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Edward N. Rappaport
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John J. Cassano
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Andreas Schiller
,
Mike Herzfeld
,
Richard Brinkman
, and
Greg Stuart
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Toshihisa Matsui
,
Takamichi Iguchi
,
Xiaowen Li
,
Mei Han
,
Wei-Kuo Tao
,
Walter Petersen
,
Tristan L'Ecuyer
,
Robert Meneghini
,
William Olson
,
Christian D. Kummerow
,
Arthur Y. Hou
,
Mathew R. Schwaller
,
Erich F. Stocker
, and
John Kwiatkowski
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Jonathan J. Rutz
and
Chris V. Gibson

Today's winter weather headlines are based on the meteorological strength of an event with the assumption that stronger events produce larger public impacts. In reality, public impacts involve many factors, such as whether or not snow will accumulate on roads and affect traffic. Along with numerous environmental factors, decisions are further complicated by societal factors (e.g., timing of the commute).

The National Weather Service (NWS) Strategic Plan calls for increased emphasis on decision support services (DSS) to our partners, especially during high-impact events. However, determining when events will produce high-impact conditions often remains a challenge. While forecasters should be aware of the relevant societal factors, they also need objective tools capable of integrating over the wide range of environmental factors that intersect in producing high-impact weather. This is particularly true in the case of road surface conditions, where complex interactions between temperature, moisture, and the road surface play a key role in determining what hazards might develop during wintry weather.

Initial verification suggests that output from the Model of the Environment and Temperature of Roads (METRo) can provide useful information with regard to the timing and severity of hazardous road surface conditions, allowing NWS forecasters to more effectively highlight the impacts associated with impending meteorological events. This information enhances the DSS that the NWS is able to provide to government partners, local emergency management, and the public during high-impact winter weather events.

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C. David Whiteman
and
Rolando Garibotti

Rime mushrooms, commonly called ice mushrooms, are large bulbous or mushroom-shaped accretions of hard rime that build up on the upwind side of mountain summits and ridges and on windward rock faces. This paper reviews the characteristics of rime mushrooms; the topographical, geographical, and meteorological conditions under which they form; and the significant challenge they pose to climbers. Photographs and descriptions from Southern Patagonia, where rime mushrooms are well known, illustrate the phenomenon.

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Linnea M. Avallone
,
A. Gannet Hallar
,
Heather Thiry
, and
Laura M. Edwards
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M.G. Donat
,
L.V. Alexander
,
H. Yang
,
I. Durre
,
R. Vose
, and
J. Caesar
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Jonathan J. Gourley
,
Yang Hong
,
Zachary L. Flamig
,
Ami Arthur
,
Robert Clark
,
Martin Calianno
,
Isabelle Ruin
,
Terry Ortel
,
Michael E. Wieczorek
,
Pierre-Emmanuel Kirstetter
,
Edward Clark
, and
Witold F. Krajewski

Despite flash flooding being one of the most deadly and costly weather-related natural hazards worldwide, individual datasets to characterize them in the United States are hampered by limited documentation and can be difficult to access. This study is the first of its kind to assemble, reprocess, describe, and disseminate a georeferenced U.S. database providing a long-term, detailed characterization of flash flooding in terms of spatiotemporal behavior and specificity of impacts. The database is composed of three primary sources: 1) the entire archive of automated discharge observations from the U.S. Geological Survey that has been reprocessed to describe individual flooding events, 2) flash-flooding reports collected by the National Weather Service from 2006 to the present, and 3) witness reports obtained directly from the public in the Severe Hazards Analysis and Verification Experiment during the summers 2008–10. Each observational data source has limitations; a major asset of the unified flash flood database is its collation of relevant information from a variety of sources that is now readily available to the community in common formats. It is anticipated that this database will be used for many diverse purposes, such as evaluating tools to predict flash flooding, characterizing seasonal and regional trends, and improving understanding of dominant flood-producing processes. We envision the initiation of this community database effort will attract and encompass future datasets.

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