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Christopher S. Velden
,
Timothy L. Olander
, and
Steve Wanzong

Abstract

Satellite-based remote sensing has long been recognized as an important method to reconnoiter oceanic tropical cyclones due to the scarcity of in situ observations. Beyond the standard qualitative applications offered by imagery, algorithms are being developed to process the information-wealthy imagery into quantitative parameters necessary to positively impact objective analyses on which numerical track predictions are initialized. Techniques developed at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies enable the automated extraction of displacement vectors from animated imagery featuring sequential geostationary satellite multispectral observations of clouds and water vapor. Recent upgrades to these algorithms and a focused processing strategy directed toward optimizing the retrieved wind vector coverage are discussed. In combination with advanced sensing technology afforded by the National Oceanic and Atmospheric Administration’s latest generation of geostationary meteorological satellites, GOES-8, superior vector yield and quality are being realized.

In this set of two papers, datasets produced during the 1995 Atlantic hurricane season are examined for their impact on tropical cyclone analyses and numerical track forecasts. In Part I, the wind retrieval methodology and data characteristics are described, along with a brief discussion of the tropical cyclones selected for study. Part II addresses the input of the GOES-8 wind information into a global data assimilation system, and the resultant impact on numerical track predictions.

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Christopher Velden
,
Timothy Olander
,
Derrick Herndon
, and
James P. Kossin

Abstract

In recent years, a number of extremely powerful tropical cyclones have revived community debate on methodologies used to estimate the lifetime maximum intensity (LMI) of these events. And how do these storms rank historically? In this study, the most updated version of an objective satellite-based intensity estimation algorithm [advanced Dvorak technique (ADT)] is employed and applied to the highest-resolution (spatial and temporal) geostationary satellite data available for extreme-intensity tropical cyclones that occurred during the era of these satellites (1979–present). Cases with reconnaissance aircraft observations are examined and used to calibrate the ADT at extreme intensities. Bias corrections for observing properties such as satellite viewing angle and image spatiotemporal resolution, and storm characteristics such as small eye size are also considered.

The results of these intensity estimates (maximum sustained 1-min wind) show that eastern North Pacific Hurricane Patricia (2015) ranks as the strongest storm in any basin (182 kt), followed by western North Pacific Typhoons Haiyan (2013), Tip (1979), and Gay (1992). The following are the strongest classifications in other basins—Atlantic: Gilbert (1988), north Indian Ocean basin: Paradip (1999), south Indian Ocean: Gafilo (2004), Australian region: Monica (2006), and southeast Pacific basin: Pam (2015). In addition, ADT LMI estimates for four storms exceed the maximum allowable limit imposed by the operational Dvorak technique. This upper bound on intensity may be an unnatural constraint, especially if tropical cyclones get stronger in a warmer biosphere as some theorize. This argues for the need of an extension to the Dvorak scale to allow higher intensity estimates.

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