Presentation description

Energy fluxes between the land surface and the atmosphere are modulated by complex biogeophysical processes. Surface property characteristics are crucial in governing atmospheric response mechanisms because they initiate forcings that alter the surface energy budget. Here, I plotted and mapped the output of coupled land-atmosphere simulations from CESM to show that modifying forest surface properties significantly impacts the surface energy budget in different NEON domains, and that the same change in forest cover has different impacts on surface climate in different regions. Modifying surface properties can impact local surface climate by changing the energy budget's interaction with the atmosphere, potentially altering atmospheric circulation, and creating teleconnections. The Community Earth System Model (CESM) is a global earth system model that simulates biogeochemical cycling between the land surface and the atmosphere. Forest loss simulations from previous studies using this model have shown that changes in surface properties have the capacity to create significant teleconnections to other regions on a global scale. However, more information needs to be generated about its effect on the U.S, specifically in different domains of the National Ecological Observatory Network (NEON). I analyzed CESM output using Python programming (CHPH, version 3.10.3) to display net changes of sensible/latent heat, and incoming/outgoing shortwave & longwave radiation resulting from removal of forests in 4 NEON domains: the Pacific Northwest/Southwest, and the Atlantic Southeast/Northeast. Simulations show that larger energy fluxes changes occurred in heavily forested areas, impacting outgoing longwave radiation the most. I also found that indirect radiative forcing greatly influenced the surface energy budget resulting in a spectrum of responses varying by region. More research needs to be done to investigate the seasonality of when bigger and smaller changes in surface fluxes due to forest loss occur and how these changes impact climate both locally and remotely.