The importance of classification differences and spatial resolution of land cover data in the uncertainty in model results over boreal ecosystems

One of the governing scientific objectives of the Boreal Ecosystem-Atmosphe re Study (BOREAS) is the development of methods for applying process models over large spatial scales using remote sensing and other integrative model ing techniques. This paper presents the first step in a modeling strategy t hat focuses on scaling a point model up to the BOREAS regional scale. The o bjective of this paper is to compare the effect of differences in spatial r esolution of land cover data to land-atmosphere model results relative to t he effect of differences in land cover sensors and classification schemes. The analysis suggests that the uncertainty in model results arises mainly f rom the uncertainty in the land cover classification and that the lack of s patial resolution has a lower effect. Overall, an uncertainty of approximat ely 15% in modeled energy and water balance fluxes and states has to be ass igned because of the uncertainty in land cover classification.