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Abstract
A large sample of Atlantic and eastern North Pacific tropical cyclone cases (2005–10) is used to investigate the relationships between lightning activity and intensity changes for storms over water. The lightning data are obtained from the ground-based World Wide Lightning Location Network (WWLLN). The results generally confirm those from previous studies: the average lightning density (strikes per unit area and time) decreases with radius from the storm center; tropical storms tend to have more lightning than hurricanes; intensifying storms tend to have greater lightning density than weakening cyclones; and the lightning density for individual cyclones is very episodic. Results also show that Atlantic tropical cyclones tend to have greater lightning density than east Pacific storms. The largest lightning density values are associated with sheared cyclones that do not intensify very much. The results also show that when the lightning density is compared with intensity change in the subsequent 24 h, Atlantic cyclones that rapidly weaken have a larger inner-core (0–100 km) lightning density than those that rapidly intensify. Thus, large inner-core lightning outbreaks are sometimes a signal that an intensification period is coming to an end. Conversely, the lightning density in the rainband regions (200–300 km) is higher for those cyclones that rapidly intensified in the following 24 h in both the Atlantic and east Pacific. When lightning density parameters are used as input to a discriminant analysis technique, results show that lightning information has the potential to improve the short-term prediction of tropical cyclone rapid intensity changes.
Abstract
A large sample of Atlantic and eastern North Pacific tropical cyclone cases (2005–10) is used to investigate the relationships between lightning activity and intensity changes for storms over water. The lightning data are obtained from the ground-based World Wide Lightning Location Network (WWLLN). The results generally confirm those from previous studies: the average lightning density (strikes per unit area and time) decreases with radius from the storm center; tropical storms tend to have more lightning than hurricanes; intensifying storms tend to have greater lightning density than weakening cyclones; and the lightning density for individual cyclones is very episodic. Results also show that Atlantic tropical cyclones tend to have greater lightning density than east Pacific storms. The largest lightning density values are associated with sheared cyclones that do not intensify very much. The results also show that when the lightning density is compared with intensity change in the subsequent 24 h, Atlantic cyclones that rapidly weaken have a larger inner-core (0–100 km) lightning density than those that rapidly intensify. Thus, large inner-core lightning outbreaks are sometimes a signal that an intensification period is coming to an end. Conversely, the lightning density in the rainband regions (200–300 km) is higher for those cyclones that rapidly intensified in the following 24 h in both the Atlantic and east Pacific. When lightning density parameters are used as input to a discriminant analysis technique, results show that lightning information has the potential to improve the short-term prediction of tropical cyclone rapid intensity changes.
Abstract
This paper presents a climatology of the initial eye formations of a broad set of Atlantic tropical cyclones (TCs) during 1989–2008. A new dataset of structure and intensity parameters is synthesized from the vortex data messages transmitted by routine aircraft reconnaissance. Using these data together with satellite imagery and other established datasets, the times when each TC achieved various stages of eye development are tabulated to form the basis of the climatology. About 60% of Atlantic TCs form eyes. Most often, aircraft observe the eye structure before it appears in IR satellite imagery. Eyes tend to form in high potential intensity environments characterized by high sea surface temperatures and low-to-moderate environmental vertical wind shear. A notable discovery is that most (67%) TCs that form eyes tend to do so within 48 h of the cyclone’s reaching tropical storm strength. This suggests the existence of an opportune time window during which a TC can readily form an eye. From the lengths of time taken to reach various stages of eye development, the characteristic time scale for eye formation is estimated to be about 36 h.
Abstract
This paper presents a climatology of the initial eye formations of a broad set of Atlantic tropical cyclones (TCs) during 1989–2008. A new dataset of structure and intensity parameters is synthesized from the vortex data messages transmitted by routine aircraft reconnaissance. Using these data together with satellite imagery and other established datasets, the times when each TC achieved various stages of eye development are tabulated to form the basis of the climatology. About 60% of Atlantic TCs form eyes. Most often, aircraft observe the eye structure before it appears in IR satellite imagery. Eyes tend to form in high potential intensity environments characterized by high sea surface temperatures and low-to-moderate environmental vertical wind shear. A notable discovery is that most (67%) TCs that form eyes tend to do so within 48 h of the cyclone’s reaching tropical storm strength. This suggests the existence of an opportune time window during which a TC can readily form an eye. From the lengths of time taken to reach various stages of eye development, the characteristic time scale for eye formation is estimated to be about 36 h.
Abstract
A regional hybrid variational–ensemble data assimilation system (HVEDAS), the maximum likelihood ensemble filter (MLEF), is applied to the 2011 version of the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model to evaluate the impact of direct assimilation of cloud-affected Advanced Microwave Sounding Unit-A (AMSU-A) radiances in tropical cyclone (TC) core areas. The forward components of both the gridpoint statistical interpolation (GSI) analysis system and the Community Radiative Transfer Model (CRTM) are utilized to process and simulate satellite radiances. The central strategies to allow the use of cloud-affected radiances are (i) to augment the control variables to include clouds and (ii) to add the model cloud representations in the observation forward models to simulate the microwave radiances. The cloudy AMSU-A radiance assimilation in Hurricane Danielle's (2010) core area has produced encouraging results with respect to the operational cloud-cleared radiance preprocessing procedures used in this study. Through the use of the HVEDAS, ensemble covariance statistics for a pseudo-AMSU-A observation in Danielle's core area show physically meaningful error covariances and statistical couplings with hydrometeor variables (i.e., the total-column condensate in Ferrier microphysics). The cloudy radiance assimilation in the TC core region (i.e., ASR experiment) consistently reduced the root-mean-square errors of the background departures, and also generally improved the forecasts of Danielle's intensity as well as the quantitative cloud analysis and prediction. It is also indicated that an entropy-based information content quantification process provides a useful metric for evaluating the utility of satellite observations in hybrid data assimilation.
Abstract
A regional hybrid variational–ensemble data assimilation system (HVEDAS), the maximum likelihood ensemble filter (MLEF), is applied to the 2011 version of the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model to evaluate the impact of direct assimilation of cloud-affected Advanced Microwave Sounding Unit-A (AMSU-A) radiances in tropical cyclone (TC) core areas. The forward components of both the gridpoint statistical interpolation (GSI) analysis system and the Community Radiative Transfer Model (CRTM) are utilized to process and simulate satellite radiances. The central strategies to allow the use of cloud-affected radiances are (i) to augment the control variables to include clouds and (ii) to add the model cloud representations in the observation forward models to simulate the microwave radiances. The cloudy AMSU-A radiance assimilation in Hurricane Danielle's (2010) core area has produced encouraging results with respect to the operational cloud-cleared radiance preprocessing procedures used in this study. Through the use of the HVEDAS, ensemble covariance statistics for a pseudo-AMSU-A observation in Danielle's core area show physically meaningful error covariances and statistical couplings with hydrometeor variables (i.e., the total-column condensate in Ferrier microphysics). The cloudy radiance assimilation in the TC core region (i.e., ASR experiment) consistently reduced the root-mean-square errors of the background departures, and also generally improved the forecasts of Danielle's intensity as well as the quantitative cloud analysis and prediction. It is also indicated that an entropy-based information content quantification process provides a useful metric for evaluating the utility of satellite observations in hybrid data assimilation.
Abstract
This study introduces and examines a symmetric category of tropical cyclone, which the authors call annular hurricanes. The structural characteristics and formation of this type of hurricane are examined and documented using satellite and aircraft reconnaissance data. The formation is shown to be systematic, resulting from what appears to be asymmetric mixing of eye and eyewall components of the storms involving either one or two possible mesovortices. Flight-level thermodynamic data support this contention, displaying uniform values of equivalent potential temperature in the eye, while the flight-level wind observations within annular hurricanes show evidence that mixing inside the radius of maximum wind likely continues. Intensity tendencies of annular hurricanes indicate that these storms maintain their intensities longer than the average hurricane, resulting in larger-than-average intensity forecast errors and thus a significant intensity forecasting challenge. In addition, these storms are found to exist in a specific set of environmental conditions, which are only found 3% and 0.8% of the time in the east Pacific and Atlantic tropical cyclone basins during 1989–99, respectively. With forecasting issues in mind, two methods of objectively identifying these storms are also developed and discussed.
Abstract
This study introduces and examines a symmetric category of tropical cyclone, which the authors call annular hurricanes. The structural characteristics and formation of this type of hurricane are examined and documented using satellite and aircraft reconnaissance data. The formation is shown to be systematic, resulting from what appears to be asymmetric mixing of eye and eyewall components of the storms involving either one or two possible mesovortices. Flight-level thermodynamic data support this contention, displaying uniform values of equivalent potential temperature in the eye, while the flight-level wind observations within annular hurricanes show evidence that mixing inside the radius of maximum wind likely continues. Intensity tendencies of annular hurricanes indicate that these storms maintain their intensities longer than the average hurricane, resulting in larger-than-average intensity forecast errors and thus a significant intensity forecasting challenge. In addition, these storms are found to exist in a specific set of environmental conditions, which are only found 3% and 0.8% of the time in the east Pacific and Atlantic tropical cyclone basins during 1989–99, respectively. With forecasting issues in mind, two methods of objectively identifying these storms are also developed and discussed.
Abstract
Forecasts of tropical cyclone (TC) surface wind structure have recently begun to show some skill, but the number of reliable forecast tools, mostly regional hurricane and select global models, remains limited. To provide additional wind structure guidance, this work presents the development of a statistical–dynamical method to predict tropical cyclone wind structure in terms of wind radii, which are defined as the maximum extent of the 34-, 50-, and 64-kt (1 kt = 0.514 m s−1) winds in geographical quadrants about the center of the storm. The basis for TC size variations is developed from an infrared satellite-based record of TC size, which is homogenously calculated from a global sample. The change in TC size is predicted using a statistical–dynamical approach where predictors are based on environmental diagnostics derived from global model forecasts and observed storm conditions. Once the TC size has been predicted, the forecast intensity and track are used along with a parametric wind model to estimate the resulting wind radii. To provide additional guidance for applications and users that require forecasts of central pressure, a wind–pressure relationship that is a function of TC motion, intensity, wind radii (i.e., size), and latitude is then applied to these forecasts. This forecast method compares well with similar wind structure forecasts made by global forecast and regional hurricane models and when these forecasts are used as a member of a simple consensus; its inclusion improves the forecast performance of the consensus.
Abstract
Forecasts of tropical cyclone (TC) surface wind structure have recently begun to show some skill, but the number of reliable forecast tools, mostly regional hurricane and select global models, remains limited. To provide additional wind structure guidance, this work presents the development of a statistical–dynamical method to predict tropical cyclone wind structure in terms of wind radii, which are defined as the maximum extent of the 34-, 50-, and 64-kt (1 kt = 0.514 m s−1) winds in geographical quadrants about the center of the storm. The basis for TC size variations is developed from an infrared satellite-based record of TC size, which is homogenously calculated from a global sample. The change in TC size is predicted using a statistical–dynamical approach where predictors are based on environmental diagnostics derived from global model forecasts and observed storm conditions. Once the TC size has been predicted, the forecast intensity and track are used along with a parametric wind model to estimate the resulting wind radii. To provide additional guidance for applications and users that require forecasts of central pressure, a wind–pressure relationship that is a function of TC motion, intensity, wind radii (i.e., size), and latitude is then applied to these forecasts. This forecast method compares well with similar wind structure forecasts made by global forecast and regional hurricane models and when these forecasts are used as a member of a simple consensus; its inclusion improves the forecast performance of the consensus.
Abstract
This note describes an updated tropical cyclone vortex climatology for the western North Pacific version of the operational wind radii climatology and persistence (i.e., CLIPER) model. The update addresses known shortcomings of the existing formulation, namely, that the wind radii used to develop the original model were too small and symmetric. The underlying formulation of the CLIPER model has not changed, but the larger and more realistic vortex climatology produces improved forecast biases. Other applications that make use of the vortex climatology and CLIPER model forecasts should also benefit from the bias improvements.
Abstract
This note describes an updated tropical cyclone vortex climatology for the western North Pacific version of the operational wind radii climatology and persistence (i.e., CLIPER) model. The update addresses known shortcomings of the existing formulation, namely, that the wind radii used to develop the original model were too small and symmetric. The underlying formulation of the CLIPER model has not changed, but the larger and more realistic vortex climatology produces improved forecast biases. Other applications that make use of the vortex climatology and CLIPER model forecasts should also benefit from the bias improvements.
Abstract
Previous work, in which Advanced Microwave Sounding Unit (AMSU) data from the Atlantic Ocean and east Pacific Ocean basins during 1999–2001 were used to provide objective estimates of 1-min maximum sustained surface winds, minimum sea level pressure, and the radii of 34-, 50-, and 64-kt (1 kt ≡ 0.5144 m s−1) winds in the northeast, southeast, southwest, and northwest quadrants of tropical cyclones, is updated to reflect larger datasets, improved statistical analysis techniques, and improved estimation through dependent variable transforms. A multiple regression approach, which utilizes best-subset predictor selection and cross validation, is employed to develop the estimation models, where the dependent data (i.e., maximum sustained winds, minimum pressure, wind radii) are from the extended best track and the independent data consist of AMSU-derived parameters that give information about retrieved pressure, winds, temperature, moisture, and satellite resolution. The developmental regression models result in mean absolute errors (MAE) of 10.8 kt and 7.8 hPa for estimating maximum winds and minimum pressure, respectively. The MAE for the 34-, 50-, and 64-kt azimuthally averaged wind radii are 16.9, 13.3, and 6.8 n mi (1 n mi ≡ 1852 m), respectively.
Abstract
Previous work, in which Advanced Microwave Sounding Unit (AMSU) data from the Atlantic Ocean and east Pacific Ocean basins during 1999–2001 were used to provide objective estimates of 1-min maximum sustained surface winds, minimum sea level pressure, and the radii of 34-, 50-, and 64-kt (1 kt ≡ 0.5144 m s−1) winds in the northeast, southeast, southwest, and northwest quadrants of tropical cyclones, is updated to reflect larger datasets, improved statistical analysis techniques, and improved estimation through dependent variable transforms. A multiple regression approach, which utilizes best-subset predictor selection and cross validation, is employed to develop the estimation models, where the dependent data (i.e., maximum sustained winds, minimum pressure, wind radii) are from the extended best track and the independent data consist of AMSU-derived parameters that give information about retrieved pressure, winds, temperature, moisture, and satellite resolution. The developmental regression models result in mean absolute errors (MAE) of 10.8 kt and 7.8 hPa for estimating maximum winds and minimum pressure, respectively. The MAE for the 34-, 50-, and 64-kt azimuthally averaged wind radii are 16.9, 13.3, and 6.8 n mi (1 n mi ≡ 1852 m), respectively.
Abstract
A ubiquitous cold signal near the tropopause, here called “tropopause layer cooling” (TLC), has been documented in deep convective regions such as tropical cyclones (TCs). Temperature retrievals from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) reveal cooling of order 0.1–1 K day−1 on spatial scales of order 1000 km above TCs. Data from the Cloud Profiling Radar (onboard CloudSat) and from the Cloud–Aerosol Lidar with Orthogonal Polarization [onboard the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] are used to analyze cloud distributions associated with TCs. Evidence is found that convective clouds within TCs reach the upper part of the tropical tropopause layer (TTL) more frequently than do convective clouds outside TCs, raising the possibility that convective clouds within TCs and associated cirrus clouds modulate TLC. The contribution of clouds to radiative heating rates is then quantified using the CloudSat and CALIPSO datasets: in the lower TTL (below the tropopause), clouds produce longwave cooling of order 0.1–1 K day−1 inside the TC main convective region, and longwave warming of order 0.01–0.1 K day−1 outside; in the upper TTL (near and above the tropopause), clouds produce longwave cooling of the same order as TLC inside the TC main convective region, and one order of magnitude smaller outside. Considering that clouds also produce shortwave warming, cloud radiative effects are suggested to explain only modest amounts of TLC while other processes must provide the remaining cooling.
Abstract
A ubiquitous cold signal near the tropopause, here called “tropopause layer cooling” (TLC), has been documented in deep convective regions such as tropical cyclones (TCs). Temperature retrievals from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) reveal cooling of order 0.1–1 K day−1 on spatial scales of order 1000 km above TCs. Data from the Cloud Profiling Radar (onboard CloudSat) and from the Cloud–Aerosol Lidar with Orthogonal Polarization [onboard the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] are used to analyze cloud distributions associated with TCs. Evidence is found that convective clouds within TCs reach the upper part of the tropical tropopause layer (TTL) more frequently than do convective clouds outside TCs, raising the possibility that convective clouds within TCs and associated cirrus clouds modulate TLC. The contribution of clouds to radiative heating rates is then quantified using the CloudSat and CALIPSO datasets: in the lower TTL (below the tropopause), clouds produce longwave cooling of order 0.1–1 K day−1 inside the TC main convective region, and longwave warming of order 0.01–0.1 K day−1 outside; in the upper TTL (near and above the tropopause), clouds produce longwave cooling of the same order as TLC inside the TC main convective region, and one order of magnitude smaller outside. Considering that clouds also produce shortwave warming, cloud radiative effects are suggested to explain only modest amounts of TLC while other processes must provide the remaining cooling.
Abstract
Tropical cyclone (TC) size, usually measured with the radius of gale force wind (34 kt or 17 m s−1), is an important parameter for estimating TC risks such as wind damage, rainfall distribution, and storm surge. Previous studies have reported that there is a very weak relationship between TC size and TC intensity. A close examination presented here using satellite-based wind analyses suggests that the relationship between TC size and intensity is nonlinear. TC size generally increases with increasing TC maximum sustained wind before a maximum of 2.50° latitude at an intensity of 103 kt or 53.0 m s−1 and then slowly decreases as the TC intensity further increases. The observed relationship between TC size and intensity is compared to the relationships produced by an 11-yr seasonal numerical simulation of TC activity. The numerical simulations were able to produce neither the observed maximum sustained winds nor the observed nonlinear relationship between TC size and intensity. This finding suggests that TC size cannot reasonably be simulated with 9-km horizontal resolution and increased resolution is needed to study TC size variations using numerical simulations.
Abstract
Tropical cyclone (TC) size, usually measured with the radius of gale force wind (34 kt or 17 m s−1), is an important parameter for estimating TC risks such as wind damage, rainfall distribution, and storm surge. Previous studies have reported that there is a very weak relationship between TC size and TC intensity. A close examination presented here using satellite-based wind analyses suggests that the relationship between TC size and intensity is nonlinear. TC size generally increases with increasing TC maximum sustained wind before a maximum of 2.50° latitude at an intensity of 103 kt or 53.0 m s−1 and then slowly decreases as the TC intensity further increases. The observed relationship between TC size and intensity is compared to the relationships produced by an 11-yr seasonal numerical simulation of TC activity. The numerical simulations were able to produce neither the observed maximum sustained winds nor the observed nonlinear relationship between TC size and intensity. This finding suggests that TC size cannot reasonably be simulated with 9-km horizontal resolution and increased resolution is needed to study TC size variations using numerical simulations.
Abstract
Diurnal oscillations of infrared cloud-top brightness temperatures (Tbs) in tropical cyclones (TCs) as inferred from storm-centered, direction-relative longwave infrared (~11 μm) imagery are quantified for Northern Hemisphere TCs (2005–15) using statistical methods. These methods show that 45%, 54%, and 61% of at least tropical storm-, hurricane-, and major hurricane-strength TC cases have moderate or strong diurnal signals. Principal component analysis–based average behavior of all TCs with intensities of 34 kt (17.5 m s−1) or greater is shown to have a nearly symmetric diurnal signal where Tbs oscillate from warm to cold and cold to warm within and outside of a radius of approximately 220 km, with maximum central cooling occurring in the early morning (0300–0800 local standard time), and a nearly simultaneous maximum warming occurring near the 500-km radius—a radial standing wave with a node near 220-km radius. Amplitude and phase of these diurnal oscillations are quantified for individual 24-h periods (or cases) relative to the mean oscillation. Details of the diurnal behavior of TCs are used to examine preferred storm and environmental characteristics using a combination of spatial, composite, and regression analyses. Results suggest that diurnal, cloud-top Tb oscillations in TCs are strongest and most regular when storm characteristics (e.g., intensity and motion) and environmental conditions (e.g., vertical wind shear and low-level temperature advection) support azimuthally symmetric storm structures and when surrounding mid- and upper-level relative humidity values are greater. Finally, it is hypothesized that larger mid- and upper-level relative humidity values are necessary ingredients for robust, large-amplitude, and regular diurnal oscillations of Tbs in TCs.
Abstract
Diurnal oscillations of infrared cloud-top brightness temperatures (Tbs) in tropical cyclones (TCs) as inferred from storm-centered, direction-relative longwave infrared (~11 μm) imagery are quantified for Northern Hemisphere TCs (2005–15) using statistical methods. These methods show that 45%, 54%, and 61% of at least tropical storm-, hurricane-, and major hurricane-strength TC cases have moderate or strong diurnal signals. Principal component analysis–based average behavior of all TCs with intensities of 34 kt (17.5 m s−1) or greater is shown to have a nearly symmetric diurnal signal where Tbs oscillate from warm to cold and cold to warm within and outside of a radius of approximately 220 km, with maximum central cooling occurring in the early morning (0300–0800 local standard time), and a nearly simultaneous maximum warming occurring near the 500-km radius—a radial standing wave with a node near 220-km radius. Amplitude and phase of these diurnal oscillations are quantified for individual 24-h periods (or cases) relative to the mean oscillation. Details of the diurnal behavior of TCs are used to examine preferred storm and environmental characteristics using a combination of spatial, composite, and regression analyses. Results suggest that diurnal, cloud-top Tb oscillations in TCs are strongest and most regular when storm characteristics (e.g., intensity and motion) and environmental conditions (e.g., vertical wind shear and low-level temperature advection) support azimuthally symmetric storm structures and when surrounding mid- and upper-level relative humidity values are greater. Finally, it is hypothesized that larger mid- and upper-level relative humidity values are necessary ingredients for robust, large-amplitude, and regular diurnal oscillations of Tbs in TCs.
