The Alpert–Stein Factor Separation Methodology (FS) has been applied effectively in the Regional Atmospheric Modeling System (RAMS) to assess the relative contribution of different factors to weather and climate processes. In this chapter we will discuss model sensitivities to historical and future changes in land-use land-cover (LULC), biophysical and radiative effects of increased carbon dioxide (CO2) concentration and land-cover representation assessed using FS in weather and regional climate simulations for various regions around the world. This method emphasizes the importance of land-cover changes and CO2 biological effects when addressing regional-scale future climate change impacts.
Observations and modeling studies show that land-surface properties can influence the near-surface atmosphere through exchanges of heat, moisture, momentum, gases, and aerosols on timescales ranging from seconds to years, and on local to regional and possibly global spatial scales (Pielke, 2001; Arora, 2002; Pielke et al., 2002; Pitman, 2003; Niyogi et al. 2004; Foley et al., 2005). Urbanization, deforestation–reforestation, conversion of natural areas to agriculture, and increases in irrigation areas are some LULC modifications that often affect albedo, leaf area, roughness length, and root biomass. These landscape modifications can lead to changes in near-surface fluxes that affect temperature (e.g., Baidya Roy et al., 2003; Strack et al., 2008), humidity (e.g., Douglas et al., 2006, 2009; Roy et al., 2007), boundary-layer process, and precipitation (Pielke et al., 2007a). These changes can potentially feed back to the biophysical variables through a two-way interaction, enhancing or decreasing the initial perturbation (Pitman, 2003; Pielke and Niyogi, 2008).