits of a simpler approach developed by Veerasamy in 2005 that utilizes the radius of 1004 hPa to determine the “proper” wind–pressure relationship. The third comment concerns the performance of the Knaff and Zehr wind–pressure relationship [their Eq. (7)] during the well-observed North Atlantic Hurricanes Katrina, Rita, and Wilma during 2005. The final comment suggests that the techniques discussed in Knaff and Zehr are more difficult to apply than an operational method developed by Veerasamy and used in Mauritius. These comments are addressed individually along with some of the lessons learned since the publication of the Knaff and Zehr methodology that are important to the tropical cyclone community.
Abstract
A method is developed to adjust the Kaplan and DeMaria tropical cyclone inland wind decay model for storms that move over narrow landmasses. The basic assumption that the wind speed decay rate after landfall is proportional to the wind speed is modified to include a factor equal to the fraction of the storm circulation that is over land. The storm circulation is defined as a circular area with a fixed radius. Application of the modified model to Atlantic Ocean cases from 1967 to 2003 showed that a circulation radius of 110 km minimizes the bias in the total sample of landfalling cases and reduces the mean absolute error of the predicted maximum winds by about 12%. This radius is about 2 times the radius of maximum wind of a typical Atlantic tropical cyclone. The modified decay model was applied to the Statistical Hurricane Intensity Prediction Scheme (SHIPS), which uses the Kaplan and DeMaria decay model to adjust the intensity for the portion of the predicted track that is over land. The modified decay model reduced the intensity forecast errors by up to 8% relative to the original decay model for cases from 2001 to 2004 in which the storm was within 500 km from land.
Abstract
A method is developed to adjust the Kaplan and DeMaria tropical cyclone inland wind decay model for storms that move over narrow landmasses. The basic assumption that the wind speed decay rate after landfall is proportional to the wind speed is modified to include a factor equal to the fraction of the storm circulation that is over land. The storm circulation is defined as a circular area with a fixed radius. Application of the modified model to Atlantic Ocean cases from 1967 to 2003 showed that a circulation radius of 110 km minimizes the bias in the total sample of landfalling cases and reduces the mean absolute error of the predicted maximum winds by about 12%. This radius is about 2 times the radius of maximum wind of a typical Atlantic tropical cyclone. The modified decay model was applied to the Statistical Hurricane Intensity Prediction Scheme (SHIPS), which uses the Kaplan and DeMaria decay model to adjust the intensity for the portion of the predicted track that is over land. The modified decay model reduced the intensity forecast errors by up to 8% relative to the original decay model for cases from 2001 to 2004 in which the storm was within 500 km from land.
Abstract
A revised rapid intensity index (RII) is developed for the Atlantic and eastern North Pacific basins. The RII uses large-scale predictors from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) to estimate the probability of rapid intensification (RI) over the succeeding 24 h utilizing linear discriminant analysis. Separate versions of the RII are developed for the 25-, 30-, and 35-kt RI thresholds, which represent the 90th (88th), 94th (92nd), and 97th (94th) percentiles of 24-h overwater intensity changes of tropical and subtropical cyclones in the Atlantic (eastern North Pacific) basins from 1989 to 2006, respectively. The revised RII became operational at the NHC prior to the 2008 hurricane season.
The relative importance of the individual RI predictors is shown to differ between the two basins. Specifically, the previous 12-h intensity change, upper-level divergence, and vertical shear have the highest weights for the Atlantic basin, while the previous 12-h intensity change, symmetry of inner-core convection, and the difference in a system’s current and maximum potential intensity are weighted highest in the eastern North Pacific basin.
A verification of independent forecasts from the 2006 and 2007 hurricane seasons shows that the probabilistic RII forecasts are generally skillful in both basins when compared to climatology. Moreover, when employed in a deterministic manner, the RII forecasts were superior to all other available operational intensity guidance in terms of the probability of detection (POD) and false alarm ratio (FAR). Specifically, the POD for the RII ranged from 15% to 59% (53% to 73%) while the FAR ranged from 71% to 85% (53% to 79%) in the Atlantic (eastern North Pacific) basins, respectively, for the three RI thresholds studied. Nevertheless, the modest POD and relatively high FAR of the RII and other intensity guidance demonstrate the difficulty of predicting RI, particularly in the Atlantic basin.
Abstract
A revised rapid intensity index (RII) is developed for the Atlantic and eastern North Pacific basins. The RII uses large-scale predictors from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) to estimate the probability of rapid intensification (RI) over the succeeding 24 h utilizing linear discriminant analysis. Separate versions of the RII are developed for the 25-, 30-, and 35-kt RI thresholds, which represent the 90th (88th), 94th (92nd), and 97th (94th) percentiles of 24-h overwater intensity changes of tropical and subtropical cyclones in the Atlantic (eastern North Pacific) basins from 1989 to 2006, respectively. The revised RII became operational at the NHC prior to the 2008 hurricane season.
The relative importance of the individual RI predictors is shown to differ between the two basins. Specifically, the previous 12-h intensity change, upper-level divergence, and vertical shear have the highest weights for the Atlantic basin, while the previous 12-h intensity change, symmetry of inner-core convection, and the difference in a system’s current and maximum potential intensity are weighted highest in the eastern North Pacific basin.
A verification of independent forecasts from the 2006 and 2007 hurricane seasons shows that the probabilistic RII forecasts are generally skillful in both basins when compared to climatology. Moreover, when employed in a deterministic manner, the RII forecasts were superior to all other available operational intensity guidance in terms of the probability of detection (POD) and false alarm ratio (FAR). Specifically, the POD for the RII ranged from 15% to 59% (53% to 73%) while the FAR ranged from 71% to 85% (53% to 79%) in the Atlantic (eastern North Pacific) basins, respectively, for the three RI thresholds studied. Nevertheless, the modest POD and relatively high FAR of the RII and other intensity guidance demonstrate the difficulty of predicting RI, particularly in the Atlantic basin.
Abstract
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
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
Storm-centered infrared (IR) imagery of tropical cyclones (TCs) is related to the 850-hPa mean tangential wind at a radius of 500 km (V500) calculated from 6-hourly global numerical analyses for North Atlantic and eastern North Pacific TCs for 1995–2011. V500 estimates are scaled using the climatological vortex decay rate beyond 500 km to estimate the radius of 5 kt (1 kt = 0.514 m s−1) winds (R5) or TC size. A much larger historical record of TC-centered IR imagery (1978–2011) is then used to estimate TC sizes and form a global TC size climatology. The basin-specific distributions of TC size reveal that, among other things, the eastern North Pacific TC basins have the smallest while western North Pacific have the largest TC size distributions. The life cycle of TC sizes with respect to maximum intensity shows that TC growth characteristics are different among the individual TC basins, with the North Atlantic composites showing continued growth after maximum intensity. Small TCs are generally located at lower latitudes, westward steering, and preferred in seasons when environmental low-level vorticity is suppressed. Large TCs are generally located at higher latitudes, poleward steering, and preferred in enhanced low-level vorticity environments. Postmaximum intensity growth of TCs occurs in regions associated with enhanced baroclinicity and TC recurvature, while those that do not grow much are associated with west movement, erratic storm tracks, and landfall at or near the time of maximum intensity. With respect to climate change, no significant long-term trends are found in the dataset of TC size.
Abstract
Storm-centered infrared (IR) imagery of tropical cyclones (TCs) is related to the 850-hPa mean tangential wind at a radius of 500 km (V500) calculated from 6-hourly global numerical analyses for North Atlantic and eastern North Pacific TCs for 1995–2011. V500 estimates are scaled using the climatological vortex decay rate beyond 500 km to estimate the radius of 5 kt (1 kt = 0.514 m s−1) winds (R5) or TC size. A much larger historical record of TC-centered IR imagery (1978–2011) is then used to estimate TC sizes and form a global TC size climatology. The basin-specific distributions of TC size reveal that, among other things, the eastern North Pacific TC basins have the smallest while western North Pacific have the largest TC size distributions. The life cycle of TC sizes with respect to maximum intensity shows that TC growth characteristics are different among the individual TC basins, with the North Atlantic composites showing continued growth after maximum intensity. Small TCs are generally located at lower latitudes, westward steering, and preferred in seasons when environmental low-level vorticity is suppressed. Large TCs are generally located at higher latitudes, poleward steering, and preferred in enhanced low-level vorticity environments. Postmaximum intensity growth of TCs occurs in regions associated with enhanced baroclinicity and TC recurvature, while those that do not grow much are associated with west movement, erratic storm tracks, and landfall at or near the time of maximum intensity. With respect to climate change, no significant long-term trends are found in the dataset of TC size.
Abstract
Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)−1; or 12.9, 15.4, and 18.0 m s−1 (24 h)−1] for the 24-h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50% probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40% threshold for producing the RI aid initially. The 40% threshold is available for approximately 8% of all verifying forecasts, produces approximately 4% reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%–20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill).
Abstract
Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)−1; or 12.9, 15.4, and 18.0 m s−1 (24 h)−1] for the 24-h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50% probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40% threshold for producing the RI aid initially. The 40% threshold is available for approximately 8% of all verifying forecasts, produces approximately 4% reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%–20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill).
Abstract
Vertical wind shear and storm motion are two of the most important factors contributing to rainfall asymmetries in tropical cyclones (TCs). Global TC rainfall structure, in terms of azimuthal distribution and asymmetries relative to storm motion, has been previously described using the Tropical Rainfall Measuring Mission Microwave Imager rainfall estimates. The mean TC rainfall distribution and the wavenumber-1 asymmetry vary with storm intensity and geographical location among the six oceanic basins. This study uses a similar approach to investigate the relationship between the structure of TC rainfall and the environmental flow by computing the rainfall asymmetry relative to the vertical wind shear. The environmental vertical wind shear is defined as the difference between the mean wind vectors of the 200- and 850-hPa levels over an outer region extending from the radius of 200–800 km around the storm center. The wavenumber-1 maximum rainfall asymmetry is downshear left (right) in the Northern (Southern) Hemisphere. The rainfall asymmetry decreases (increases) with storm intensity (shear strength). The rainfall asymmetry maximum is predominantly downshear left for shear values > 7.5 m s−1. Large asymmetries are usually observed away from the TC centers. As TC intensity increases, the asymmetry maximum shifts upwind to the left. The analysis is further extended to examine the storm motion and the vertical wind shear and their collective effects on TC rainfall asymmetries. It is found that the vertical wind shear is a dominant factor for the rainfall asymmetry when shear is >5 m s−1. The storm motion–relative rainfall asymmetry in the outer rainband region is comparable to that of shear relative when the shear is <5 m s−1, suggesting that TC translation speed becomes an important factor in the low shear environment. The overall TC rainfall asymmetry depends on the juxtaposition and relative magnitude of the storm motion and environmental shear vectors in all oceanic basins.
Abstract
Vertical wind shear and storm motion are two of the most important factors contributing to rainfall asymmetries in tropical cyclones (TCs). Global TC rainfall structure, in terms of azimuthal distribution and asymmetries relative to storm motion, has been previously described using the Tropical Rainfall Measuring Mission Microwave Imager rainfall estimates. The mean TC rainfall distribution and the wavenumber-1 asymmetry vary with storm intensity and geographical location among the six oceanic basins. This study uses a similar approach to investigate the relationship between the structure of TC rainfall and the environmental flow by computing the rainfall asymmetry relative to the vertical wind shear. The environmental vertical wind shear is defined as the difference between the mean wind vectors of the 200- and 850-hPa levels over an outer region extending from the radius of 200–800 km around the storm center. The wavenumber-1 maximum rainfall asymmetry is downshear left (right) in the Northern (Southern) Hemisphere. The rainfall asymmetry decreases (increases) with storm intensity (shear strength). The rainfall asymmetry maximum is predominantly downshear left for shear values > 7.5 m s−1. Large asymmetries are usually observed away from the TC centers. As TC intensity increases, the asymmetry maximum shifts upwind to the left. The analysis is further extended to examine the storm motion and the vertical wind shear and their collective effects on TC rainfall asymmetries. It is found that the vertical wind shear is a dominant factor for the rainfall asymmetry when shear is >5 m s−1. The storm motion–relative rainfall asymmetry in the outer rainband region is comparable to that of shear relative when the shear is <5 m s−1, suggesting that TC translation speed becomes an important factor in the low shear environment. The overall TC rainfall asymmetry depends on the juxtaposition and relative magnitude of the storm motion and environmental shear vectors in all oceanic basins.
