Publications

West, Tristram O.; Le Page, Yannick; Huang, Maoyi; Wolf, Julie; Thomson, Allison M. (2014). Downscaling global land cover projections from an integrated assessment model for use in regional analyses: results and evaluation for the US from 2005 to 2095. ENVIRONMENTAL RESEARCH LETTERS, 9(6), 64004.

Abstract
Projections of land cover change generated from integrated assessment models (IAM) and other economic-based models can be applied for analyses of environmental impacts at sub-regional and landscape scales. For those IAM and economic models that project land cover change at the continental or regional scale, these projections must be downscaled and spatially distributed prior to use in climate or ecosystem models. Downscaling efforts to date have been conducted at the national extent with relatively high spatial resolution (30 m) and at the global extent with relatively coarse spatial resolution (0.5 degrees). We revised existing methods to downscale global land cover change projections for the US to 0.05 degrees resolution using MODIS land cover data as the initial proxy for land class distribution. Land cover change realizations generated here represent a reference scenario and two emissions mitigation pathways (MPs) generated by the global change assessment model (GCAM). Future gridded land cover realizations are constructed for each MODIS plant functional type (PFT) from 2005 to 2095, commensurate with the community land model PFT land classes, and archived for public use. The GCAM land cover realizations provide spatially explicit estimates of potential shifts in croplands, grasslands, shrublands, and forest lands. Downscaling of the MPs indicate a net replacement of grassland by cropland in the western US and by forest in the eastern US. An evaluation of the downscaling method indicates that it is able to reproduce recent changes in cropland and grassland distributions in respective areas in the US, suggesting it could provide relevant insights into the potential impacts of socioeconomic and environmental drivers on future changes in land cover.

DOI:
10.1088/1748-9326/9/6/064004

ISSN:
1748-9326