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Lindsey R. Barnes
,
David M. Schultz
,
Eve C. Gruntfest
,
Mary H. Hayden
, and
Charles C. Benight

Abstract

Two items need to be clarified from an earlier work of the authors. The first is that the layout of the 2 × 2 contingency table was reversed from standard practice, with the titles of “observed event” and “forecast” transposed. The second is that FAR should have represented “false alarm ratio,” not “false alarm rate.” Unfortunately, the terminology used in the atmospheric sciences is confusing, with authors as early as 1965 having used the terminology differently from currently accepted practice. More recent studies are not much better. A survey of peer-reviewed articles published in American Meteorological Society journals between 2001 and 2007 found that, of 26 articles using those terms, 10 (38%) used them inconsistently with the currently accepted definitions. This article recommends that authors make explicit how their verification statistics are calculated in their manuscripts and consider using the terms probability of false detection and probability of false alarm instead of false alarm rate and false alarm ratio.

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Lindsey R. Barnes
,
Eve C. Gruntfest
,
Mary H. Hayden
,
David M. Schultz
, and
Charles Benight

Abstract

The false alarm rate (FAR) measures the fraction of forecasted events that did not occur, and it remains one of the key metrics for verifying National Weather Service (NWS) weather warnings. The national FAR for tornado warnings in 2003 was 0.76, indicating that only one in four tornado warnings was verified. The NWS’s goal for 2010 is to reduce this value to 0.70. Conventional wisdom is that false alarms reduce the public’s willingness to respond to future events. This paper questions this conventional wisdom. In addition, this paper argues that the metrics used to evaluate false alarms do not accurately represent the numbers of actual false alarms or the forecasters’ abilities because current metrics categorize events as either a hit or a miss and do not give forecasters credit for close calls. Aspects discussed in this paper include how the NWS FAR is measured, how humans respond to warnings, and what are alternative approaches to measure FAR. A conceptual model is presented as a framework for a new perspective on false alarms that includes close calls, providing a more balanced view of forecast verification.

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