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Title: wfip2.model/retro.rap.02.fcst.01 (Model: 10-Day Retrospective)

Abstract

The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the physics associated with the wind flow in and around the wind plant across a range of temporal and spatial scales, which will be gained through WFIP2’s observational field study and analysis.

Authors:
Publication Date:
Research Org.:
Atmosphere to Electrons (A2e) Data Archive and Portal, Pacific Northwest National Laboratory; PNNL
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1405135
DOE Contract Number:  
67025F
Resource Type:
Data
Data Type:
Specialized Mix
Country of Publication:
United States
Language:
English
Subject:
17 Wind Energy

Citation Formats

Macduff, Matt. wfip2.model/retro.rap.02.fcst.01 (Model: 10-Day Retrospective). United States: N. p., 2017. Web. doi:10.21947/1405135.
Macduff, Matt. wfip2.model/retro.rap.02.fcst.01 (Model: 10-Day Retrospective). United States. doi:10.21947/1405135.
Macduff, Matt. Fri . "wfip2.model/retro.rap.02.fcst.01 (Model: 10-Day Retrospective)". United States. doi:10.21947/1405135. https://www.osti.gov/servlets/purl/1405135.
@article{osti_1405135,
title = {wfip2.model/retro.rap.02.fcst.01 (Model: 10-Day Retrospective)},
author = {Macduff, Matt},
abstractNote = {The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the physics associated with the wind flow in and around the wind plant across a range of temporal and spatial scales, which will be gained through WFIP2’s observational field study and analysis.},
doi = {10.21947/1405135},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Oct 27 00:00:00 EDT 2017},
month = {Fri Oct 27 00:00:00 EDT 2017}
}

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