Article citationsMore>>

Maurer, E.P., Wood, A.W., Adam, J.C., Lattenmaier, D.P. and Nijssen, B. (2002) A Long-Term Hydrologically-Based Dataset of Land Surface Fluxes and States for the Conterminous United States. Journal of Climate, 15, 3237-3251.
http://dx.doi.org/10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2

has been cited by the following article:

• 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skill and biases were presented in hindcasting daily minimum and maximum temperature and mean precipitation during a historical reference period, 1970-1999.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.