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Project ID: 07-2-1-42

Year: 2007

Date Started: 06/04/2007

Date Completed: 07/23/2010

Title: Predicting Lightning Risk Nationwide

Project Proposal Abstract: Dry thunderstorms are a major source of wildfires, and are disproportionately responsible for igniting major wildfires, yet currently dry thunderstorm predictions at high spatial resolutions are unavailable for most of the country. We propose development of improved dry lightning algorithms to expand their coverage, and improve accuracy and usability of such predictions in fire management. In JFSP project #01-1-6-08, a discriminant algorithm was developed for the Pacific Northwest. Additional work by NOAA?s Storm Prediction Center (SPC) has produced a statistical scheme to predict the location and intensity of lightning outbreaks. We propose here to build on this work in 3 ways: -Incorporate additional data to expand these predictions to other geographic areas as appropriate, including the interior of Alaska -Incorporate predictions of large lightning outbreaks (storms that generate hundreds to thousands of lightning strikes over relatively small areas) which ignite multiple fires, overwhelm suppression resources, and lead to a disproportionate number of uncontrolled wildfires -Determine the feasibility of using an alternative, physically based algorithm that includes temperature and moisture from multiple vertical atmospheric layers Specifically, we will obtain lightning strike data for Alaska and Canada (which was not available at the time we started our original JFSP project) to generate risk predictions for these domains. Additionally, we will incorporate a methodology developed by SPC to predict the probability of high numbers of cloud-to-ground flashes. By integrating these two approaches we will be able to create models for large lightning outbreaks occurring without significant rainfall and put into place forecasts available through our website. To address a weakness in the existing algorithm (it considers meteorological variables at only two vertical levels in the atmosphere), we will also develop and test a new geographically independent algorithm for identifying dry thunderstorm days, using moisture and temperature variables throughout a deeper atmospheric layer.

Principal Investigator: Miriam L. Rorig

Agency/Organization: Forest Service

Branch or Dept: PNW-Pacific Northwest Research Station

Other Project Collaborators

Type	Name	Agency/Organization	Branch or Dept
Co-Principal Investigator	Phillip Bothwell	NOAA-National Oceanic & Atmospheric Administration	NCEP-Storm Prediction Center
Federal Cooperator	Miriam L. Rorig	Forest Service	PNW-Pacific Northwest Research Station
Federal Fiscal Representative	Tamatha S. Verhunc	Forest Service	PNW-Pacific Northwest Research Station

Project Locations

Consortium

Alaska

There are no project locations identified for this project.

Project Deliverables

Final Report ("Results presented in JFSP Final Reports may not have been peer-reviewed and should be interpreted as tentative until published in a peer-reviewed source.")

	ID	Type	Title
	8402	Conference/Symposia/Workshop	A Climatology and the Intra-Seasonal Variation of Summertime Cloud-to-Ground Lightning in Mainland Alaska
	8401	Conference/Symposia/Workshop	Using the Perfect Prognosis Technique for Predicting Cloud-to-Ground Lightning in Mainland Alaska

Supporting Documents

The following supporting documents are available for this project.

Brief

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