Statistical Tropical Cyclone Wind Radii Prediction Using Climatology and Persistence

2007 ◽  
Vol 22 (4) ◽  
pp. 781-791 ◽  
Author(s):  
John A. Knaff ◽  
Charles R. Sampson ◽  
Mark DeMaria ◽  
Timothy P. Marchok ◽  
James M. Gross ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Department Of Defense ◽  
Parametric Model ◽  
Forecast Method ◽  
Operational Model ◽  
Wind Structure ◽  
East Pacific ◽  
Operational Forecasts ◽  
National Hurricane Center ◽  
Joint Typhoon Warning Center

Abstract 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.

A New Method for Estimating Tropical Cyclone Wind Speed Probabilities

2009 ◽  
Vol 24 (6) ◽  
pp. 1573-1591 ◽  
Author(s):  
Mark DeMaria ◽  
John A. Knaff ◽  
Richard Knabb ◽  
Chris Lauer ◽  
Charles R. Sampson ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Probability Distributions ◽  
Forecast Error ◽  
Probability Model ◽  
Skill Score ◽  
Wind Structure ◽  
Operational Forecasts ◽  
Error Distributions ◽  
Center Track ◽  
National Hurricane Center

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.

Wind Structure Discrepancies between Two Best Track Datasets for Western North Pacific Tropical Cyclones

2016 ◽  
Vol 144 (12) ◽  
pp. 4533-4551 ◽  
Author(s):  
Jinjie Song ◽  
Philip J. Klotzbach
Keyword(s):  
Tropical Cyclone ◽  
North Pacific ◽  
Western North Pacific ◽  
Shape Parameter ◽  
Surface Wind ◽  
Japan Meteorological Agency ◽  
Wind Structure ◽  
Linear Relationships ◽  
Wind Analysis ◽  
Joint Typhoon Warning Center

Abstract Symmetric and wavenumber-1 asymmetric characteristics of western North Pacific tropical cyclone (TC) outer wind structures are compared between best tracks from the Joint Typhoon Warning Center (JTWC) and the Japan Meteorological Agency (JMA) from 2004 to 2014 as well as the Multiplatform Tropical Cyclone Surface Wind Analysis (MTCSWA) product from 2007 to 2014. Significant linear relationships of averaged wind radii are obtained among datasets, in which both gale-force and storm-force wind radii are generally estimated slightly smaller (much larger) by JTWC (JMA) than by MTCSWA. These correlations are strongly related to TC intensity relationships discussed in earlier work. Moreover, JTWC (JMA) on average represents a smaller (greater) derived shape parameter than MTCSWA does, implying that JTWC (JMA) typically assesses a more compact (less compact) storm than MTCSWA. For the wavenumber-1 asymmetry, large differences among datasets are found regardless of the magnitude or the direction of the longest radius. JTWC estimates more asymmetric storms than JMA, and it provides greater wavenumber-1 asymmetry magnitudes on average. Asymmetric storms are most frequently oriented toward the east, northeast, and north in JTWC and MTCSWA, whereas they are most frequently oriented toward the southeast, east, and northeast in JMA. The direction of the longest gale-force (storm force) wind radius in JTWC is statistically rotated 18° (32°) clockwise to that in JMA. Although the wind radii in JTWC are of higher quality than those in JMA when using MTCSWA as a baseline, there remains a need to provide a consistent and reliable wind radii estimating process among operational centers.

scholarly journals A Technique to Determine the Radius of Maximum Wind of a Tropical Cyclone

2008 ◽  
Vol 23 (5) ◽  
pp. 1007-1015 ◽  
Author(s):  
France Lajoie ◽  
Kevin Walsh
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Simple Technique ◽  
Cloud Data ◽  
Maximum Wind ◽  
Wind Structure ◽  
The Mean ◽  
The Difference ◽  
Two Parameters ◽  
National Hurricane Center

Abstract A simple technique is developed that enables the radius of maximum wind of a tropical cyclone to be estimated from satellite cloud data. It is based on the characteristic cloud and wind structure of the eyewall of a tropical cyclone, after the method developed by Jorgensen more than two decades ago. The radius of maximum wind is shown to be partly dependent on the radius of the eye and partly on the distance from the center to the top of the most developed cumulonimbus nearest to the cyclone center. The technique proposed here involves the analysis of high-resolution IR and microwave satellite imagery to determine these two parameters. To test the technique, the derived radius of maximum wind was compared with high-resolution wind analyses compiled by the U.S. National Hurricane Center and the Atlantic Oceanographic and Meteorological Laboratory. The mean difference between the calculated radius of maximum wind and that determined from observations is 2.8 km. Of the 45 cases considered, the difference in 50% of the cases was ≤2 km, for 33% it was between 3 and 4 km, and for 17% it was ≥5 km, with only two large differences of 8.7 and 10 km.

scholarly journals GPCE-AX: An Anisotropic Extension to the Goerss Predicted Consensus Error in Tropical Cyclone Track Forecasts

2011 ◽  
Vol 26 (3) ◽  
pp. 416-422 ◽  
Author(s):  
James A. Hansen ◽  
James S. Goerss ◽  
Charles Sampson
Keyword(s):  
Tropical Cyclone ◽  
Forecast Error ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Consensus Forecasts ◽  
The Mean ◽  
Along Track ◽  
National Hurricane Center ◽  
Joint Typhoon Warning Center ◽  
Initial Intensity

Abstract A method to predict an anisotropic expected forecast error distribution for consensus forecasts of tropical cyclone (TC) tracks is presented. The method builds upon the Goerss predicted consensus error (GPCE), which predicts the isotropic radius of the 70% isopleth of expected TC track error. Consensus TC track forecasts are computed as the mean of a collection of TC track forecasts from different models and are basin dependent. A novel aspect of GPCE is that it uses not only the uncertainty in the collection of constituent models to predict expected error, but also other features of the predicted storm, including initial intensity, forecast intensity, and storm speed. The new method, called GPCE along–across (GPCE-AX), takes a similar approach but separates the predicted error into across-track and along-track components. GPCE-AX has been applied to consensus TC track forecasts in the Atlantic (CONU/TVCN, where CONU is consensus version U and TVCN is the track variable consensus) and in the western North Pacific (consensus version W, CONW). The results for both basins indicate that GPCE-AX either outperforms or is equal in quality to GPCE in terms of reliability (the fraction of time verification is bound by the 70% uncertainty isopleths) and sharpness (the area bound by the 70% isopleths). GPCE-AX has been implemented at both the National Hurricane Center and at the Joint Typhoon Warning Center for real-time testing and evaluation.

A Global Statistical–Dynamical Tropical Cyclone Wind Radii Forecast Scheme

2017 ◽  
Vol 32 (2) ◽  
pp. 629-644 ◽  
Author(s):  
John A. Knaff ◽  
Charles R. Sampson ◽  
Galina Chirokova
Keyword(s):  
Tropical Cyclone ◽  
Surface Wind ◽  
Global Model ◽  
Wind Pressure ◽  
Forecast Method ◽  
Wind Model ◽  
Global Models ◽  
Forecast Performance ◽  
Wind Structure ◽  
Dynamical Method

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.

scholarly journals The Impact of Best Track Discrepancies on Global Tropical Cyclone Climatologies using IBTrACS

2014 ◽  
Vol 142 (10) ◽  
pp. 3881-3899 ◽  
Author(s):  
Carl J. Schreck ◽  
Kenneth R. Knapp ◽  
James P. Kossin
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Historical Analysis ◽  
The West ◽  
West Pacific ◽  
Global Context ◽  
The North ◽  
The Impact ◽  
National Hurricane Center ◽  
Joint Typhoon Warning Center

Abstract Using the International Best Track Archive for Climate Stewardship (IBTrACS), the climatology of tropical cyclones is compared between two global best track datasets: 1) the World Meteorological Organization (WMO) subset of IBTrACS (IBTrACS-WMO) and 2) a combination of data from the National Hurricane Center and the Joint Typhoon Warning Center (NHC+JTWC). Comparing the climatologies between IBTrACS-WMO and NHC+JTWC highlights some of the heterogeneities inherent in these datasets for the period of global satellite coverage 1981–2010. The results demonstrate the sensitivity of these climatologies to the choice of best track dataset. Previous studies have examined best track heterogeneities in individual regions, usually the North Atlantic and west Pacific. This study puts those regional issues into their global context. The differences between NHC+JTWC and IBTrACS-WMO are greatest in the west Pacific, where the strongest storms are substantially weaker in IBTrACS-WMO. These disparities strongly affect the global measures of tropical cyclone activity because 30% of the world’s tropical cyclones form in the west Pacific. Because JTWC employs similar procedures throughout most of the globe, the comparisons in this study highlight differences between WMO agencies. For example, NHC+JTWC has more 96-kt (~49 m s−1) storms than IBTrACS-WMO in the west Pacific but fewer in the Australian region. This discrepancy probably points to differing operational procedures between the WMO agencies in the two regions. Without better documentation of historical analysis procedures, the only way to remedy these heterogeneities will be through systematic reanalysis.

scholarly journals Changes of Tropical Cyclone Size in three Oceanic Basins of the Northern Hemisphere since 2001

2017 ◽  
Author(s):  
banglin zhang
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
North Pacific ◽  
Japan Meteorological Agency ◽  
Data Sets ◽  
The North ◽  
Sea Surface Temperature Anomaly ◽  
Storm Duration ◽  
National Hurricane Center ◽  
Joint Typhoon Warning Center

In this study the latest changes of tropical cyclone size are analyzed based on linear and quadratic curve fittings of the National Hurricane Center (NHC)/Joint Typhoon Warning Center (JTWC) best track data for the radius of maximum wind (RMW), the average radius of 34-kt wind (AR34), and the storm duration index “storm days” (SD) in three oceanic basins of the North Atlantic (NATL), the Western North Pacific (WPAC) and the Eastern North Pacific (EPAC). The computations are done separately for two categories of tropical cyclones: tropical storms (TS), and hurricanes in NATL and EPAC or typhoons in WPAC (HT). The results show that the RMW trends for TS are positive in all basins, and the RMW trends for HT are positive in the NATL basin, but negative in the WPAC and EPAC basins. The AR34 changes are more complex due to the fact that they reflect not only the strength of tropical cyclones, but also the environmental conditions. The trends of two other data sets, with WPAC dataset from the Japan Meteorological Agency (JMA) and the extended best track dataset for NATL and EPAC from NESDIS/RAMMB, are also consistent with the trends derived from the 16-year best track data. The relationships between storm size and sea surface temperature anomaly and the departure from the zonal mean have also been investigated, and some statistically significant correlations are found.

scholarly journals Operational Forecasting of Tropical Cyclone Rapid Intensification at the National Hurricane Center

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 683
Author(s):  
Mark DeMaria ◽  
James L. Franklin ◽  
Matthew J. Onderlinde ◽  
John Kaplan
Keyword(s):  
Tropical Cyclone ◽  
Absolute Error ◽  
Baseline Period ◽  
Probability Of Detection ◽  
Rapid Intensification ◽  
Improvement Program ◽  
Deterministic Models ◽  
Operational Forecasting ◽  
National Hurricane Center ◽  
Made In

Although some recent progress has been made in operational tropical cyclone (TC) intensity forecasting, the prediction of rapid intensification (RI) remains a challenging problem. To document RI forecast progress, deterministic and probabilistic operational intensity models used by the National Hurricane Center (NHC) are briefly reviewed. Results show that none of the deterministic models had RI utility from 1991 to about 2015 due to very low probability of detection, very high false alarm ratio, or both. Some ability to forecast RI has emerged since 2015, with dynamical models being the best guidance for the Atlantic and statistical models the best RI guidance for the eastern North Pacific. The first probabilistic RI guidance became available in 2001, with several upgrades since then leading to modest skill in recent years. A tool introduced in 2018 (DTOPS) is currently the most skillful among NHC’s probabilistic RI guidance. To measure programmatic progress in forecasting RI, the Hurricane Forecast Improvement Program has introduced a new RI metric that uses the traditional mean absolute error but restricts the sample to only those cases where RI occurred in the verifying best track or was forecast. By this metric, RI forecasts have improved by ~20–25% since the 2015–2017 baseline period.

scholarly journals Observed Boundary Layer Wind Structure and Balance in the Hurricane Core. Part I: Hurricane Georges

2006 ◽  
Vol 63 (9) ◽  
pp. 2169-2193 ◽  
Author(s):  
Jeffrey D. Kepert
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Tropical Cyclone ◽  
Radial Profile ◽  
Lower Altitude ◽  
Near Surface ◽  
Wind Structure ◽  
The Right ◽  
Tropical Cyclone Boundary Layer ◽  
Upper Boundary

Abstract The GPS dropsonde allows observations at unprecedentedly high horizontal and vertical resolution, and of very high accuracy, within the tropical cyclone boundary layer. These data are used to document the boundary layer wind field of the core of Hurricane Georges (1998) when it was close to its maximum intensity. The spatial variability of the boundary layer wind structure is found to agree very well with the theoretical predictions in the works of Kepert and Wang. In particular, the ratio of the near-surface wind speed to that above the boundary layer is found to increase inward toward the radius of maximum winds and to be larger to the left of the track than to the right, while the low-level wind maximum is both more marked and at lower altitude on the left of the storm track than on the right. However, the expected supergradient flow in the upper boundary layer is not found, with the winds being diagnosed as close to gradient balance. The tropical cyclone boundary layer model of Kepert and Wang is used to simulate the boundary layer flow in Hurricane Georges. The simulated wind profiles are in good agreement with the observations, and the asymmetries are well captured. In addition, it is found that the modeled flow in the upper boundary layer at the eyewall is barely supergradient, in contrast to previously studied cases. It is argued that this lack of supergradient flow is a consequence of the particular radial structure in Georges, which had a comparatively slow decrease of wind speed with radius outside the eyewall. This radial profile leads to a relatively weak gradient of inertial stability near the eyewall and a strong gradient at larger radii, and hence the tropical cyclone boundary layer dynamics described by Kepert and Wang can produce only marginally supergradient flow near the radius of maximum winds. The lack of supergradient flow, diagnosed from the observational analysis, is thus attributed to the large-scale structure of this particular storm. A companion paper presents a similar analysis for Hurricane Mitch (1998), with contrasting results.

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