Title: Nonlocal inadvertent weather modification associated with wind farms in the Central United States

Author: Matthew J. Lauridsen (Texas Tech University)
Brian Ancell (Texas Tech University)

With the recent push for alternative, renewable energy, the wind energy industry has seen a marked boom in the United States and other countries. An interesting consequence of the creation of wind farms has been an inadvertent change in weather. The local effects within and near the farms have been well documented by a number of studies and observational campaigns; however, the broader nonlocal atmospheric effects of wind farms are much less clear. In turn, there is a need to understand how wind farms are impacting the atmosphere on large temporal and spatial scales. The main goal of this study is to determine how wind farm- induced perturbations evolve over periods of days, and over areas of thousands of square kilometers, to modify specific atmospheric features that have large impacts on society and the environment (e.g., cyclogenesis, quantity of precipitation).

Here we use an ensemble approach with the WRF mesoscale model and a wind farm parameterization outlined in Fitch et al. (2012) to quantify the sensitivity of meteorological variables to the presence of wind farms. This wind farm parameterization imposes a momentum sink on the mean flow and transfers kinetic energy into electricity and turbulent kinetic energy. Ensemble variations involving wind farm locations and sizes for cases of cyclogenesis are explored to determine how perturbations evolve into significant changes to nonlocal aspects of the atmospheric state.

GMAO Head: Steven Pawson Global Modeling and Assimilation Office NASA Goddard Space Flight Center

Curator: Nikki Privé Last Updated: Feb 9 2015