Predicting climate change in Big Bend National Park, Texas

Abstract

This study uses statistical downscaling to improve the resolution of global climate model predictions of temperature and precipitation over the next 100 years in Big Bend National Park, Texas. The method is an adaptation of climate prediction by model statistics. I use historical data from 12 weather stations and the NCAR-NCAR reanalysis to build a model of the relationship between the surface and upper air, then use this model to downscale upper air output from several global climate models for several greenhouse gas emission scenarios. In this way the spatial resolution of climate change predictions is increased and maps can be produced of possible future temperature and precipitation patterns in the park.