Search Results

You are looking at 1 - 1 of 1 items for

  • Author or Editor: Maximilian Striegl x
  • All content x
Clear All Modify Search
Christopher C. Hennon, Kenneth R. Knapp, Carl J. Schreck III, Scott E. Stevens, James P. Kossin, Peter W. Thorne, Paula A. Hennon, Michael C. Kruk, Jared Rennie, Jean-Maurice Gadéa, Maximilian Striegl, and Ian Carley

Abstract

The global tropical cyclone (TC) intensity record, even in modern times, is uncertain because the vast majority of storms are only observed remotely. Forecasters determine the maximum wind speed using a patchwork of sporadic observations and remotely sensed data. A popular tool that aids forecasters is the Dvorak technique—a procedural system that estimates the maximum wind based on cloud features in IR and/or visible satellite imagery. Inherently, the application of the Dvorak procedure is open to subjectivity. Heterogeneities are also introduced into the historical record with the evolution of operational procedures, personnel, and observing platforms. These uncertainties impede our ability to identify the relationship between tropical cyclone intensities and, for example, recent climate change.

A global reanalysis of TC intensity using experts is difficult because of the large number of storms. We will show that it is possible to effectively reanalyze the global record using crowdsourcing. Through modifying the Dvorak technique into a series of simple questions that amateurs (“citizen scientists”) can answer on a website, we are working toward developing a new TC dataset that resolves intensity discrepancies in several recent TCs. Preliminary results suggest that the performance of human classifiers in some cases exceeds that of an automated Dvorak technique applied to the same data for times when the storm is transitioning into a hurricane.

Full access