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Seneviratne, S.I., Nicholls, N., Easterling, D., Goodess, C.M., Kanae S., Kossin, J., Luo, Y., Marengo, J., McInnes, K., Rahimi, M., Reichstein, M., Sorteberg, A., Vera, C. and Zhang, X. (2012) Changes in Climate Extremes and Their Impacts on the Natural Physical Environment. Managing the Risks of Extreme Events and Distasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC), Cambridge University Press, Cambridge.
has been cited by the following article:
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TITLE:
NARCCAP Model Skill and Bias for the Southeast United States
AUTHORS:
Erik D. Kabela, Gregory J. Carbone
KEYWORDS:
NARCCAP, Model Skill, Model Bias
JOURNAL NAME:
American Journal of Climate Change,
Vol.4 No.1,
March
23,
2015
ABSTRACT: This paper investigates dynamically downscaled regional climate model
(RCM) output from the North American Regional Climate Change Assessment Program
(NARCCAP) for two sub-regions of the Southeast United States. A suite of four
statistical measures were used to assess model skill and biases were presented
in hindcasting daily minimum and maximum temperature and mean precipitation
during a historical reference period, 1970-1999. Most models demonstrated high
skill for temperature during the historical period. Two outliers included two
RCMs run using the Geophysical Fluids Dynamics Lab (GFDL) model as their
lateral boundary conditions; these models suffered from a cold maximum
temperature bias. Improvement with GFDL-based projections of maximum temperature was noted
from May through November when they ran with observed seasurface conditions
(GFDL-timeslice), particularly for the east sub-region. Precipitation skill
proved mixed-relatively high when measured using a probability density function
overlap measurement or the index of agreement, but relatively low when measured
with root-mean square error or mean absolute error, because several models
overestimated the frequency of extreme precipitation events.