scholarly journals Performance Evaluation of Numerical Tools for Hurricane Forecast (NTHF) System during 2020 North Atlantic Tropical Cyclones Season

2021 ◽  
Vol 8 (1) ◽  
pp. 22
Author(s):  
Albenis Pérez-Alarcón ◽  
José C. Fernández-Alvarez ◽  
Alfo J. Batista-Leyva
Keyword(s):  
Tropical Cyclones ◽  
North Atlantic ◽  
Track Forecast ◽  
Forecast Errors ◽  
Prediction Scheme ◽  
Numerical Tools ◽  
Marginal Improvement ◽  
National Hurricane Center ◽  
Basic Input ◽  
Better Than

This study evaluates the performance of the Numerical Tools for Hurricane Forecast (NTHF) system during the 2020 North Atlantic (NATL) tropical cyclones (TCs) season. The system is configured to provide 5-day forecasts with basic input from the National Hurricane Center (NHC) and the Global Forecast System. For the NTHF validation, the NHC operational best track was used. The average track errors for 2020 NATL TCs ranged from 62 km at 12 h to 368 km at 120 h. The NTHF track forecast errors displayed an improvement over 60% above the guidance Climatology and Persistence (CLIPER) model from 36 h to 96 h, although the NTHF was better than the CLIPER in all forecast periods. The forecast errors for the maximum wind speed (minimum central pressure) ranged between 20 km/h and 25 km/h (4 hPa to 8 hPa), but the NTHF model intensity forecasts showed only marginal improvement of less than 20% after 78 h over the baseline Decay Statistical Hurricane Intensity Prediction Scheme (D-SHIPS) model. Nevertheless, the NTHF’s ability to provide accurate intensity forecasts for the 2020 NATL TCs was higher than the NTHF’s average ability during the 2016–2019 period.

Atlantic Hurricane Season of 2006

2008 ◽  
Vol 136 (3) ◽  
pp. 1174-1200 ◽  
Author(s):  
James L. Franklin ◽  
Daniel P. Brown
Keyword(s):  
Tropical Cyclones ◽  
The United States ◽  
Tropical Storm ◽  
Track Forecast ◽  
Forecast Errors ◽  
Atlantic Hurricane ◽  
Hurricane Season ◽  
First Time ◽  
National Hurricane Center

Abstract The 2006 Atlantic hurricane season is summarized and the year’s tropical cyclones are described. A verification of National Hurricane Center official forecasts during 2006 is also presented. Ten cyclones attained tropical storm intensity in 2006. Of these, five became hurricanes and two became “major” hurricanes. Overall activity was near the long-term mean, but below the active levels of recent seasons. For the first time since 2001, no hurricanes made landfall in the United States. Elsewhere in the basin, hurricane-force winds were experienced in Bermuda (from Florence) and in the Azores (from Gordon). Official track forecast errors were smaller in 2006 than during the previous 5-yr period (by roughly 15%–20% out to 72 h), establishing new all-time lows at forecast projections through 72 h. Since 1990, 24–72-h official track forecast errors have been reduced by roughly 50%.

scholarly journals Reducing Operational Hurricane Intensity Forecast Errors during Eyewall Replacement Cycles

2016 ◽  
Vol 31 (2) ◽  
pp. 601-608 ◽  
Author(s):  
James P. Kossin ◽  
Mark DeMaria
Keyword(s):  
Forecast Error ◽  
Intensity Change ◽  
Forecast Errors ◽  
Hurricane Intensity ◽  
Intensity Forecast ◽  
Prediction Scheme ◽  
Hurricane Prediction ◽  
Eyewall Replacement Cycles ◽  
National Hurricane Center ◽  
Intensity Evolution

Abstract Eyewall replacement cycles (ERCs) are fairly common events in tropical cyclones (TCs) of hurricane intensity or greater and typically cause large and sometimes rapid changes in the intensity evolution of the TC. Although the details of the intensity evolution associated with ERCs appear to have some dependence on the ambient environmental conditions that the TCs move through, these dependencies can also be quite different than those of TCs that are not undergoing an ERC. For example, the Statistical Hurricane Prediction Scheme (SHIPS), which is used in National Hurricane Center operations and provides intensity forecast skill that is, on average, equal to or greater than deterministic numerical model skill, typically identifies an environment that is not indicative of weakening during the onset and subsequent evolution of an ERC. Contrarily, a period of substantial weakening does typically begin near the onset of an ERC, and this disparity can cause large SHIPS intensity forecast errors. Here, a simple model based on a climatology of ERC intensity change is introduced and tested against SHIPS. It is found that the application of the model can reduce intensity forecast error substantially when applied at, or shortly after, the onset of ERC weakening.

scholarly journals Weighted Analog Technique for Intensity and Intensity Spread Predictions of Atlantic Tropical Cyclones

2015 ◽  
Vol 30 (5) ◽  
pp. 1321-1333 ◽  
Author(s):  
Hsiao-Chung Tsai ◽  
Russell L. Elsberry
Keyword(s):  
Tropical Cyclones ◽  
Bias Correction ◽  
Western North Pacific ◽  
Probability Of Detection ◽  
Track Forecast ◽  
Sample Mean ◽  
Prediction Technique ◽  
Intensity Spread ◽  
National Hurricane Center ◽  
Joint Typhoon Warning Center

Abstract A situation-dependent intensity and intensity spread prediction technique for the Atlantic called the Weighted Analog Intensity Atlantic (WAIA) is developed using the same procedures as for a similar technique for the western North Pacific that is operational at the Joint Typhoon Warning Center. These simple techniques are based on rankings of the 10 best historical track analogs to match the official track forecast and current intensity. A key step is the development of a bias correction to eliminate an overforecast bias. The second key step is a calibration of the original intensity spread among the 10 analogs to achieve a probability of detection of about 68% at all forecast intervals, which it is proposed would be an appropriate intensity spread for the National Hurricane Center (NHC) official intensity forecasts. The advantages of WAIA as an operational intensity forecast product for Atlantic tropical cyclones are described in terms of mean absolute errors, sample-mean biases, and geographic distributions of WAIA versus various guidance products available at NHC. Specific attention is given to the four guidance products that are included in the intensity consensus (ICON) technique that is the most skillful of all the products. Evidence is given that WAIA would be an independent, and more likely skillful at longer forecast intervals, technique to include in ICON. Consequently, WAIA would likely lead to improved NHC intensity forecasts at 4–5-day intervals.

Impact of Refractivity Profiles from a Proposed GNSS-RO Constellation on Tropical Cyclone Forecasts in a Global Modeling System

2020 ◽  
Vol 148 (7) ◽  
pp. 3037-3057
Author(s):  
Michael J. Mueller ◽  
Andrew C. Kren ◽  
Lidia Cucurull ◽  
Sean P. F. Casey ◽  
Ross N. Hoffman ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
North Atlantic ◽  
Forecast Error ◽  
Good Control ◽  
Track Forecast ◽  
Forecast Errors ◽  
Random Errors ◽  
Error Statistics ◽  
The North ◽  
The North Atlantic

Abstract A global observing system simulation experiment (OSSE) was used to assess the potential impact of a proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellation on tropical cyclone (TC) track, maximum 10-m wind speed (Vmax), and integrated kinetic energy (IKE) forecasts. The OSSE system was based on the 7-km NASA nature run and simulated RO refractivity determined by the spatial distribution of observations from the original planned (i.e., including both equatorial and polar orbits) Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2). Data were assimilated using the NOAA operational weather analysis and forecasting system. Three experiments generated global TC track, Vmax, and IKE forecasts over 6 weeks of the North Atlantic hurricane season in the North Atlantic, east Pacific, and west Pacific basins. Confidence in our results was bolstered because track forecast errors were similar to those of official National Hurricane Center forecasts, and Vmax errors and IKE errors showed similar results. GNSS-RO assimilation did not significantly impact global track forecasts, but did slightly degrade Vmax and IKE forecasts in the first 30–60 h of lead time. Global forecast error statistics show adding or excluding explicit random errors to RO profiles made little difference to forecasts. There was large forecast-to-forecast variability in RO impact. For two cases studied in depth, track and Vmax improvements and degradations were traced backward through the previous 24 h of assimilation cycles. The largest Vmax degradation was traced to particularly good control analyses rather than poor analyses caused by GNSS-RO.

After a Decade Are Atlantic Tropical Cyclone Gale Force Wind Radii Forecasts Now Skillful?

2015 ◽  
Vol 30 (3) ◽  
pp. 702-709 ◽  
Author(s):  
John A. Knaff ◽  
Charles R. Sampson
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
North Atlantic ◽  
The Public ◽  
The North ◽  
Radial Extent ◽  
History Of ◽  
The North Atlantic ◽  
National Hurricane Center ◽  
Atlantic Tropical Cyclone

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.

scholarly journals The Sanders Barotropic Tropical Cyclone Track Prediction Model (SANBAR)

2008 ◽  
Vol 55 ◽  
pp. 233-240 ◽  
Author(s):  
Robert W. Burpee
Keyword(s):  
Tropical Cyclone ◽  
Prediction Model ◽  
Large Scale ◽  
Track Forecast ◽  
Forecast Errors ◽  
The North ◽  
Regional Area ◽  
Wind Input ◽  
Large Scale Flow ◽  
National Hurricane Center

Abstract Sanders designed a barotropic tropical cyclone (TC) track prediction model for the North Atlantic TC basin that became known as the Sanders barotropic (SANBAR) model. It predicted the streamfunction of the deeplayer mean winds (tropical circulation vertically averaged from 1000 to 100 hPa) that represents the vertically averaged tropical circulations. Originally, the wind input for the operational objective analysis (OA) consisted of winds measured by radiosondes and 44 bogus winds provided by analysis at the National Hurricane Center (NHC), which corresponded to the vertically averaged flow over sparsely observed tropical, subtropical, and midlatitude oceanic regions. The model covered a fixed regional area and had a grid size of ~ 154 km. It estimated the initial storm motion solely on the basis of the large-scale flow from the OA, not taking into account the observed storm motion. During 1970, the SANBAR model became the first dynamical TC track model to be run operationally at NHC. Track forecasts of SANBAR were verified from the 1971 TC season when track model verifications began at NHC until its retirement after the 1989 Atlantic TC season. The average annual SANBAR forecast track errors were verified relative to Climatology and Persistence (CLIPER), the standard no-skill track forecast. Comparison with CLIPER determines the skill of track forecast methods. Verifications are presented for two different versions of the SANBAR model system used operationally during 1973–84 and 1985–89. In homogeneous comparisons (i.e., includes only forecasts for the same initial times) for the former period, SANBAR's track forecasts were slightly better than CLIPER at 24–48-h forecast intervals; however, from 1985 to 1989 the average SANBAR track forecast errors from 24–72 h were ~10% more skillful than homogeneous CLIPER track forecasts.

Contrasting Behaviors between the Rapidly Intensifying and Slowly Intensifying Tropical Cyclones in the North Atlantic and Eastern Pacific Basins

2021 ◽  
Vol 34 (3) ◽  
pp. 987-1003
Author(s):  
Xinxi Wang ◽  
Haiyan Jiang
Keyword(s):  
Tropical Cyclones ◽  
North Atlantic ◽  
Heat Content ◽  
Vertical Wind Shear ◽  
Environmental Parameters ◽  
Relative Vorticity ◽  
The North ◽  
Prediction Scheme ◽  
Westerly Flow ◽  
First Time

AbstractBased on 35-yr (1982–2016) best track and Statistical Hurricane Intensity Prediction Scheme data, this study examined climatology of rapidly intensifying (RI) and slowly intensifying (SI) events as well as their time evolutions of storm-related and environmental parameters for tropical cyclones (TCs) in both North Atlantic (AL) and eastern North Pacific (EP) basins. Major hurricanes were intensified mainly through RI while tropical depression and tropical storms were intensified through SI. The percentage of TCs that underwent RI peaks in the late hurricane season whereas the percentage of TCs that underwent SI peaks early. For the first time in the literature, this study found that RI events have significantly different storm-related and environmental characteristics than SI events for before-, during-, and after-event stages. In both AL and EP basins, RI events always intensify significantly faster during the previous 12 h, are located farther south, and have warmer sea surface and 200-hPa temperatures, greater ocean heat content, larger 200-hPa divergence, weaker vertical wind shear, and weaker 200-hPa westerly flow than SI events for all event-relative stages. In the AL basin, RI events have larger low-level and midlevel relative humidity and larger 850-hPa relative vorticity than SI events for all event-relative stages in the AL and most event-relative stages in the EP. RI events are associated with more convectively unstable atmosphere and are farther away from their maximum potential intensities than SI events for most event-relative stages in the AL and for all event-relative stages in the EP.

Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model

2013 ◽  
Vol 52 (11) ◽  
pp. 2476-2492 ◽  
Author(s):  
Krishna K. Osuri ◽  
U. C. Mohanty ◽  
A. Routray ◽  
M. Mohapatra ◽  
Dev Niyogi
Keyword(s):  
High Resolution ◽  
Indian Ocean ◽  
Real Time ◽  
Tropical Cyclones ◽  
North Indian Ocean ◽  
Track Forecast ◽  
Forecast Errors ◽  
The North ◽  
Arw Model ◽  
The Impact

AbstractThe performance of the Advanced Research version of the Weather Research and Forecasting (ARW) model in real-time prediction of tropical cyclones (TCs) over the north Indian Ocean (NIO) at 27-km resolution is evaluated on the basis of 100 forecasts for 17 TCs during 2007–11. The analyses are carried out with respect to 1) basins of formation, 2) straight-moving and recurving TCs, 3) TC intensity at model initialization, and 4) season of occurrence. The impact of high resolution (18 and 9 km) on TC prediction is also studied. Model results at 27-km resolution indicate that the mean track forecast errors (skill with reference to persistence track) over the NIO were found to vary from 113 to 375 km (7%–51%) for a 12–72-h forecast. The model showed a right/eastward and slow bias in TC movement. The model is more skillful in track prediction when initialized at the intensity stage of severe cyclone or greater than at the intensity stage of cyclone or lower. The model is more efficient in predicting landfall location than landfall time. The higher-resolution (18 and 9 km) predictions yield an improvement in mean track error for the NIO Basin by about 4%–10% and 8%–24%, respectively. The 9-km predictions were found to be more accurate for recurving TC track predictions by ~13%–28% and 5%–15% when compared with the 27- and 18-km runs, respectively. The 9-km runs improve the intensity prediction by 15%–40% over the 18-km predictions. This study highlights the capabilities of the operational ARW model over the Indian monsoon region and the continued need for operational forecasts from high-resolution models.

scholarly journals Is Tropical Cyclone Intensity Guidance Improving?

2014 ◽  
Vol 95 (3) ◽  
pp. 387-398 ◽  
Author(s):  
Mark DeMaria ◽  
Charles R. Sampson ◽  
John A. Knaff ◽  
Kate D. Musgrave
Keyword(s):  
Tropical Cyclone ◽  
North Pacific ◽  
Absolute Error ◽  
Track Forecast ◽  
Forecast Errors ◽  
Cyclone Intensity ◽  
The Past ◽  
Forecast Models ◽  
Combine Information ◽  
National Hurricane Center

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.

scholarly journals A Statistical Model to Predict the Extratropical Transition of Tropical Cyclones

2020 ◽  
Vol 35 (2) ◽  
pp. 451-466
Author(s):  
Melanie Bieli ◽  
Adam H. Sobel ◽  
Suzana J. Camargo ◽  
Michael K. Tippett
Keyword(s):  
Tropical Cyclones ◽  
North Atlantic ◽  
North Pacific ◽  
Lead Time ◽  
Western North Pacific ◽  
Extratropical Transition ◽  
The North ◽  
Operational Forecasts ◽  
The North Atlantic ◽  
Better Than

Abstract This paper introduces a logistic regression model for the extratropical transition (ET) of tropical cyclones in the North Atlantic and the western North Pacific, using elastic net regularization to select predictors and estimate coefficients. Predictors are chosen from the 1979–2017 best track and reanalysis datasets, and verification is done against the tropical/extratropical labels in the best track data. In an independent test set, the model skillfully predicts ET at lead times up to 2 days, with latitude and sea surface temperature as its most important predictors. At a lead time of 24 h, it predicts ET with a Matthews correlation coefficient of 0.4 in the North Atlantic, and 0.6 in the western North Pacific. It identifies 80% of storms undergoing ET in the North Atlantic and 92% of those in the western North Pacific. In total, 90% of transition time errors are less than 24 h. Select examples of the model’s performance on individual storms illustrate its strengths and weaknesses. Two versions of the model are presented: an “operational model” that may provide baseline guidance for operational forecasts and a “hazard model” that can be integrated into statistical TC risk models. As instantaneous diagnostics for tropical/extratropical status, both models’ zero lead time predictions perform about as well as the widely used cyclone phase space (CPS) in the western North Pacific and better than the CPS in the North Atlantic, and predict the timings of the transitions better than CPS in both basins.

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