The East African Great Lake Environments (EAGLE) Climate Downscaling Dataset
Grim, J. A., Pinto, J. A., Jensen, A. A., & Seimon, A. (2020). The East African Great Lake Environments (EAGLE) Climate Downscaling Dataset (No. NCAR/TN-563+STR). doi:10.5065/xvky-2g77
The East African Great Lake Environments (EAGLE) climate downscaling dataset was created to provide a high-resolution depiction of present and future climate scenarios in the EAGLE region, in order to serve the needs of a wide range of stakeholders who are interested in the potential socio-ecolog... Show moreThe East African Great Lake Environments (EAGLE) climate downscaling dataset was created to provide a high-resolution depiction of present and future climate scenarios in the EAGLE region, in order to serve the needs of a wide range of stakeholders who are interested in the potential socio-ecological and socio-economic impacts of climate change. Due to limited funds and a fixed amount of computational resources, rather than performing continuous century-scale model runs, three decadal time periods were simulated: present day (2009-2018), mid-century (2055-2064), and end-of-century (2090-2099.) The Weather Research and Forecasting (WRF) model was used to dynamically downscale the National Center for Atmospheric Research’s (NCAR’s) Community Earth System Model (CESM) input using Representative Concentration Pathways (RCP) 8.5 for future climate, and RCP 4.5 for present day. A 10 km spatial resolution was used for the outer domain, and convection-permitting resolution of 3.33 km on the inner domain. The resulting output data set consists of thirty-nine different fields, with hourly resolution on the inner domain, and 6-hourly on the outer. To optimize the model configuration for this location and climate, before the full simulations were done, a series of 18 sensitivity tests were performed, comparing model output with observations. The full simulation data files are available to anyone who wants access to them at NCAR’s Climate Data Gateway at https://dx.doi.org/10.26024/mahn-2660Show less