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Kyle Davis
,
Xubin Zeng
, and
Elizabeth A. Ritchie

Abstract

Statistical, dynamical, and statistical–dynamical hybrid models have been developed in past decades for the seasonal prediction of North Atlantic hurricane numbers. These models’ prediction skills show considerable decadal variability, with particularly poor performance in the past few years. Here, environmental factors that affect hurricane activities are reevaluated to develop a new statistical model for seasonal prediction by 1 June of each year. The predictors include the April–May multivariate ENSO index (MEI) conditioned upon the Atlantic multidecadal oscillation (AMO) index, the power of the average zonal pseudo–wind stress across the North Atlantic in May, and the average March–May tropical Atlantic sea surface temperature. When compared to the actual number of hurricanes each year from 1950 to 2013, this model has a root-mean-square error (RMSE) of 1.91 with a correlation coefficient of 0.71. It shows a 39% improvement in RMSE over a no-skill metric (based on the 5-yr running mean of seasonal hurricane counts) for the period 2001–13. It also outperforms three statistical–dynamical hybrid models [CPC, Colorado State University (CSU), and Tropical Storm Risk (TSR)] by more than 25% for the same period. Furthermore, two approaches are developed to provide the uncertainty ranges around the predicted (deterministic) hurricane number per season that better encompass the range of uncertainty than does the standard method of adding/subtracting a standard deviation of the errors.

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Liang Hu
,
Elizabeth A. Ritchie
, and
J. Scott Tyo

Abstract

The deviation angle variance (DAV) is a parameter that characterizes the level of organization of a cloud cluster compared with a perfectly axisymmetric tropical cyclone (TC) using satellite infrared (IR) imagery, and can be used to estimate the intensity of the TC. In this study, the DAV technique is further used to analyze the relationship between satellite imagery and TC future intensity over the North Atlantic basin. The results show that the DAV of the TC changes ahead of the TC intensity change, and this can be used to predict short-term TC intensity. The DAV-IR 24-h forecast is close to the National Hurricane Center (NHC) 24-h forecast, and the bias is lower than NHC and other methods during weakening periods. Furthermore, an improved TC intensity forecast is obtained by incorporating all four satellite bands. Using SST and TC latitude as the other two predictors in a linear regression model, the RMSE and MAE of the DAV 24-h forecast are 13.7 and 10.9 kt (1 kt ≈ 0.51 m s−1), respectively, and the skill space of the DAV is about 5.5% relative to the Statistical Hurricane Intensity Forecast model with inland decay (Decay-SHIFOR) during TC weakening periods. Considering the DAV is an independent intensity technique, it could potentially add value as a member of the suite of operational intensity forecast techniques, especially during TC weakening periods.

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Klaus Dolling
,
Elizabeth A. Ritchie
, and
J. Scott Tyo

Abstract

This study extends past research based on the deviation angle variance (DAV) technique that utilizes digital brightness temperatures from longwave infrared satellite images to objectively measure the symmetry of a tropical cyclone (TC). In previous work, the single-pixel DAV values were used as an objective estimator of storm intensity while maps of the DAV values indicated areas where tropical cyclogenesis was occurring. In this study the spatial information in the DAV maps is utilized along with information from the Cooperative Institute for Research in the Atmosphere’s extended best-track archive and the Statistical Hurricane Intensity Prediction Scheme model to create multiple linear regression models of wind radii parameters for TCs in the North Atlantic basin. These models are used to estimate both symmetric, and by quadrant, 34-, 50-, and 64-kt wind radii (where 1 kt = 0.51 m s−1 1) on a half-hourly time scale. The symmetric model assumes azimuthal symmetry and has mean absolute errors of 38.5, 23.2, and 13.5 km (20.8, 12.5, and 7.3 n mi) for the 34-, 50-, and 64-kt wind radii, respectively, which are lower than results for most other techniques except for those based on AMSU. The asymmetric model independently estimates radii in each quadrant and produces mean absolute errors for the wind radii that are generally highest in the northwest quadrant and lowest in the southwest quadrant similar to other techniques. However, as a percentage of the average wind radii from aircraft reconnaissance, all quadrants have similar errors.

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Miguel F. Piñeros
,
Elizabeth A. Ritchie
, and
J. Scott Tyo

Abstract

This paper describes results from a near-real-time objective technique for estimating the intensity of tropical cyclones from satellite infrared imagery in the North Atlantic Ocean basin. The technique quantifies the level of organization or axisymmetry of the infrared cloud signature of a tropical cyclone as an indirect measurement of its maximum wind speed. The final maximum wind speed calculated by the technique is an independent estimate of tropical cyclone intensity. Seventy-eight tropical cyclones from the 2004–09 seasons are used both to train and to test independently the intensity estimation technique. Two independent tests are performed to test the ability of the technique to estimate tropical cyclone intensity accurately. The best results from these tests have a root-mean-square intensity error of between 13 and 15 kt (where 1 kt ≈ 0.5 m s−1) for the two test sets.

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Liang Hu
,
Elizabeth A. Ritchie
, and
J. Scott Tyo

Abstract

The deviation angle variance (DAV) is a parameter that characterizes the level of organization of a cloud cluster compared with a perfectly axisymmetric tropical cyclone (TC) using satellite infrared (IR) imagery, and can be used to estimate the intensity of the TC. In this study, the DAV technique is further used to analyze the relationship between satellite imagery and TC future intensity over the North Atlantic basin. The results show that the DAV of the TC changes ahead of the TC intensity change, and this can be used to predict short-term TC intensity. The DAV-IR 24-h forecast is close to the National Hurricane Center (NHC) 24-h forecast, and the bias is lower than NHC and other methods during weakening periods. Furthermore, an improved TC intensity forecast is obtained by incorporating all four satellite bands. Using SST and TC latitude as the other two predictors in a linear regression model, the RMSE and MAE of the DAV 24-h forecast are 13.7 and 10.9 kt (1 kt ≈ 0.51 m s−1), respectively, and the skill space of the DAV is about 5.5% relative to the Statistical Hurricane Intensity Forecast model with inland decay (Decay-SHIFOR) during TC weakening periods. Considering the DAV is an independent intensity technique, it could potentially add value as a member of the suite of operational intensity forecast techniques, especially during TC weakening periods.

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Elizabeth A. Ritchie
,
Genevieve Valliere-Kelley
,
Miguel F. Piñeros
, and
J. Scott Tyo

Abstract

This paper describes results from an improvement to the objective deviation angle variance technique to estimate the intensity of tropical cyclones from satellite infrared imagery in the North Atlantic basin. The technique quantifies the level of organization of the infrared cloud signature of a tropical cyclone as an indirect measurement of its maximum wind speed. The major change described here is to use the National Hurricane Center’s best-track database to constrain the technique. Results are shown for the 2004–10 North Atlantic hurricane seasons and include an overall root-mean-square intensity error of 12.9 kt (6.6 m s−1, where 1 kt = 0.514 m s−1) and annual root-mean-square intensity errors ranging from 10.3 to 14.1 kt. A direct comparison between the previous version and the one reported here shows root-mean-square intensity error improvements in all years with a best improvement in 2009 from 17.9 to 10.6 kt and an overall improvement from 14.8 to 12.9 kt. In addition, samples from the 7-yr period are binned based on level of intensity and on the strength of environmental vertical wind shear as extracted from Statistical Hurricane Intensity Prediction Scheme (SHIPS) data. Preliminary results suggest that the deviation angle variance technique performs best at the weakest intensity categories of tropical storm through hurricane category 3, representing 90% of the samples, and then degrades in performance for hurricane categories 4 and 5. For environmental vertical wind shear, there is far less spread in the results with the technique performing better with increasing vertical wind shear.

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Greg J. Holland
,
Lance M. Leslie
,
Elizabeth A. Ritchie
,
Gary S. Dietachmayer
,
Peter E. Powers
, and
Mark Klink

Abstract

The design concept and operational trial of a fully interactive analysis and numerical forecast system for tropical-cyclone motion are described. The design concept emphasizes an interactive system in which forecasters can test various scenarios objectively, rather than having to subjectively decide between conflicting forecasts from standardized techniques. The system is designed for use on a personal computer, or workstation, located on the forecast bench. A choice of a Barnes or statistical interpolation scheme is provided to analyze raw or bogus observations at any atmospheric level or layer mean selected by the forecaster. The track forecast is then made by integration of a nondivergent barotropic model.

An operational trial during the 1990 tropical-cyclone field experiments in the western north Pacific Ocean indicated that the system can be used very effectively in real time. A series of case-study examples is presented.

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Kimberly M. Wood
,
Oscar G. Rodríguez-Herrera
,
Elizabeth A. Ritchie
,
Miguel F. Piñeros
,
Ivan Arias Hernández
, and
J. Scott Tyo

Abstract

The deviation angle variance technique (DAV-T) for genesis detection is applied in the western and eastern North Pacific basins. The DAV-T quantifies the axisymmetric organization of cloud clusters using infrared brightness temperature. Since axisymmetry is typically correlated with intensity, the technique can be used to identify relatively high levels of organization at early stages of storm life cycles associated with tropical cyclogenesis. In addition, the technique can be used to automatically track cloud clusters that exhibit signs of organization. In the western North Pacific, automated tracking results for the 2009–11 typhoon seasons show that for a false alarm rate of 25.6%, 96.8% of developing tropical cyclones are detected with a median time of 18.5 h before the cluster reaches an intensity of 30 knots (kt; 1 kt = 0.51 m s−1) in the Joint Typhoon Warning Center best track at a DAV threshold of 1750°2. In the eastern North Pacific, for a false alarm rate of 38.0%, the system detects 92.9% of developing tropical cyclones with a median time of 1.25 h before the cluster reaches an intensity of 30 kt in the National Hurricane Center best track during the 2009–11 hurricane seasons at a DAV threshold of 1650°2. A significant decrease in tracked nondeveloping clusters occurs when a second organization threshold is introduced, particularly in the western North Pacific.

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Elizabeth A. Ritchie
,
Kimberly M. Wood
,
Oscar G. Rodríguez-Herrera
,
Miguel F. Piñeros
, and
J. Scott Tyo

Abstract

The deviation-angle variance technique (DAV-T), which was introduced in the North Atlantic basin for tropical cyclone (TC) intensity estimation, is adapted for use in the North Pacific Ocean using the “best-track center” application of the DAV. The adaptations include changes in preprocessing for different data sources [Geostationary Operational Environmental Satellite-East (GOES-E) in the Atlantic, stitched GOES-E–Geostationary Operational Environmental Satellite-West (GOES-W) in the eastern North Pacific, and the Multifunctional Transport Satellite (MTSAT) in the western North Pacific], and retraining the algorithm parameters for different basins. Over the 2007–11 period, DAV-T intensity estimation in the western North Pacific results in a root-mean-square intensity error (RMSE, as measured by the maximum sustained surface winds) of 14.3 kt (1 kt ≈ 0.51 m s−1) when compared to the Joint Typhoon Warning Center best track, utilizing all TCs to train and test the algorithm. The RMSE obtained when testing on an individual year and training with the remaining set lies between 12.9 and 15.1 kt. In the eastern North Pacific the DAV-T produces an RMSE of 13.4 kt utilizing all TCs in 2005–11 when compared with the National Hurricane Center best track. The RMSE for individual years lies between 9.4 and 16.9 kt. The complex environment in the western North Pacific led to an extension to the DAV-T that includes two different radii of computation, producing a parametric surface that relates TC axisymmetry to intensity. The overall RMSE is reduced by an average of 1.3 kt in the western North Pacific and 0.8 kt in the eastern North Pacific. These results for the North Pacific are comparable with previously reported results using the DAV for the North Atlantic basin.

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