Project Objective

Develop an economical, computationally efficient, and scientifically sound approach to creating dynamical downscaled wind analyses for renewable energy applications that can be used for any region of the world.

Project Motivation

The increasing global demand for the finite (and sometimes volatile) supply of fossil fuels has spurred large investments in renewable energy resources that are clean, reliable, and reduce the Nation's dependence on foreign oil. Wind and solar are the fastest growing sources of renewable electric energy—U. S. wind energy capacity increased by 45% from 2006 to 2009 amid the nearly 30% global increase, a trend that is expected to continue. Yet, renewable energy companies struggle to assess the reliability of wind-generated electricity at prospective sites, owing to wind's intermittent nature.

We aim to greatly improve upon current wind energy prospecting techniques by creating prototype high-resolution dynamically downscaled wind analyses with NCAR's Climate Four Dimensional Data Assimilation System (CFDDA), based upon the state-of-the-art WRF model. CFDDA will use key NASA Earth science datasets to downscale the NASA MERRA global reanalyses to scales appropriate for assessing the wind variability for prospective wind farms (1-3 km). Innovative sampling strategies will be developed to generate the equivalent of a 20-year reanalysis for assessing seasonal to inter-annual variability. The impact of NASA datasets on dynamically downscaled winds will be quantified using ClimoFDDA for two different climate regimes in the U. S.: (1) coastal California and (2) the central Great Plains—both environments having great potential for wind-power production.

By incorporating key NASA Earth science observations and research results into an improved and more efficient wind energy prospecting capability that is ultimately intended for use by the renewable energy industry, we help accelerate the Nation's independence from foreign oil, and the development of clean, reliable and sustainable energy resources.

Composite characteristics for strong low-level jet (LLJ) events for the Great Plains region, as represented by NASA's Modern Era Retrospective Reanalysis(MERRA). The mean winds at 300 m AGL are shown by the arrows, and the colors denote the wind speeds. Thick black line marks the location of the cross section shown in the right panel. LLJs are the primary driver of the abundant wind resource over the Great Plains. They are shallow streams of fast moving air, usually located between about 300 to 600 m above the ground, with maximum wind speeds of 10-20 m s-1.