Application of a prognostic model validation system to real-time dispersion modeling

PDF Version Also Available for Download.

Description

The Atmospheric Release Advisory Capability (ARAC) at the Lawrence Livermore National Laboratory uses the U.S. Navy's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) to supply high-resolution wind data for use in its real-time dispersion modeling system. ARAC has used COAMPS products to support several events and exercises, and COAMPS forecasts appear accurate, based on qualitative examination. Recently ARAC has developed a quantitative verification system which calculates COAMPS error and bias statistics, comparing COAMPS forecasts of various lengths with observational data. This paper shows how this system has been used to guide ARAC operators, who need an estimate of the likely behavior ... continued below

Physical Description

777 Kilobytes pages

Creation Information

Pace, J C October 18, 1999.

Context

This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

Who

People and organizations associated with either the creation of this article or its content.

Author

Sponsor

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this article. Follow the links below to find similar items on the Digital Library.

Description

The Atmospheric Release Advisory Capability (ARAC) at the Lawrence Livermore National Laboratory uses the U.S. Navy's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) to supply high-resolution wind data for use in its real-time dispersion modeling system. ARAC has used COAMPS products to support several events and exercises, and COAMPS forecasts appear accurate, based on qualitative examination. Recently ARAC has developed a quantitative verification system which calculates COAMPS error and bias statistics, comparing COAMPS forecasts of various lengths with observational data. This paper shows how this system has been used to guide ARAC operators, who need an estimate of the likely behavior of COAMPS forecasts of various lengths in different regions, seasons, and weather patterns.

Physical Description

777 Kilobytes pages

Source

  • American Meteorological Science (AMS) 80th Annual Meeting, Long Beach, CA (US), 01/09/2000--01/14/2000

Language

Item Type

Identifier

Unique identifying numbers for this article in the Digital Library or other systems.

  • Report No.: UCRL-JC-136134
  • Report No.: DP0402061
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 756956
  • Archival Resource Key: ark:/67531/metadc705947

Collections

This article is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

What responsibilities do I have when using this article?

When

Dates and time periods associated with this article.

Creation Date

  • October 18, 1999

Added to The UNT Digital Library

  • Sept. 12, 2015, 6:31 a.m.

Description Last Updated

  • May 5, 2016, 9:03 p.m.

Usage Statistics

When was this article last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 2

Interact With This Article

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Pace, J C. Application of a prognostic model validation system to real-time dispersion modeling, article, October 18, 1999; California. (digital.library.unt.edu/ark:/67531/metadc705947/: accessed September 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.