UMD AOSC Seminar
Modeling Land Cover/Land Use Changes and Their Impact on Regional Climate
Professor Hugo Berbery
University of Maryland
Department of Atmospheric and Oceanic Science
The anthropogenic impacts of land cover/land use changes (LCLUC), which are second in importance after greenhouse gases, are very difficult to assess. They include urbanization, agriculture, desertification, deforestation and reforestation. Some studies have concluded that the contribution of land cover to climate change is about 10% of the total global change, but that regionally the relative contribution of LCLUC may be much larger. This seminar will discuss the impacts of LCLUC over vast areas of southern South America that have experienced recent changes in surface conditions not only due to the expansion of the agriculture at the expense of natural vegetation, but also due to changes in crop types. Unlike North America, where land cover changes have occurred throughout the last century, South America has had the largest land cover changes in the last few decades, therefore presenting a unique opportunity to assess the impact of those changes in an era when satellite data are available. The presentation will discuss the mechanisms by which LCLUC affect the local physical properties and the dynamical mechanisms that help transfer the signals to the atmospheric circulation.
Typically, LSMs included in regional models use land-cover classifications dictated by fixed attributes of vegetation, which reduces their ability to represent rapid changes including land-use shifts, but also the consequences on the land properties caused by preceding fires, floods, and droughts. Including the interannual variability of vegetation dynamics into land surface models (LSMs) is thus necessary to account for land use/cover change effects on climate models. The seminar will discuss a new approach for regional model simulations where land cover types are adapted to represent time-varying Ecosystem Functional Types (EFTs; patches of the land-surface with similar carbon gain dynamics) to characterize the spatial and inter-annual variability of vegetation dynamics across natural and agricultural systems.
April 8, 2010, Thursday