A climate model investigation of lower-atmospheric wind speed biases over wind farm development regions of the continental United States
Jonathan Collier, Garrad Hassan America, Inc., San Diego, CA; and G. Zhang
The new energy economy of the U.S. will depend on the long-term success of wind as a conventional source of power. Wind (and solar) forms of power currently are required to comprise at least a portion of the total power portfolio for many states. This requirement fuels regional development, and a federal renewable portfolio standard likely will increase development and force a much-needed upgrade and expansion of the nation's electric transmission system. While this expansion certainly presents the largest present challenge to increased penetration of wind, there also has been a growing concern over the long-term stability of the lower-atmospheric wind resource in the U.S. -- and across the rest of the world. There is speculation, supported by a number of modeling studies, that a warming climate may reduce the wind resource. Such studies have been largely inconclusive however, primarily due to contradictory results from simulations of future climate and trends assessed from long-term records of data, whose methods of measurement have been inconsistent.
It is well known that global climate models are relatively unreliable in their simulations of low-level wind magnitude, compared to those of other atmospheric variables. Studies of the long-term projection of lower-atmospheric wind under climate change scenarios generally rely on some form of physical and/or statistical downscaling of other model output variables. It is of interest, particularly for further model improvement however, to address the underlying causes of poor wind climate simulation so that these models can be more valuable in long-term projections of wind resource and sensitivity studies. One of the models used in the most recent IPCC report is the National Center for Atmospheric Research's Community Climate System Model. The output from various control and climate change scenario simulations at T85 resolution used in the report is archived and available for analysis. An analysis of lower atmospheric wind speed simulation from this model's control run indeed shows biases over high wind resource areas including the northern Plains and upper Midwest. In these regions, where wind is predominantly westerly, zonal wind speeds are biased high in the model by as much as 20% when compared to long-term records. This project aims to understand the nature of such biases and investigate their possible causes. Multiple, carefully-designed simulations of the atmospheric component of this model, the Community Atmosphere Model, are carried out and monthly mean wind speeds are compared to same-height means from tower measurements in high wind resource regions such as west Texas, the Central Plains, and the Midwest. Diagnosis of biases is sought by linking the simulation of boundary-layer wind speed to the simulation of other atmospheric variables and to possible deficiencies in model physics. Additionally, slab-ocean projected greenhouse warming simulations of the coupled model (the CCSM) are carried out to measure the sensitivity of projections to wind speed bias.
Extended Abstract (2.1M)
Joint Session 9, Wind Energy: Applied Modeling and Forecasting I
Wednesday, 20 January 2010, 8:30 AM-10:00 AM, B202
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