542 Cost-effective Dynamical Downscaling: An Illustration of Downscaling CESM with the WRF Model

Wednesday, 9 January 2013
Exhibit Hall 3 (Austin Convention Center)
Jared H. Bowden, University of North Carolina, Chapel Hill, NC; and S. Arunachalam

Dynamical downscaling of climate change projections from Global Climate Models (GCMs) requires large computational resources (high cost) because dynamical downscaling requires simulating multiple years to decades to provide statistics of the weather. With cost-effective dynamical downscaling, we only simulate a year each in the contemporary and future periods (low cost) to project the climate change signal. Our strategy is to understand and acknowledge potential limitations (effectiveness) of using a select few years while selecting years of interest using a quantitative measure. Such a strategy is important for applications wanting to use dynamical downscaling information for select years. For instance, we have an interest in the impact of climate change on future year air quality as emissions change, where emissions estimates are available only for 2005 and 2025.

For illustrative purposes of cost-effective dynamical downscaling, we will downscale Climate Earth System Model (CESM) using the Weather Research and Forecasting (WRF) model for a year each in the contemporary and future climate. A comparison will be made between the dynamical downscaling projection to the GCM projection for both a 30-year mean climate and for the same select years. We will describe the quantitative method used to arrive at the years selected, discuss the potential limitations of those years selected, and summarize the effectiveness of downscaling select years.

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