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John A. Knaff
,
Christopher J. Slocum
, and
Kate D. Musgrave

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.

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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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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
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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Andrea B. Schumacher
,
Mark DeMaria
, and
John A. Knaff

Abstract

A new product for estimating the 24-h probability of TC formation in individual 5° × 5° subregions of the North Atlantic, eastern North Pacific, and western North Pacific tropical basins is developed. This product uses environmental and convective parameters computed from best-track tropical cyclone (TC) positions, National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) analysis fields, and water vapor (∼6.7 μm wavelength) imagery from multiple geostationary satellite platforms. The parameters are used in a two-step algorithm applied to the developmental dataset. First, a screening step removes all data points with environmental conditions highly unfavorable to TC formation. Then, a linear discriminant analysis (LDA) is applied to the screened dataset. A probabilistic prediction scheme for TC formation is developed from the results of the LDA.

Coefficients computed by the LDA show that the largest contributors to TC formation probability are climatology, 850-hPa circulation, and distance to an existing TC. The product was evaluated by its Brier and relative operating characteristic skill scores and reliability diagrams. These measures show that the algorithm-generated probabilistic forecasts are skillful with respect to climatology, and that there is relatively good agreement between forecast probabilities and observed frequencies. As such, this prediction scheme has been implemented as an operational product called the National Environmental Satellite, Data, and Information Services (NESDIS) Tropical Cyclone Formation Probability (TCFP) product. The TCFP product updates every 6 h and displays plots of TC formation probability and input parameter values on its Web site. At present, the TCFP provides real-time, objective TC formation guidance used by tropical cyclone forecast offices in the Atlantic, eastern Pacific, and western Pacific basins.

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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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Charles R. Sampson
,
John A. Knaff
, and
Edward M. Fukada

Abstract

The Systematic Approach Forecast Aid (SAFA) has been in use at the Joint Typhoon Warning Center since the 2000 western North Pacific season. SAFA is a system designed for determination of erroneous 72-h track forecasts through identification of predefined error mechanisms associated with numerical weather prediction models. A metric for the process is a selective consensus in which model guidance suspected to have 72-h error greater than 300 n mi (1 n mi = 1.85 km) is first eliminated prior to calculating the average of the remaining model tracks. The resultant selective consensus should then provide improved forecasts over the nonselective consensus. In the 5 yr since its introduction into JTWC operations, forecasters have been unable to produce a selective consensus that provides consistent improved guidance over the nonselective consensus. Also, the rate at which forecasters exercised the selective consensus option dropped from approximately 45% of all forecasts in 2000 to 3% in 2004.

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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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