EaSM-3: Land Use Change and Land Atmosphere Feedback Processes as Regulators of Regional Climate Change

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Changes in land use and land cover, such as converting forests to cropland or irrigating formerly dry areas, are known to impact climate on the local and regional level. There is some indication from prior modeling studies that the land-atmosphere interactions that cause these climate impacts will become more pronounced in a warming world. In order to further study this concept, researchers will perform simulations using advanced numerical models and compare those results to observational data to assess how the models are performing. This study will impact society by providing better information to policymakers about the impact of future land use changes. The project would also provide an opportunity to train the next generation of scientists through the inclusion of a graduate student and a postdoctoral researcher in the study.The researchers hypothesize that the rate of climate change, frequency and severity of extremes, and predictability of climate variations will depend on the type of regional land use practices implemented in the coming decades. While the study of land use land cover change (LULCC) impacts on climate are not new, this project is starting from a point where the model consensus is that there will be a strengthened coupling between land and atmosphere in a warming climate. This result would mean that climate may become more sensitive to both natural and anthropogenic variations at the land surface. Two main hypotheses will be addressed: 1) Regions of strong land-atmosphere feedback in the physical climate system will evolve significantly in a changing climate, and 2) regionally, the rate of climate change, the frequency and severity of extremes, and the predictability of climate variability will be dependent on the type of land use practices implemented in the coming decades. To address these hypotheses, the PIs plan to use the Community Earth System Model (CESM) with a focus on the Community Land Model (CLM) and Community Atmosphere Model (CAM). A variety of observational data would be used to validate the models.