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- Author or Editor: John M. Brown x
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Abstract
This study uses a series of numerical simulations to examine the structure of the wake of the Hawaiian island of Kauai. The primary focus is on the conditions on 26 June 2003, which was the day of the demise of the Helios aircraft within Kauai’s wake. The simulations show that, in an east-northeasterly trade wind flow, Kauai produces a well-defined wake that can extend 40 km downstream of the island. The wake is bounded to the north and south by regions of strong vertical and horizontal shear—that is, shear lines. These shear lines mark the edge of the wake in the horizontal plane and are aligned approximately parallel to the upstream flow direction at each respective height. The highest-resolution simulations show that these shear lines can become unstable and break down through Kelvin–Helmholtz instability. The breakdown generates turbulent eddies that are advected both downstream and into the recirculating wake flow. Turbulence statistics are estimated from the simulation using a technique that analyzes model-derived structure functions. A number of sensitivity studies are also completed to determine the influence of the upstream conditions on the structure of the wake. These simulations show that directional shear controls the tilt of the wake in the north–south plane with height. These simulations also show that at lower incident wind speeds the wake has a qualitatively similar structure but is less turbulent. At higher wind speeds, the flow regime changes, strong gravity waves are generated, and the wake is poorly defined. These results are consistent with previous idealized studies of stratified flow over isolated obstacles.
Abstract
This study uses a series of numerical simulations to examine the structure of the wake of the Hawaiian island of Kauai. The primary focus is on the conditions on 26 June 2003, which was the day of the demise of the Helios aircraft within Kauai’s wake. The simulations show that, in an east-northeasterly trade wind flow, Kauai produces a well-defined wake that can extend 40 km downstream of the island. The wake is bounded to the north and south by regions of strong vertical and horizontal shear—that is, shear lines. These shear lines mark the edge of the wake in the horizontal plane and are aligned approximately parallel to the upstream flow direction at each respective height. The highest-resolution simulations show that these shear lines can become unstable and break down through Kelvin–Helmholtz instability. The breakdown generates turbulent eddies that are advected both downstream and into the recirculating wake flow. Turbulence statistics are estimated from the simulation using a technique that analyzes model-derived structure functions. A number of sensitivity studies are also completed to determine the influence of the upstream conditions on the structure of the wake. These simulations show that directional shear controls the tilt of the wake in the north–south plane with height. These simulations also show that at lower incident wind speeds the wake has a qualitatively similar structure but is less turbulent. At higher wind speeds, the flow regime changes, strong gravity waves are generated, and the wake is poorly defined. These results are consistent with previous idealized studies of stratified flow over isolated obstacles.
Abstract
Tropical cyclone (TC) translation speed influences rainfall accumulation, storm surge, and exposure to high winds. These effects are greatest when storms stall. Here, we provide a definition and climatology of slow-moving or stalling TCs in the North Atlantic from 1900–2020. A stall is defined as a TC with a track contained in a circular area (“corral”) with a radius of ≤ 200 km for 72 hours. Of the 1,274 North Atlantic TCs, 191 storms met this definition (15%). Ten are multi-stalling storms, or those that experienced more than one stall period. Hurricane Ginger in 1971 stalled the most with four separate stalls. Stalling TC locations are clustered in the western Caribbean, the central Gulf Coast, the Bay of Campeche, and near Florida and the Carolinas. Stalling was most common in October TCs (17.3% of October total) and least common in August (8.2%). The estimated annual frequency of stalls significantly increased over the satellite-era (1966–2020) by 1.5% per year, and the cumulative frequency in the number of stalls compared to all storms also increased. Stalling storms have a significantly higher frequency of major hurricane status than non-stalling storms. Storms are also more likely to stall near the coast (≤ 200 km). Approximately 40% (n=77) of the stalling TCs experienced a period of rapid intensification, and five did so within 200 km of a coastal zone. These results will aid emergency managers in regions that experience frequent stalls by providing information they can use to better prepare for the future.
Abstract
Tropical cyclone (TC) translation speed influences rainfall accumulation, storm surge, and exposure to high winds. These effects are greatest when storms stall. Here, we provide a definition and climatology of slow-moving or stalling TCs in the North Atlantic from 1900–2020. A stall is defined as a TC with a track contained in a circular area (“corral”) with a radius of ≤ 200 km for 72 hours. Of the 1,274 North Atlantic TCs, 191 storms met this definition (15%). Ten are multi-stalling storms, or those that experienced more than one stall period. Hurricane Ginger in 1971 stalled the most with four separate stalls. Stalling TC locations are clustered in the western Caribbean, the central Gulf Coast, the Bay of Campeche, and near Florida and the Carolinas. Stalling was most common in October TCs (17.3% of October total) and least common in August (8.2%). The estimated annual frequency of stalls significantly increased over the satellite-era (1966–2020) by 1.5% per year, and the cumulative frequency in the number of stalls compared to all storms also increased. Stalling storms have a significantly higher frequency of major hurricane status than non-stalling storms. Storms are also more likely to stall near the coast (≤ 200 km). Approximately 40% (n=77) of the stalling TCs experienced a period of rapid intensification, and five did so within 200 km of a coastal zone. These results will aid emergency managers in regions that experience frequent stalls by providing information they can use to better prepare for the future.
Abstract
Clouds pose many operational hazards to the aviation community in terms of ceilings and visibility, turbulence, and aircraft icing. Realistic descriptions of the three-dimensional (3D) distribution and temporal evolution of clouds in numerical weather prediction models used for flight planning and routing are therefore of central importance. The introduction of satellite-based cloud radar (CloudSat) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) sensors to the National Aeronautics and Space Administration A-Train is timely in light of these needs but requires a new paradigm of model-evaluation tools that are capable of exploiting the vertical-profile information. Early results from the National Center for Atmospheric Research Model Evaluation Toolkit (MET), augmented to work with the emergent satellite-based active sensor observations, are presented here. Existing horizontal-plane statistical evaluation techniques have been adapted to operate on observations in the vertical plane and have been extended to 3D object evaluations, leveraging blended datasets from the active and passive A-Train sensors. Case studies of organized synoptic-scale and mesoscale distributed cloud systems are presented to illustrate the multiscale utility of the MET tools. Definition of objects on the basis of radar-reflectivity thresholds was found to be strongly dependent on the model’s ability to resolve details of the cloud’s internal hydrometeor distribution. Contoured-frequency-by-altitude diagrams provide a useful mechanism for evaluating the simulated and observed 3D distributions for regional domains. The expanded MET provides a new dimension to model evaluation and positions the community to better exploit active-sensor satellite observing systems that are slated for launch in the near future.
Abstract
Clouds pose many operational hazards to the aviation community in terms of ceilings and visibility, turbulence, and aircraft icing. Realistic descriptions of the three-dimensional (3D) distribution and temporal evolution of clouds in numerical weather prediction models used for flight planning and routing are therefore of central importance. The introduction of satellite-based cloud radar (CloudSat) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) sensors to the National Aeronautics and Space Administration A-Train is timely in light of these needs but requires a new paradigm of model-evaluation tools that are capable of exploiting the vertical-profile information. Early results from the National Center for Atmospheric Research Model Evaluation Toolkit (MET), augmented to work with the emergent satellite-based active sensor observations, are presented here. Existing horizontal-plane statistical evaluation techniques have been adapted to operate on observations in the vertical plane and have been extended to 3D object evaluations, leveraging blended datasets from the active and passive A-Train sensors. Case studies of organized synoptic-scale and mesoscale distributed cloud systems are presented to illustrate the multiscale utility of the MET tools. Definition of objects on the basis of radar-reflectivity thresholds was found to be strongly dependent on the model’s ability to resolve details of the cloud’s internal hydrometeor distribution. Contoured-frequency-by-altitude diagrams provide a useful mechanism for evaluating the simulated and observed 3D distributions for regional domains. The expanded MET provides a new dimension to model evaluation and positions the community to better exploit active-sensor satellite observing systems that are slated for launch in the near future.
