Upscaling and Downscaling - A Regional View of the Soil-Plant-Atmosphere Continuum

Abstract

The strength of interaction among soil, plants, and atmosphere depends highly on scale. As the spatial scale of organized soil-plant behavior (e.g., soil drying and/or stomatal closure) increases, so does the influence the land surface has on atmospheric properties and circulations. Counterbalancing this is a system of feedback loops that serve to reduce the sensitivity of surface fluxes to changes in surface conditions. Model upscaling involves capturing land-atmosphere feedbacks and effects of land surface heterogeneity on surface fluxes and atmospheric boundary-layer dynamics that become operative at progressively larger spatial scales. Conversely, by downscaling, we learn how to appropriately parameterize subgrid-scale phenomena within large-scale modeling frameworks. This paper discusses some of the major challenges faced today in properly describing system behavior at regional spatial scales. We focus on a suite of simple biophysical models, tied closely to remote sensing, that work synergistically from canopy to mesoscales. This suite includes a diagnostic regional-scale model used for routine mapping of flux and moisture conditions across the United States at 10-km resolution. A related approach disaggregates regional flux estimates to local scales (100-10 2 m) for comparison with ground-based measurements or for use in site-specific agricultural or resource management applications. Coupled with turbulence- and mesoscale atmospheric models, the core land surface representation provides means for assimilating remote sensing data into large-eddy simulations and improving short-range weather forecasts. This multiscale modeling framework is being utilized in a concerted research effort aimed at identifying scale-relevant land-atmosphere feedbacks and representing surface heterogeneity efficiently and robustly in regional modeling schemes.