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  • Author or Editor: Timothy Olander x
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Timothy L. Olander
and
Christopher S. Velden

Abstract

Tropical cyclones are becoming an increasing menace to society as populations grow in coastal regions. Forecasting the intensity of these often-temperamental weather systems can be a real challenge, especially if the true intensity at the forecast time is not well known. To address this issue, techniques to accurately estimate tropical cyclone intensity from satellites are a natural goal because in situ observations over the vast oceanic basins are scarce. The most widely utilized satellite-based method to estimate tropical cyclone intensity is the Dvorak technique, a partially subjective scheme that has been employed operationally at tropical forecast centers around the world for over 30 yr. With the recent advent of improved satellite sensors, the rapid advances in computing capacity, and accumulated experience with the behavioral characteristics of the Dvorak technique, the development of a fully automated, computer-based objective scheme to derive tropical cyclone intensity has become possible.

In this paper the advanced Dvorak technique is introduced, which, as its name implies, is a derivative of the original Dvorak technique. The advanced Dvorak technique builds on the basic conceptual model and empirically derived rules of the original Dvorak technique, but advances the science and applicability in an automated environment that does not require human intervention. The algorithm is the culmination of a body of research that includes the objective Dvorak technique (ODT) and advanced objective Dvorak technique (AODT) developed at the University of Wisconsin—Madison’s Cooperative Institute for Meteorological Satellite Studies. The ODT could only be applied to storms that possessed a minimum intensity of hurricane/typhoon strength. In addition, the ODT still required a storm center location to be manually selected by an analyst prior to algorithm execution. These issues were the primary motivations for the continued advancement of the algorithm (AODT). While these two objective schemes had as their primary goal to simply achieve the basic functionality and performance of the Dvorak technique in a computer-driven environment, the advanced Dvorak technique exceeds the boundaries of the original Dvorak technique through modifications based on rigorous statistical and empirical analysis. It is shown that the accuracy of the advanced Dvorak technique is statistically competitive with the original Dvorak technique, and can provide objective tropical cyclone intensity guidance for systems in all global basins.

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Timothy L. Olander
and
Christopher S. Velden

Abstract

The advanced Dvorak technique (ADT) is used operationally by tropical cyclone forecast centers worldwide to help estimate the intensity of tropical cyclones (TCs) from operational geostationary meteorological satellites. New enhancements to the objective ADT have been implemented by the algorithm development team to further expand its capabilities and precision. The advancements include the following: 1) finer tuning to aircraft-based TC intensity estimates in an expanded development sample, 2) the incorporation of satellite-based microwave information into the intensity estimation scheme, 3) more sophisticated automated TC center-fixing routines, 4) adjustments to the intensity estimates for subtropical systems and TCs undergoing extratropical transition, and 5) addition of a surface wind radii estimation routine. The goals of these upgrades and others are to provide TC analysts/forecasters with an expanded objective guidance tool to more accurately estimate the intensity of TCs and those storms forming from, or converting into, hybrid/nontropical systems. The 2018 TC season is used to illustrate the performance characteristics of the upgraded ADT.

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Timothy L. Olander
and
Christopher S. Velden

Abstract

A technique to identify and quantify intense convection in tropical cyclones (TCs) using bispectral, geostationary satellite imagery is explored. This technique involves differencing the water vapor (WV) and infrared window (IRW) channel brightness temperature values, which are available on all current operational geostationary weather satellites. Both the derived IRW minus WV (IRWV) imagery and the raw data values can be used in a variety of methods to provide TC forecasters with important information about current and future intensity trends, a component within the operational TC forecasting arena that has shown little improvement during the past few decades.

In this paper several possible uses for this bispectral technique, both qualitative and quantitative, are explored and outlined. Qualitative monitoring of intense convection can be used as a proxy for passive microwave (MW) imager data obtained from polar-orbiting satellite platforms when not available. In addition, the derived imagery may aid in the TC storm center identification process, both manually and objectively, especially in difficult situations where the IRW imagery alone cannot be used such as when the storm circulation center and/or eye features are obscured by a cirrus canopy. Quantitative methods discussed involve the predictive quality of the IRWV data in terms of TC intensity changes, primarily during TC intensification. Strong correlations exist between storm intensity changes and IRWV values at varying 6-h forecast interval periods, peaking between the 12- and 24-h time periods. Implications for the use of the IRWV data on such objective satellite intensity estimate algorithms as the University of Wisconsin—Madison (UW) Cooperative Institute for Meteorological Satellite Studies (CIMSS) advanced Dvorak technique (ADT) are also discussed.

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Christopher S. Velden
,
Timothy L. Olander
, and
Raymond M. Zehr

Abstract

The standard method for estimating the intensity of tropical cyclones is based on satellite observations (Dvorak technique) and is utilized operationally by tropical analysis centers around the world. The technique relies on image pattern recognition along with analyst interpretation of empirically based rules regarding the vigor and organization of convection surrounding the storm center. While this method performs well enough in most cases to be employed operationally, there are situations when analyst judgment can lead to discrepancies between different analysis centers estimating the same storm.

In an attempt to eliminate this subjectivity, a computer-based algorithm that operates objectively on digital infrared information has been developed. An original version of this algorithm (engineered primarily by the third author) has been significantly modified and advanced to include selected “Dvorak rules,” additional constraints, and a time-averaging scheme. This modified version, the Objective Dvorak Technique (ODT), is applicable to tropical cyclones that have attained tropical storm or hurricane strength.

The performance of the ODT is evaluated on cases from the 1995 and 1996 Atlantic hurricane seasons. Reconnaissance aircraft measurements of minimum surface pressure are used to validate the satellite-based estimates. Statistical analysis indicates the technique to be competitive with, and in some cases superior to, the Dvorak-based intensity estimates produced operationally by satellite analysts from tropical analysis centers. Further analysis reveals situations where the algorithm needs improvement, and directions for future research and modifications are suggested.

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Timothy Olander
,
Anthony Wimmers
,
Christopher Velden
, and
James P. Kossin

Abstract

Several simple and computationally inexpensive machine learning models are explored that can use advanced Dvorak technique (ADT)-retrieved features of tropical cyclones (TCs) from satellite imagery to provide improved maximum sustained surface wind speed (MSW) estimates. ADT (version 9.0) TC analysis parameters and operational TC forecast center best track datasets from 2005 to 2016 are used to train and validate the various models over all TC basins globally and select the best among them. Two independent test sets of TC cases from 2017 to 2018 are used to evaluate the intensity estimates produced by the final selected model called the “artificial intelligence (AI)” enhanced advanced Dvorak technique (AiDT). The 2017–18 MSW results demonstrate a global RMSE of 7.7 and 8.2 kt (1 kt ≈ 0.51 m s−1), respectively. Basin-specific MSW RMSEs of 8.4, 6.8, 7.3, 8.0, and 7.5 kt were obtained with the 2017 dataset in the North Atlantic, east/central Pacific, northwest Pacific, South Pacific/south Indian, and north Indian Ocean basins, respectively, with MSW RMSE values of 8.9, 6.7, 7.1, 10.4, and 7.7 obtained with the 2018 dataset. These represent a 30% and 23% improvement over the corresponding ADT RMSE for the 2017–18 datasets, respectively, with the AiDT error reduction significant to 99% in both sets. The AiDT model represents a notable improvement over the ADT performance and also compares favorably to more computationally expensive and complex machine learning models that interrogate satellite images directly while still preserving the operational familiarity of the ADT.

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Alexander Manion
,
Clark Evans
,
Timothy L. Olander
,
Christopher S. Velden
, and
Lewis D. Grasso

Abstract

It is known that both Dvorak technique and advanced Dvorak technique–derived intensity estimates for tropical cyclones during extratropical transition are less reliable because the empirical relationships between cloud patterns and cyclone intensity underlying each technique are primarily tropical in nature and thus less robust during extratropical transition. However, as direct observations of cyclone intensity during extratropical transition are rare, the precise extent to which such remotely sensed intensity estimates are in error is uncertain. To address this uncertainty and provide insight into how advanced Dvorak technique–derived intensity estimates during extratropical transition may be improved, the advanced Dvorak technique is applied to synthetic satellite imagery derived from 25 numerical simulations of Atlantic basin tropical cyclones—five cases, five microphysical parameterizations—during extratropical transition. From this, an internally consistent evaluation between model-derived and advanced Dvorak technique–derived cyclone intensity estimates is conducted. Intensity estimate error and bias peak at the beginning of extratropical transition and decline thereafter for maximum sustained surface wind. On average, synthetic advanced Dvorak technique–derived estimates of maximum sustained surface wind asymptote toward or remain near their weakest-possible values after extratropical transition begins. Minimum sea level pressure estimates exhibit minimal bias, although this result is sensitive to microphysical parameterization. Such sensitivity to microphysical parameterization, particularly with respect to cloud radiative properties, suggests that only qualitative insight regarding advanced Dvorak technique–derived intensity estimate error during extratropical transition may be obtained utilizing synthetic satellite imagery. Implications toward developing improved intensity estimates during extratropical transition are discussed.

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