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Jay S. Hobgood

Abstract

A possible mechanism for the diurnal oscillations of tropical cyclones is presented. In the conceptual model developed to explain these features, the diurnal cycle of net radiation at the cloud tops is identified as the primary cause of the oscillations. Radiative cooling of the cloud tops at night steepens the lapse rate and increases convection. This generates a slight intensification in the storm. The reverse occurs during the daytime as the cloud tops absorb solar radiation. This process may be augmented by differential cooling of cloudy and clear areas.

This conceptual model is tested through the use of a numerical model. The basic model reproduces well the development of a strong hurricane from a weak tropical depression. The model storm exhibits strong, cyclonic low-level inflow and weaker anticyclonic upper-level outflow. In addition, spiral rainbands and an eye are observed during the simulation.

When the fluxes of longwave and shortwave radiation are added into the model, a definite diurnal fluctuation of intensity is evident during the early stages of the simulation. These fluctuations vary in the manner suggested by the conceptual model. This is confirmed by the oscillation of the latent heating, which peaks at night and diminishes during the day. As the storm intensifies, the fluctuations become less evident. This is to be expected, since the radiative fluxes comprise a smaller portion of the total energy budget during the later stages of the simulation.

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Jay S. Hobgood

Abstract

The effects of 10 climatological and persistence variables (latitude, maximum wind speed, 12-h change of maximum wind speed, longitude, distance to land, Julian date, sea surface temperature, speed of movement, zonal component of motion, and meridional component of motion) on changes of intensities of tropical cyclones over the eastern North Pacific Ocean were examined for the periods 1982–87 and 1988–93. Backward multiple regressions were performed to relate these 10 variables to changes in maximum intensity (as determined by wind speed) over periods ranging from 12 to 72 h. Latitude, maximum wind speed, and the 12-h change of maximum wind speed were the most significant variables. Each of the 10 variables was statistically significant at the 95% level at one or more of the time periods. Speed of movement, the component of motion, and the meridional component of motion were the least significant factors. The statistical relationships were tested using independent data from 1994. The mean absolute forecast errors ranged from 3.0 m s−1 at 12 h to 13.2 m s−1 at 72 h using one of two sets of regression equations developed in this study.

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Jay S. Hobgood

Abstract

The maximum potential intensity (MPI) of a tropical cyclone represents a theoretical upper limit to the strength of the storm imposed by the laws of physics and the energy available to the system in the atmosphere and the ocean. The MPI in this study was computed using a method in which the cyclone is assumed to consist of the environment, an eyewall, and an eye. Calculation of the MPI requires a vertical sounding of temperature, the surface pressure, and the surface air temperature. The soundings used in this study were taken at Isla Socorro, Mexico, during the period 1994–97. The MPIs were compared to the minimum surface pressures for seven tropical cyclones that passed near Isla Socorro. The MPI provided an accurate indication of the potential for the atmosphere to support the intensification of a tropical cyclone. The thermodynamically based MPI also proved to be superior to an SST-based MPI.

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Jay S. Hobgood
and
John N. Rayner

Abstract

In recent years a number of different methods have been proposed for the inclusion of the effects of cumuli in numerical models of tropical cyclones. In this paper several of the Kuo-type parameterizations have been tested by simulating the development of tropical cyclones from identical sets of initial conditions. The use of the same model and initial conditions made it possible to determine the effects of the various parameterizations. In the simulations without radiative fluxes, significant differences in the rates of intensification were evident in certain cases. In those simulations with radiative fluxes, the various parameterizations also produced different diurnal oscillations of pressure and wind speed.

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Christopher C. Hennon
and
Jay S. Hobgood

Abstract

A new dataset of tropical cloud clusters, which formed or propagated over the Atlantic basin during the 1998–2000 hurricane seasons, is used to develop a probabilistic prediction system for tropical cyclogenesis (TCG). Using data from the National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) reanalysis (NNR), eight large-scale predictors are calculated at every 6-h interval of a cluster's life cycle. Discriminant analysis is then used to find a linear combination of the predictors that best separates the developing cloud clusters (those that became tropical depressions) and nondeveloping systems. Classification results are analyzed via composite and case study points of view.

Despite the linear nature of the classification technique, the forecast system yields useful probabilistic forecasts for the vast majority of the hurricane season. The daily genesis potential (DGP) and latitude predictors are found to be the most significant at nearly all forecast times. Composite results show that if the probability of development P < 0.7, TCG rarely occurs; if P > 0.9, genesis occurs about 40% of the time. A case study of Tropical Depression Keith (2000) illustrates the ability of the forecast system to detect the evolution of the large-scale environment from an unfavorable to favorable one. An additional case study of an early-season nondeveloping cluster demonstrates some of the shortcomings of the system and suggests possible ways of mitigating them.

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Stephen Lavin
,
Jay Hobgood
, and
Paul Kramer

Abstract

Traditionally, spatial distributions of continuous climatological variables have been displayed using isolines. The placement of isolines involves an assumption about the gradient of the variable being mapped. Because of the numerical value associated with an isoline, a degree of precision is associated with this type of map that may not be justified. Dot-density shading offers an alternative technique for displaying these spatial distributions. The continuous nature of the dot-density display makes it an effective means of thematically depicting variations in the magnitudes of climatological variables. This is demonstrated by maps of various climatological variables for Colorado and from an experimental global climate model.

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Randall S. Cerveny
and
Jay S. Hobgood

The log of the first voyage of Christopher Columbus to the New World provides valuable information on the meteorological conditions of September 1492. Comparison and analysis of the descriptive accounts of weather made by Columbus and his pilots to other available Columbian and modern data leads to two distinct perspectives on the Columbian voyage: an examination of the frequency of “calm” events, and an analysis of the lack of tropical storm activity. The major conclusions of the first portion of the study include: 1) The Columbian pilots' descriptions of “calms” related to travel slower than travel occurring during other portions of the voyage. That rate of travel compares favorably to calm winds and an oceanic current of 0.4 knots, a value close to modern-day values; 2) The frequency of “calm” events experienced by Christopher Columbus in 1492 is significantly higher than the most liberal estimates of calms in the North Atlantic over the last 100 years; and 3) The locations of the Columbian calms are generally in the same region currently experiencing the highest frequency of calms. The main finding of the second portion of the study is that, based on historical hurricane records from 1886 to 1989, the center of a hurricane would have passed within 100 km of Columbus only once in the past 104 years. Inclusion of tropical storms increases this number to four out of 104 years. Therefore, while Columbus may indeed have been fortunate to have avoided severe weather during his voyage, the odds decidedly were in his favor. This Columbian “weather luck” was due to a combination of 1) encountering abnormally strong anticyclonic flow over the eastern North Atlantic, 2) starting late enough in the hurricane season to significantly decrease the probability of experiencing a hurricane, and 3) taking a north and easterly voyage, thereby avoiding the area of maximum hurricane occurrence.

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Luke D. Whitney
and
Jay S. Hobgood

Abstract

An empirical relationship between climatological sea surface temperatures (SST) and the maximum intensities of tropical cyclones over the eastern North Pacific Ocean is developed from a 31-yr sample (1963–93). This relationship is compared with an empirical relationship for tropical cyclones over the Atlantic Ocean and with theoretical results. Over the period of study, the storms over the eastern North Pacific Ocean reached a lower percentage of their empirical maximum potential intensity (MPI) than tropical cyclones over the Atlantic Ocean. At the time of their maximum intensity, only 11% of eastern North Pacific storms reach 80% of their MPI, while 19% of the Atlantic tropical cyclones reach that proportion of their MPIs. Poleward recurvature of Atlantic storms over cooler waters appears to be a major factor in the difference between the two regions. The storms were stratified by latitude, longitude, the phase of the quasi-biennial oscillation (QBO), and the status of the El Niño phenomenon. Tropical cyclones that develop west of 110°W tend to reach a higher percentage of their MPI than storms developing farther east. Tropical cyclones also tended to reach a higher percentage of their MPI and to attain higher maximum intensities when the QBO was in its westerly phase.

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Kevin T. Law
and
Jay S. Hobgood

Abstract

An alternative 24-h statistical hurricane intensity model is presented and verified for 13 hurricanes during the 2004–05 seasons. The model uses a new method involving a discriminant function analysis (DFA) to select from a collection of multiple regression equations. These equations were developed to predict the future 24-h wind speed increase and the 24-h pressure drop that were constructed from a dataset of 103 hurricanes from 1988 to 2003 that utilized 25 predictors of rapid intensification. The accuracy of the 24-h wind speed increase models was tested and compared with the official National Hurricane Center (NHC) 24-h intensity forecasts, which are currently more accurate on average than other 24-h intensity models. Individual performances are shown for Hurricanes Charley (2004) and Katrina (2005) along with a summary of all 13 hurricanes in the study. The average error for the 24-h wind speed increase models was 11.83 kt (1 kt = 0.5144 m s−1) for the DFA-selected models and 12.53 kt for the official NHC forecast. When the DFA used the correctly selected model (CSM) for the same cases, the average error was 8.47 kt. For the 24-h pressure reduction models, the average error was 7.33 hPa for the DFA-selected models, and 5.85 hPa for the CSM. This shows that the DFA performed well against the NHC, but improvements can still be made to make the accuracy even better.

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Kevin R. Petty
and
Jay S. Hobgood

Abstract

The primary objective of this research is the development of a statistical model that will provide tropical cyclone (TC) intensity guidance for the eastern North Pacific (ENP) superior to that provided by climatology and persistence models. Toward this goal, the authors investigate the use of shear and thermal variables in statistical forecasts of TC intensity change. European Centre for Medium-Range Weather Forecasts (ECMWF) global analyses are used to develop an Eastern Pacific Intensity Change (EPIC) model, forecasting tropical cyclone intensity changes at 12-h intervals, out to 72 h. The dataset consists of ENP tropical cyclones during the years 1989–96 along with ECMWF analyses for those years.

The synoptic predictors examined in this study consist of shear and thermal variables, including zonal and meridional components of shear between 200 and 850 mb, the difference in temperature between 200 and 850 mb, and equivalent potential temperature at 700 mb. The time tendency of these variables is also explored, and multiple linear regression analysis is used to detect which variables best explain the variance in tropical cyclone intensity change in the ENP.

The EPIC model forecasts are compared to those from a climatology–persistence model developed from the 1989–96 dataset, and to the current operational statistical models, SHIFOR (a model based on climatology and persistence) and SHIPS (Statistical Hurricane Intensity Prediction Scheme—a model based on climatology, persistence, and synoptic variables), in the ENP basin for the 1997 and 1998 hurricane seasons. Results for these seasons reveal that EPIC may provide better intensity guidance than statistical models based on climatology and persistence, and confirm that the inclusion of synoptic predictors in a statistical intensity prediction scheme improves intensity change forecasts and that, overall, EPIC may better forecast intensity change in the ENP.

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