PARENT SESSION
Oral Session # 72: GIS and Remote Sensing I.
Presiding: J Drake
Thursday, August 7. 8:00 AM to 11:30 AM, SITCC Meeting Room 203.
Climate models and landscape heterogeneity: Can we see the forest without the trees?
Prihodko, Lara*,1, Denning, A. Scott1, Nicholls, Melville1, 1 Colorado State University, Fort Collins, CO
ABSTRACT- Ecological processes and land surface atmosphere interactions occur at spatial scales much finer than is commonly represented in global and regional atmospheric circulation models. Restrictions on the representation of land surface processes in these models are typically driven by computational limitations and by the spatial scale of available input data. Mismatches in scale are commonly addressed through functional groupings of vegetation types and averaging of surface properties and soil characteristics. Remotely sensed data is often relied upon to characterize those surface processes and conditions which cannot be easily measured on the surface, either spatially or temporally, at the necessary scales. What are the consequences of disregarding fine scale landscape heterogeneity for regional and global simulations of land surface-atmosphere interactions and boundary layer processes? This study reports on experiments using a spatially explicit coupled land-surface atmosphere model, the Simple Biosphere Model (SiB2) coupled to the Regional Atmospheric Modeling System (RAMS). The coupled model was parameterized using AVHRR data, the STATSGO soil database, a land cover type map and NCEP reanalysis data for a domain in the upper Midwest United States. Simulations were run with varying land surface representations and used to explore how point and regional fluxes of carbon dioxide, latent and sensible heat, and atmospheric properties, depend on the resolution with which the land surface is represented. Differences in simulated fluxes and scalar fields were observed between resolutions however domain average fluxes appear to smooth this variability.
Key words: Remote Sensing, Regional modeling, Scaling, Landscape Heterogeneity