Our plane left the Seattle/Tacoma airport 15 minutes ago and the pilot just announced that we had reached our cruising altitude of 30,000 feet. Looking out the window, and resisting the temptation to fall asleep, I am reminded that climate models include land surface components that are parameterized at a scale similar to the landscape that stretches out below me. A grid cell depicts the spatial resolution of a climate model and is frequently measured in hundreds of square kilometers. At this scale it is possible to distinguish only broad characteristics of ecosystems. The structural and functional diversity that I know is present within these ecosystems when viewed on the ground, is seen as only different shades of green from this altitude. That becomes a problem when we try to represent critical processes that are important but must do so at scales far larger than those at which ecology, hydrology, plant and energy dynamics, and biogeochemical cycles play out on the landscape. High-resolution models where the grid cell is much smaller in size than that used in today's models are needed if we are to adequately represent this surface and subsurface complexity in climate models. Peter Thornton, a scientist at ORNL and a member of our NGEE team, emphasized this in a presentation last week. He indicated that high-resolution, process-rich models can help integrate results from field and lab research into climate models where the goal is to improve predictions at regional and global scales. While clearly an ambitious undertaking, we envision that the NGEE project with its combination of field observations, lab experiments, and process modeling can ultimately provide this high-resolution simulation capability for Arctic landscapes. It will be an exciting week as our team considers this goal while seeing first-hand the complexity of ecosystems across Alaska.
