Charles R. Sampson

The Automated Tropical Cyclone Forecasting System (Version 3.2)

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.

Is Tropical Cyclone Intensity Guidance Improving

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 tec...

Statistical, 5-Day Tropical Cyclone Intensity Forecasts Derived from Climatology and Persistence

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 we...

An Operational Statistical Typhoon Intensity Prediction Scheme for the Western North Pacific

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.

Statistical tropical cyclone wind radii prediction using climatology and persistence

An operational model used to predict tropical cyclone wind structure in terms of significant wind radii (i.e., 34-, 50-, and 64-kt wind radii, where 1 kt 0.52 m s 1 ) at the National Oceanic and Atmospheric Administration/National Hurricane Center (NHC) and the Department of Defense/Joint Typhoon Warning Center (JTWC) is described. The statistical-parametric model employs aspects of climatology and persistence to forecast tropical cyclone wind radii through 5 days. Separate versions of the model are created for the Atlantic, east Pacific, and western North Pacific by statistically fitting a modified Rankine vortex, which is generalized to allow wavenumber-1 asymmetries, to observed values of tropical cyclone wind radii as reported by NHC and JTWC. Descriptions of the developmental data and methods used to formulate the model are given. A 2-yr verification and comparison with operational forecasts and an independently developed wind radii forecast method that also employs climatology and persistence suggests that the statistical-parametric model does a good job of forecasting wind radii. The statistical-parametric model also provides reliable operational forecasts that serve as a baseline for evaluating the skill of operational forecasts and other wind radii forecast methods in these tropical cyclone basins.

Real–Time Internet Distribution of Satellite Products for Tropical Cyclone Reconnaissance

Abstract Tropical cyclone (TC) monitoring requires the use of multiple satellites and sensors to accurately assess TC location and intensity. Visible and infrared (vis/IR) data provide the bulk of TC information, but upper–level cloud obscurations inherently limit this important dataset during a storms life cycle. Passive microwave digital data and imagery can provide key storm structural details and offset many of the vis/IR spectral problems. The ability to view storm rainbands, eyewalls, impacts of shear, and exposed low–level circulations, whether it is day or night, makes passive microwave data a significant tool for the satellite analyst. Passive microwave capabilities for TC reconnaissance are demonstrated via a near–real–time Web page created by the Naval Research Laboratory in Monterey, California. Examples are used to illustrate tropical cyclone monitoring. Collocated datasets are incorporated to enable the user to see many aspects of a storms organization and development by quickly accessing ...

A history of western North Pacific tropical cyclone track forecast skill

Abstract The tropical cyclone (TC) track forecasting skill of operational numerical weather prediction (NWP) models and their consensus is examined for the western North Pacific from 1992 to 2002. The TC track forecasting skill of the operational NWP models is steadily improving. For the western North Pacific, the typical 72-h model forecast error has decreased from roughly 600 km to roughly 400 km over the past ten years and is now comparable to the typical 48-h model forecast error of 10 years ago. In this study the performance of consensus aids that are formed whenever the TC track forecasts from at least two models from a specified pool of operational NWP models are available is examined. The 72-h consensus forecast error has decreased from about 550 km to roughly 310 km over the past ten years and is now better than the 48-h consensus forecast error of 10 years ago. For 2002, the 72-h forecast errors for a consensus computed from a specified pool of two, five, seven, and eight models were 357, 342, 3...

An Automated, Objective, Multiple-Satellite-Platform Tropical Cyclone Surface Wind Analysis

AbstractA 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 ...

A New Method for Estimating Tropical Cyclone Wind Speed Probabilities

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 through2005.Beginningin2006,theHPPproductswerereplacedbythosefromanewprogramthatestimates 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 westernNorthPacificto1008E.Becauseoftheinterdependenceofthetrack,intensity,andstructureforecasts, 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.

Experiments with a Simple Tropical Cyclone Intensity Consensus

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.