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On Bridging A Modeling Scale Gap: Mesoscale to Microscale Coupling for Wind Energy

Authors :
Domingo Muñoz-Esparza
Rao Kotamarthi
Branko Kosovic
Michael Robinson
Brandon Lee Ennis
Matthew J. Churchfield
Raj K. Rai
Caroline Draxl
Gökhan Sever
Patrick Moriarty
Laura Mazzaro
Eunmo Koo
Sue Ellen Haupt
Joel Cline
Eliot Quon
William J. Shaw
Jeffrey D. Mirocha
Larry K. Berg
Source :
Bulletin of the American Meteorological Society. 100:2533-2550
Publication Year :
2019
Publisher :
American Meteorological Society, 2019.

Abstract

Accurately representing flow across the mesoscale to the microscale is a persistent roadblock for completing realistic microscale simulations. The science challenges that must be addressed to coupling at these scales include the following: 1) What is necessary to capture the variability of the mesoscale flow, and how do we avoid generating spurious rolls within the terra incognita between the scales? 2) Which methods effectively couple the mesoscale to the microscale and capture the correct nonstationary features at the microscale? 3) What are the best methods to initialize turbulence at the microscale? 4) What is the best way to handle the surface-layer parameterizations consistently at the mesoscale and the microscale? 5) How do we assess the impact of improvements in each of these aspects and quantify the uncertainty in the simulations? The U.S. Department of Energy Mesoscale-to-Microscale-Coupling project seeks to develop, verify, and validate physical models and modeling techniques that bridge the most important atmospheric scales determining wind plant performance and reliability, which impacts many meteorological applications. The approach begins with choosing case days that are interesting for wind energy for which there are observational data for validation. The team has focused on modeling nonstationary conditions for both flat and complex terrain. This paper describes the approaches taken to answer the science challenges, culminating in recommendations for best approaches for coupled modeling.

Details

ISSN :
15200477 and 00030007
Volume :
100
Database :
OpenAIRE
Journal :
Bulletin of the American Meteorological Society
Accession number :
edsair.doi...........b2cb1ed1338b654dca5d7321e3accd65