A high resolution regional climate model (RCM) is used to simulate climate of the recent past and to project future climate change across the northeastern US. Empirical Orthogonal Functions (EOF) analysis and K-means clustering analysis are applied to divide the northeastern US region into four climatologically different zones based on the surface air temperature and precipitation variability. The RCM simulations tend to overestimate surface air temperature, especially over the northern part of the domain in winter and over the western part in summer. The RCM simulation driven by the quasi-observed boundary data shows better capabilities than the simulations driven by the GCM in reproducing the mean and variability of temperature and precipitation.
Statistically significant increase in surface air temperature under both higher and lower emissions scenarios over the whole RCM domain suggests the robustness in the future warming. Most parts of the northeastern US region will experience increasing winter precipitation and decreasing summer precipitation, but the magnitudes are insignificant. Greater magnitude of the projected temperature increase by the end of the twenty-first century under the higher emissions scenario emphasizes the essential role of emissions choices in determining the potential future climate change.
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