Description

The climate change information required for many impact studies is of a spatial scale much finer than that provided by general circulation models (GCMs). This is especially true for regions of complex topography, coastal locations, and highly mixed land cover areas like that of the Southern California region. GCMs have resolutions of hundreds of kilometers which have limited capabilities when planning mitigation strategies for a changing climate. This project uses statistical downscaling to increase the resolution from 100 x 100km to 4 x 4km per pixel. It aims to create a host of programming scripts to downscale GCM outputs and analyze the future morning and afternoon temperatures for the Southern California region. Morning and afternoon temperatures are essential because they represent the average lowest and highest temperatures of the day, which are critical for forecasting changes to the coastal marine layer and increased energy usage. Geographically knowing where temperatures will increase and by how much will assist city planners in implementing mitigations to combat the challenges associated with climate change.