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John A. Knaff and Charles R. Sampson

Abstract

The National Hurricane Center (NHC) has a long history of forecasting the radial extent of gale force or 34-knot (kt; where 1 kt = 0.51 m s−1) winds for tropical cyclones in their area of responsibility. These are referred to collectively as gale force wind radii forecasts. These forecasts are generated as part of the 6-hourly advisory messages made available to the public. In 2004, NHC began a routine of postanalysis or “best tracking” of gale force wind radii that continues to this day. At approximately the same time, a statistical wind radii forecast, based solely on climatology and persistence, was implemented so that NHC all-wind radii forecasts could be evaluated for skill. This statistical wind radii baseline forecast is also currently used in several applications as a substitute for or to augment NHC wind radii forecasts. This investigation examines the performance of NHC gale force wind radii forecasts in the North Atlantic over the last decade. Results presented within indicate that NHC’s gale force wind radii forecasts have increased in skill relative to the best tracks by several measures, and now significantly outperform statistical wind radii baseline forecasts. These results indicate that it may be time to reinvestigate whether applications that depend on wind radii forecast information can be improved through better use of NHC wind radii forecast information.

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Charles R. Sampson and Ann J. Schrader

The Automated Tropical Cyclone Forecasting System (ATCF) is software intended to automate and optimize much of the tropical cyclone forecasting process. The system features global tracking capability, a suite of objective aids, and a user interface that allows simultaneous tracking of multiple tropical cyclones. The version discussed in this article, ATCF 3.2, runs on UNIX workstations. The Joint Typhoon Warning Center in Guam, the Naval Pacific Meteorology and Oceanography Center in Pearl Harbor, and the Naval Atlantic Meteorology and Oceanography Center in Norfolk successfully used ATCF 3.2 during the 1998 tropical cyclone season.

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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, 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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Kenneth R. Knapp, John A. Knaff, Charles R. Sampson, Gustavo M. Riggio, and Adam D. Schnapp

Abstract

The western North Pacific Ocean is the most active tropical cyclone (TC) basin. However, recent studies are not conclusive on whether the TC activity is increasing or decreasing, at least when calculations are based on maximum sustained winds. For this study, TC minimum central pressure data are analyzed in an effort to better understand historical typhoons. Best-track pressure reports are compared with aircraft reconnaissance observations; little bias is observed. An analysis of wind and pressure relationships suggests changes in data and practices at numerous agencies over the historical record. New estimates of maximum sustained winds are calculated using recent wind–pressure relationships and parameters from International Best Track Archive for Climate Stewardship (IBTrACS) data. The result suggests potential reclassification of numerous typhoons based on these pressure-based lifetime maximum intensities. Historical documentation supports these new intensities in many cases. In short, wind reports in older best-track data are likely of low quality. The annual activity based on pressure estimates is found to be consistent with aircraft reconnaissance and between agencies; however, reconnaissance ended in the western Pacific in 1987. Since then, interagency differences in maximum wind estimates noted here and by others also exist in the minimum central pressure reports. Reconciling these recent interagency differences is further exasperated by the lack of adequate ground truth. This study suggests efforts to intercalibrate the interagency intensity estimate methods. Conducting an independent and homogeneous reanalysis of past typhoon activity is likely necessary to resolve the remaining discrepancies in typhoon intensity records.

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John A. Knaff, Christopher J. Slocum, Kate D. Musgrave, Charles R. Sampson, and Brian R. Strahl

Abstract

A relatively simple method to estimate tropical cyclone (TC) wind radii from routinely available information including storm data (location, motion, and intensity) and TC size is introduced. The method is based on a combination of techniques presented in previous works and makes an assumption that TCs are largely symmetric and that asymmetries are based solely on storm motion and location. The method was applied to TC size estimates from two sources: infrared satellite imagery and global model analyses. The validation shows that the methodology is comparable with other objective methods based on the error statistics. The technique has a variety of practical research and operational applications, some of which are also discussed.

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Charles R. Sampson, John Kaplan, John A. Knaff, Mark DeMaria, and Chris A. Sisko

Abstract

Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)−1; or 12.9, 15.4, and 18.0 m s−1 (24 h)−1] for the 24-h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50% probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40% threshold for producing the RI aid initially. The 40% threshold is available for approximately 8% of all verifying forecasts, produces approximately 4% reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%–20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill).

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

The mean absolute error of the official tropical cyclone (TC) intensity forecasts from the National Hurricane Center (NHC) and the Joint Typhoon Warning Center (JTWC) shows limited evidence of improvement over the past two decades. This result has sometimes erroneously been used to conclude that little or no progress has been made in the TC intensity guidance models. This article documents statistically significant improvements in operational TC intensity guidance over the past 24 years (1989–2012) in four tropical cyclone basins (Atlantic, eastern North Pacific, western North Pacific, and Southern Hemisphere). Errors from the best available model have decreased at 1%–2% yr−1 at 24–72 h, with faster improvement rates at 96 and 120 h. Although these rates are only about one-third to one-half of the rates of reduction of the track forecast models, most are statistically significant at the 95% level. These error reductions resulted from improvements in statistical–dynamical intensity models and consensus techniques that combine information from statistical–dynamical and dynamical models. The reason that the official NHC and JTWC intensity forecast errors have decreased slower than the guidance errors is because in the first half of the analyzed period, their subjective forecasts were more accurate than any of the available guidance. It is only in the last decade that the objective intensity guidance has become accurate enough to influence the NHC and JTWC forecast errors.

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Mark DeMaria, John A. Knaff, Richard Knabb, Chris Lauer, Charles R. Sampson, and Robert T. DeMaria

Abstract

The National Hurricane Center (NHC) Hurricane Probability Program (HPP) was implemented in 1983 to estimate the probability that the center of a tropical cyclone would pass within 60 n mi of a set of specified points out to 72 h. Other than periodic updates of the probability distributions, the HPP remained unchanged through 2005. Beginning in 2006, the HPP products were replaced by those from a new program that estimates probabilities of winds of at least 34, 50, and 64 kt, and incorporates uncertainties in the track, intensity, and wind structure forecasts. This paper describes the new probability model and a verification of the operational forecasts from the 2006–07 seasons.

The new probabilities extend to 120 h for all tropical cyclones in the Atlantic and eastern, central, and western North Pacific to 100°E. Because of the interdependence of the track, intensity, and structure forecasts, a Monte Carlo method is used to generate 1000 realizations by randomly sampling from the operational forecast center track and intensity forecast error distributions from the past 5 yr. The extents of the 34-, 50-, and 64-kt winds for the realizations are obtained from a simple wind radii model and its underlying error distributions.

Verification results show that the new probability model is relatively unbiased and skillful as measured by the Brier skill score, where the skill baseline is the deterministic forecast from the operational centers converted to a binary probabilistic forecast. The model probabilities are also well calibrated and have high confidence based on reliability diagrams.

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John A. Knaff, Mark DeMaria, Charles R. Sampson, James E. Peak, James Cummings, and Wayne H. Schubert

Abstract

The upper oceanic temporal response to tropical cyclone (TC) passage is investigated using a 6-yr daily record of data-driven analyses of two measures of upper ocean energy content based on the U.S. Navy’s Coupled Ocean Data Assimilation System and TC best-track records. Composite analyses of these data at points along the TC track are used to investigate the type, magnitude, and persistence of upper ocean response to TC passage, and to infer relationships between routinely available TC information and the upper ocean response. Upper oceanic energy decreases in these metrics are shown to persist for at least 30 days—long enough to possibly affect future TCs. Results also indicate that TC kinetic energy (KE) should be considered when assessing TC impacts on the upper ocean, and that existing TC best-track structure information, which is used here to estimate KE, is sufficient for such endeavors. Analyses also lead to recommendations concerning metrics of upper ocean energy. Finally, parameterizations for the lagged, along-track, upper ocean response to TC passage are developed. These show that the sea surface temperature (SST) is best related to the KE and the latitude whereas the upper ocean energy is a function of KE, initial upper ocean energy conditions, and translation speed. These parameterizations imply that the 10-day lagged SST cooling is approximately 0.7°C for a “typical” TC at 30° latitude, whereas the same storm results in 10-day (30-day) lagged decreases of upper oceanic energy by about 12 (7) kJ cm−2 and a 0.5°C (0.3°C) cooling of the top 100 m of ocean.

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