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John A. Knaff, Mark DeMaria, Charles R. Sampson, and James M. Gross

Abstract

Tropical cyclone track forecasting has improved recently to the point at which extending the official forecasts of both track and intensity to 5 days is being considered at the National Hurricane Center and the Joint Typhoon Warning Center. Current verification procedures at both of these operational centers utilize a suite of control models, derived from the “climatology” and “persistence” techniques, that make forecasts out to 3 days. To evaluate and verify 5-day forecasts, the current suite of control forecasts needs to be redeveloped to extend the forecasts from 72 to 120 h. This paper describes the development of 5-day tropical cyclone intensity forecast models derived from climatology and persistence for the Atlantic, the eastern North Pacific, and the western North Pacific Oceans. Results using independent input data show that these new models possess similar error and bias characteristics when compared with their predecessors in the North Atlantic and eastern North Pacific but that the west Pacific model shows a statistically significant improvement when compared with its forerunner. Errors associated with these tropical cyclone intensity forecast models are also shown to level off beyond 3 days in all of the basins studied.

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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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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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John A. Knaff, Charles R. Sampson, Patrick J. Fitzpatrick, Yi Jin, and Christopher M. Hill

Abstract

In 1980 the Holland tropical cyclone (TC) wind profile model was introduced. This simple model was originally intended to estimate the wind profile based on limited surface pressure information alone. For this reason and its relative simplicity, the model has been used in many practical applications. In this paper the potential of a simplified version of the Holland B parameter, which is related to the shape of the tangential wind profile, is explored as a powerful diagnostic tool for monitoring TC structure. The implementation examined is based on the limited information (maximum wind, central pressure, radius and pressure of the outer closed isobar, radii of operationally important wind radii, etc.) that is typically available in operational models and routine analyses of TC structure. This “simplified Holland B” parameter is shown to be sensitive to TC intensity, TC size, and the rate of radial decay of the tangential winds, but relatively insensitive to the radius of maximum winds. A climatology of the simplified Holland B parameter based on historical best-track data is also developed and presented, providing the expected natural ranges of variability. The relative simplicity, predictable variability, and desirable properties of the simplified Holland B parameter make it ideal for a variety of applications. Examples of how the simplified Holland B parameter can be used for improving forecaster guidance, developing TC structure tools, diagnosing TC model output, and understanding and comparing the climatological variations of TC structure are presented.

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John A. Knaff, Mark DeMaria, Debra A. Molenar, Charles R. Sampson, and Matthew G. Seybold

Abstract

A method to estimate objectively the surface wind fields associated with tropical cyclones using only data from multiple satellite platforms and satellite-based wind retrieval techniques is described. The analyses are computed on a polar grid using a variational data-fitting method that allows for the application of variable data weights to input data. The combination of gross quality control and the weighted variational analysis also produces wind estimates that have generally smaller errors than do the raw input data. The resulting surface winds compare well to the NOAA Hurricane Research Division H*Wind aircraft reconnaissance–based surface wind analyses, and operationally important wind radii estimated from these wind fields are shown to be generally more accurate than those based on climatological data. Most important, the analysis system produces global tropical cyclone surface wind analyses and related products every 6 h—without aircraft reconnaissance data. Also, the analysis and products are available in time for consideration by forecasters at the Joint Typhoon Warning Center, the Central Pacific Hurricane Center, and the National Hurricane Center in preparing their forecasts and advisories. This Multiplatform Tropical Cyclone Surface Wind Analysis (MTCSWA) product is slated to become an operationally supported product at the National Environmental Satellite Data and Information Service (NESDIS). The input data, analysis method, products, and verification statistics associated with the MTCSWA are discussed within.

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Charles R. Sampson, Efren A. Serra, John A. Knaff, and Joshua H. Cossuth

Abstract

The U.S. Navy is keenly interested in analyses and predictions of waves at sea due to their effects on important tasks such as shipping, base preparedness and disaster relief. U.S. Tropical Cyclone (TC) Forecast Centers routinely disseminate wind probabilities consistent with official TC forecasts worldwide, but do not do the same for wave forecasts. These probabilities are especially important at longer leads where TC forecast accuracy diminishes. This work describes global wave probabilities consistent with both the official TC forecasts and their wind probabilities. Real-time runs for 84 TCs between May 2018 and March 2019, with probabilities generated for 12-ft and 18-ft significant wave heights are used to calculate verification statistics. This results in 347, 319, 261, 214, 155, and 112 verification cases at lead times of 1, 2, 3, 4, and 5 days where each verification case consists of a 20x20 degree latitude longitude grid around the verifying TC position. When compared with wave probabilities generated solely by a global numerical weather prediction model, the wind probability-based algorithm demonstrates improved consistency with official forecasts and provides additional benefits. Those benefits include an improved capability to discriminate between 12-ft and 18-ft significant wave events and non-events. The verification statistics also shows that the wind probability-based algorithm has a consistent high bias. How these biases can be reduced in future efforts is also discussed.

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Charles R. Sampson, James L. Franklin, John A. Knaff, and Mark DeMaria

Abstract

Consensus forecasts (forecasts created by combining output from individual forecasts) have become an integral part of operational tropical cyclone track forecasting. Consensus aids, which generally have lower average errors than individual models, benefit from the skill and independence of the consensus members, both of which are present in track forecasting, but are limited in intensity forecasting. This study conducts experiments with intensity forecast aids on 4 yr of data (2003–06). First, the skill of the models is assessed; then simple consensus computations are constructed for the Atlantic, eastern North Pacific, and western North Pacific basins. A simple (i.e., equally weighted) consensus of three top-performing intensity forecast models is found to generally outperform the individual members in both the Atlantic and eastern North Pacific, and a simple consensus of two top-performing intensity forecast models is found to generally outperform the individual members in the western North Pacific.

An experiment using an ensemble of dynamical model track forecasts and a selection of model fields as input in a statistical–dynamical intensity forecast model to produce intensity consensus members is conducted for the western North Pacific only. Consensus member skill at 72 h is low (−0.4% to 14.2%), and there is little independence among the members. This experiment demonstrates that a consensus of these highly dependent members yields an aid that performs as well as the most skillful member. Finally, adding a less skillful, but more independent, dynamical model-based forecast aid to the consensus yields an 11-member consensus with mixed yet promising performance compared with the 10-model consensus.

Based on these findings, the simple three-member consensus model could be used as a standard of comparison for other deterministic ensemble methods for the Atlantic and eastern North Pacific. Both the two- and three-member consensus forecasts may also provide useful guidance for operational forecasters. Likewise, in the western North Pacific, the 10- and 11-member consensus could be used as operational forecast aids and standards of comparison for other ensemble intensity forecast methods.

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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, 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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Charles R. Sampson, James S. Goerss, John A. Knaff, Brian R. Strahl, Edward M. Fukada, and Efren A. Serra

Abstract

In 2016, the Joint Typhoon Warning Center extended forecasts of gale-force and other wind radii to 5 days. That effort and a thrust to perform postseason analysis of gale-force wind radii for the “best tracks” (the quality controlled and documented tropical cyclone track and intensity estimates released after the season) have prompted requirements for new guidance to address the challenges of both. At the same time, operational tools to estimate and predict wind radii continue to evolve, now forming a quality suite of gale-force wind radii analysis and forecasting tools. This work provides an update to real-time estimates of gale-force wind radii (a mean/consensus of gale-force individual wind radii estimates) that includes objective scatterometer-derived estimates. The work also addresses operational gale-force wind radii forecasting in that it provides an update to a gale-force wind radii forecast consensus, which now includes gale-force wind radii forecast error estimates to accompany the gale-force wind radii forecasts. The gale-force wind radii forecast error estimates are computed using predictors readily available in real time (e.g., consensus spread, initial size, and forecast intensity) so that operational reliability and timeliness can be ensured. These updates were all implemented in operations at the Joint Typhoon Warning Center by January 2018, and more updates should be expected in the coming years as new and improved guidance becomes available.

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