2009
DOI: 10.1175/2009bams2815.1
|View full text |Cite
|
Sign up to set email alerts
|

Abstract: Active collection of severe weather reports via telephone interviews enables students to build a high-resolution dataset useful for radar ground truth and other purposes. In general, severe storm verification from the National Weather Service (NWS) has spatial and temporal scales similar to associated severe weather warnings (Hales and Kelly 1985), on the order of 1,000 km 2 and tens of minutes. Although this spacing may be useful in verifying warnings, the spacing is too coarse to verify new severe weather ap… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
63
0

Year Published

2014
2014
2018
2018

Publication Types

Select...
10

Relationship

0
10

Authors

Journals

citations
Cited by 106 publications
(63 citation statements)
references
References 5 publications
(3 reference statements)
0
63
0
Order By: Relevance
“…Although data of this sort are generally confidential, they may be accessible through partnerships with insurance companies. Other sources of information on flash flood impacts could also be used, such as the logs of emergency services, emergency calls, information shared on social networks (USDHS, 2012;Jongman et al, 2015;Tkachenko et al, 2017), or information gathered in the field after or during the event (Ortega et al, 2009;Ruin et al, 2014). This information is also affected by uncertainties and severe biases, especially in flash flood situations: absence of information due to local breakdowns of communication networks, reduction of social network activity, and partial filling of emergency logs in strongly affected areas during the turmoil of the event.…”
Section: Discussionmentioning
confidence: 99%
“…Although data of this sort are generally confidential, they may be accessible through partnerships with insurance companies. Other sources of information on flash flood impacts could also be used, such as the logs of emergency services, emergency calls, information shared on social networks (USDHS, 2012;Jongman et al, 2015;Tkachenko et al, 2017), or information gathered in the field after or during the event (Ortega et al, 2009;Ruin et al, 2014). This information is also affected by uncertainties and severe biases, especially in flash flood situations: absence of information due to local breakdowns of communication networks, reduction of social network activity, and partial filling of emergency logs in strongly affected areas during the turmoil of the event.…”
Section: Discussionmentioning
confidence: 99%
“…MESH was defined as the hail diameter larger than 75% of the hail observed from a given storm. Ortega et al (2009) noted a wide range of measured hail sizes within a certain MESH value. Given these issues, MESH is used here as a proxy for likely hailfall size and location, rather than confirmation of the actual size of hail reaching the surface.…”
Section: ) Maximum Estimated Size Of Hailmentioning
confidence: 92%
“…Unlike NOAA's Storm Events Database, which is foremost interested in weather events independent of loss, SHELDUS focuses on loss data. Between 2008 and 2010, an experiment was also conducted by one of NOAA's laboratories to collect specific data on flash floods called the Severe Hazards Analysis and Verification Experiment (SHAVE; Gourley et al, 2013;Calianno et al, 2013;Ortega et al, 2009).…”
Section: Damage Data Collectionmentioning
confidence: 99%