Skip to main content
The University of Massachusetts Amherst

Assessment of regional climate model simulation estimates over the northeast United States

Authors:

Michael Rawlins

Raymond Bradley

Henry Diaz

Publication Type:
Journal Article
Year of Publication:
2012
Secondary Title:
Journal of Geophysical Research
ISSN:
0148-0227
DOI:
10.1029/2012JD018137
Volume:
117
Year:
2012
Date:
2012

Abstract

Given the coarse scales of coupled atmosphere-ocean global climate models, regional climate models (RCMs) are increasingly relied upon for studies at scales appropriate for many impacts studies. We use outputs from an ensemble of RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) to investigate potential changes in seasonal air temperature and precipitation between present (1971–2000) and future (2041–2070) time periods across the northeast United States. The models show a consistent modest cold bias each season and are wetter than observations in winter, spring, and summer. Agreement in spatial variability and pattern correlation is good for air temperature and marginal for precipitation. Two methods were used to evaluate robustness of the mid 21st century change projections; one which estimates model reliability to generate multimodel means and assess uncertainty and a second which depicts multimodel projections by separating lack of climate change signal from lack of model agreement. For air temperature we find changes of 2–3C are outside the level of internal natural variability and significant at all northeast grid cells. Signals of precipitation increases in winter are significant region wide. Regionally averaged precipitation changes for spring, summer, and autumn are within the level of natural variability. This study raises confidence in mid 21st century temperature projections across the northeast United States and illustrates the value in comprehensive assessments of regional climate model projections over time and space scales where natural variability may obscure signals of anthropogenically forced changes.