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Mark DeMaria
,
John A. Knaff
, and
Bernadette H. Connell

Abstract

A parameter to evaluate the potential for tropical cyclone formation (genesis) in the North Atlantic between Africa and the Caribbean islands is developed. Climatologically, this region is the source of about 40% of the Atlantic basin tropical cyclones but roughly 60% of the major hurricanes. The genesis parameter is the product of appropriately scaled 5-day running mean vertical shear, vertical instability, and midlevel moisture variables. The instability and shear variables are calculated from operational NCEP analyses, and the midlevel moisture variable is determined from cloud-cleared GOES water vapor imagery. The average shear and instability variables from 1991 to 1999 and moisture variable from 1995 to 1999 indicate that tropical cyclone formation in the early part of the season is limited by the vertical instability and midlevel moisture. Formation at the end of the season is limited by the vertical shear. On average, there is only a short period from mid-July to mid-October when all three variables are favorable for development. This observation helps explains why tropical cyclone formation in the tropical Atlantic has such a peaked distribution in time. The parameter also helps explain intra- and interseasonal variability in tropical cyclone formation. An independent evaluation of the parameter and possible applications to operational forecasting are presented using data from the 2000 hurricane season. The possibility of determining additional thermodynamic information from the GOES sounder is also discussed.

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John A. Knaff
,
Charles R. Sampson
, and
Mark DeMaria

Abstract

The current version of the Statistical Typhoon Intensity Prediction Scheme (STIPS) used operationally at the Joint Typhoon Warning Center (JTWC) to provide 12-hourly tropical cyclone intensity guidance through day 5 is documented. STIPS is a multiple linear regression model. It was developed using a “perfect prog” assumption and has a statistical–dynamical framework, which utilizes environmental information obtained from Navy Operational Global Analysis and Prediction System (NOGAPS) analyses and the JTWC historical best track for development. NOGAPS forecast fields are used in real time. A separate version of the model (decay-STIPS) is produced that accounts for the effects of landfall by using an empirical inland decay model. Despite their simplicity, STIPS and decay-STIPS produce skillful intensity forecasts through 4 days, based on a 48-storm verification (July 2003–October 2004). Details of this model’s development and operational performance are presented.

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John A. Knaff
,
Charles R. Sampson
, and
Galina Chirokova

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.

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John A. Knaff
,
James P. Kossin
, and
Mark DeMaria

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.

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Christopher J. Slocum
,
John A. Knaff
, and
Stephanie N. Stevenson

Abstract

With several seasons of Geostationary Lightning Mapper (GLM) data, this work revisits incorporating lightning observations into operational tropical cyclone rapid intensification guidance. GLM provides freely available, real-time lightning data over the central and eastern North Pacific and North Atlantic Oceans. A long-term lightning dataset is needed to use GLM in a statistical–dynamical operational application to capture the relationship between lightning and the rare occurrence of rapid intensification. This work uses the World Wide Lightning Location Network (WWLLN) dataset from 2005 to 2017 to develop lightning-based predictors for rapid intensification guidance models. The models mimic the operational Statistical Hurricane Intensity Prediction Scheme Rapid Intensification Index and Rapid Intensification Prediction Aid frameworks. The frameworks are averaged to form a consensus as a means to isolate the impact of the lightning predictors. Two configurations for lightning predictors are assessed: a spatial configuration with 0–100-km inner core and 200–300-km rainband area for the preceding 6-h predictors and a temporal configuration with an inner core only for the preceding 0–1, 0–6, and 6–12 h. When tested on the 2018–21 seasons, the temporal configuration adds skill primarily to the 12–48-h forecasts when compared to the no-lightning version and rapid intensification operational consensus. When WWLLN is replaced with GLM, minor changes to the prediction are observed suggesting that this approach is suitable for operational applications and provides a new baseline for tropical cyclone lightning-based rapid intensification aids.

Significance Statement

The forecasting of rare, yet critical, tropical cyclone rapid intensification events continues to be challenging. The current operational tools to anticipate rapid intensity changes use a combination of numerical weather prediction–derived environmental conditions and satellite-based cloud top temperature variations of deep convection. Here, we use freely available Geostationary Lightning Mapper data, which provide independent information about convection, in similar intensity guidance frameworks using temporal and spatial aspects of lightning variability. Our results show an improvement in short-term (12–48 h) rapid intensification forecasts by using temporal lightning information, and our investigation highlights that users of Geostationary Lightning Mapper lightning information should be cognizant of the influence and impact of land on these observations.

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John A. Knaff
,
Charles R. Sampson
, and
Kate D. Musgrave

Abstract

This work describes tropical cyclone rapid intensification forecast aids designed for the western North Pacific tropical cyclone basin and for use at the Joint Typhoon Warning Center. Two statistical methods, linear discriminant analysis and logistic regression, are used to create probabilistic forecasts for seven intensification thresholds including 25-, 30-, 35-, and 40-kt changes in 24 h, 45- and 55-kt in 36 h, and 70-kt in 48 h (1 kt = 0.514 m s−1). These forecast probabilities are further used to create an equally weighted probability consensus that is then used to trigger deterministic forecasts equal to the intensification thresholds once the probability in the consensus reaches 40%. These deterministic forecasts are incorporated into an operational intensity consensus forecast as additional members, resulting in an improved intensity consensus for these important and difficult to predict cases. Development of these methods is based on the 2000–15 typhoon seasons, and independent performance is assessed using the 2016 and 2017 typhoon seasons. In many cases, the probabilities have skill relative to climatology and adding the rapid intensification deterministic aids to the operational intensity consensus significantly reduces the negative forecast biases.

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John A. Knaff
,
Charles R. Sampson
, and
Kate D. Musgrave

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.

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John A. Knaff
,
Charles R. Sampson
, and
Brian R. Strahl

Abstract

In late 2017, the Rapid Intensification Prediction Aid (RIPA) was transitioned to operations at the Joint Typhoon Warning Center (JTWC). RIPA probabilistically predicts seven rapid intensification (RI) thresholds over three separate time periods: 25-, 30-, 35-, and 40-kt (1 kt ≈ 0.51 m s−1) increases in 24 h (RI25, RI30, RI35, RI40); 45- and 55-kt increases in 36 h (RI45 and RI55); and 70-kt increases in 48 h (RI70). RIPA’s probabilistic forecasts are also used to produce deterministic forecasts when probabilities exceed 40%, and the latter are included as members of the operational intensity consensus forecast aid. RIPA, initially designed for the western North Pacific, performed remarkably well in all JTWC areas of responsibility (AOR) and is now incorporated into JTWC’s ever improving suite of intensity forecast guidance. Even so, making real-time operational RIPA forecasts exposed some methodological weaknesses such as overprediction of RI for weak/disorganized systems (i.e., systems with maximum winds less than 35 kt), prediction of RI during landfall, input data reliability, and statistical inconsistencies. Modifications to the deterministic forecasts that address these issues are presented, and newly derived and more statistically consistent models are developed using data from all of JTWC’s AORs. The updated RIPA is tested as it would be run in operations and verified using a 2-yr (2018–19) independent sample. The performance from this test indicates the new RIPA—when compared to its predecessor—has improved probabilistic verification statistics, and similar deterministic skill while using fewer predictors to make forecasts.

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Charles R. Sampson
,
James A. Hansen
,
Paul A. Wittmann
,
John A. Knaff
, and
Andrea Schumacher

Abstract

Development of a 12-ft-seas significant wave height ensemble consistent with the official tropical cyclone intensity, track, and wind structure forecasts and their errors from the operational U.S. tropical cyclone forecast centers is described. To generate the significant wave height ensemble, a Monte Carlo wind speed probability algorithm that produces forecast ensemble members is used. These forecast ensemble members, each created from the official forecast and randomly sampled errors from historical official forecast errors, are then created immediately after the official forecast is completed. Of 1000 forecast ensemble members produced by the wind speed algorithm, 128 of them are selected and processed to produce wind input for an ocean surface wave model. The wave model is then run once per realization to produce 128 possible forecasts of significant wave height. Probabilities of significant wave height at critical thresholds can then be computed from the ocean surface wave model–generated significant wave heights. Evaluations of the ensemble are provided in terms of maximum significant wave height and radius of 12-ft significant wave height—two parameters of interest to both U.S. Navy meteorologists and U.S. Navy operators. Ensemble mean errors and biases of maximum significant wave height and radius of 12-ft significant wave height are found to be similar to those of a deterministic version of the same algorithm. Ensemble spreads capture most verifying maximum and radii of 12-ft significant wave heights.

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Daniel T. Lindsey
,
Donald W. Hillger
,
Louie Grasso
,
John A. Knaff
, and
John F. Dostalek

Abstract

By combining observations from the Geostationary Operational Environmental Satellite (GOES) 3.9- and 10.7-μm channels, the reflected component of the 3.9-μm radiance can be isolated. In this paper, these 3.9-μm reflectivity measurements of thunderstorm tops are studied in terms of their climatological values and their utility in diagnosing cloud-top microphysical structure. These measurements provide information about internal thunderstorm processes, including updraft strength, and may be useful for severe weather nowcasting. Three years of summertime thunderstorm-top 3.9-μm reflectivity values are analyzed to produce maps of climatological means across the United States. Maxima occur in the high plains and Rocky Mountain regions, while lower values are observed over much of the eastern United States. A simple model is used to establish a relationship between 3.9-μm reflectivity and ice crystal size at cloud top. As the mean diameter of a cloud-top ice crystal distribution decreases, more solar radiation near 3.9 μm is reflected. Using the North American Regional Reanalysis dataset, the thermodynamic environment that favors thunderstorms with large 3.9-μm reflectivity values is identified. In the high plains and mountains, environments with relatively dry boundary layers, steep lapse rates, and large vertical shear values favor thunderstorms with enhanced 3.9-μm reflectivity. Thunderstorm processes that lead to small ice crystals at cloud top are discussed, and a possible relationship between updraft strength and 3.9-μm reflectivity is presented.

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