Using a coupled atmospheric-biospheric modeling system (GEMRAMS) to model the effects of land-use/land-cover changes on the near-surface atmosphere

Abstract

A coupled atmospheric-biospheric model is a particularly valuable tool to study the potential effects of land-use/land-cover changes on near-surface atmosphere since the atmosphere and biosphere are allowed to dynamically interact through the surface and canopy energy balance. GEMRAMS is an ecophysiological process-based model, comprised of the Regional Atmospheric Modeling System (RAMS) and the General Energy and Mass Transport Model (GEMTM), and was used in this study. At a regional and seasonal scale, several spring-early summer simulations were conducted on a southern South America domain. GEMRAMS were able to simulate the observed monthly temperature and precipitation. Sensitivity to lateral boundary conditions was explored for RAMS using NCEP and ECMWF reanalysis as atmospheric forcing. Land-cover scenarios representing current, natural, and afforestation conditions were implemented for this region and used to simulate the impacts of land-cover changes on near-surface atmosphere. Changes in near-surface fluxes and temperature depended on the type of vegetation conversion and the season. Warmer temperatures were found in the conversion from wooded grasslands or forest to agriculture. Afforestation and conversion from grass to agriculture led to a cooler and wetter near-surface atmosphere. Additional simulations with a double CO2 concentration were also performed to assess the relative contributions of the land-cover and doubled CO2 forcing to meteorological and biological variables. At a local and diurnal scale, GEMRAMS was used to evaluate the effects of observed vegetation changes that occurred in the northern Chihuahuan Desert, from grasslands in the mid-1800s to shrub lands in the late 1900s. Simulations were performed using detailed vegetation maps for 1858 and 1998. Surface flux changes and the associated effects on near-surface temperature were spatially heterogeneous: different vegetation changes led to different effects, but albedo was the dominant parameter controlling the energy budget. Sensitivity experiments to soil moisture and mesquite cover were also conducted. Results of this study show that simulated shifts in vegetation led to complex interactions between biophysical and physiological characteristics of land and surface fluxes. These results also demonstrate that vegetation itself is a weather and climate variable as it significantly influences temperature, humidity, and surface fluxes.