The North American Regional Climate Change Assessment Program (NARCCAP) is an international effort designed to investigate the uncertainties in regional-scale projections of future climate and produce highresolution climate change scenarios using multiple regional climate models (RCMs) nested within atmosphere–ocean general circulation models (AOGCMs) forced with the Special Report on Emission Scenarios (SRES) A2 scenario, with a common domain covering the conterminous United States, northern Mexico, and most of Canada. The program also includes an evaluation component (phase I) wherein the participating RCMs, with a grid spacing of 50 km, are nested within 25 years of National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) Reanalysis II. This paper provides an overview of evaluations of the phase I domain-wide simulations focusing on monthly and seasonal temperature and precipitation, as well as more detailed investigation of four subregions. The overall quality of the simulations is determined, comparing the model performances with each other as well as with other regional model evaluations over North America. The metrics used herein do differentiate among the models but, as found in previous studies, it is not possible to determine a “best” model among them. The ensemble average of the six models does not perform best for all measures, as has been reported in a number of global climate model studies. The subset ensemble of the two models using spectral nudging is more often successful for domain-wide root-mean-square error (RMSE), especially for temperature. This evaluation phase of NARCCAP will inform later program elements concerning differentially weighting the models for use in producing robust regional probabilities of future climate change.

[1] A comprehensive intercomparison of historical wind speed trends over the contiguous United States is presented based on two observational data sets, four reanalysis data sets, and output from two regional climate models (RCMs). This research thus contributes to detection, quantification, and attribution of temporal trends in wind speeds within the historical/contemporary climate and provides an evaluation of the RCMs being used to develop future wind speed scenarios. Under the assumption that changes in wind climates are partly driven by variability and evolution of the global climate system, such changes should be manifest in direct observations, reanalysis products, and RCMs. However, there are substantial differences in temporal trends derived from observational wind speed data, reanalysis products, and RCMs. The two observational data sets both exhibit an overwhelming dominance of trends toward declining values of the 50th and 90th percentile and annual mean wind speeds, which is also the case for simulations conducted using MM5 with NCEP-2 boundary conditions. However, converse trends are seen in output from the North American Regional Reanalysis, other global reanalyses (NCEP-1 and ERA-40), and the Regional Spectral Model. Equally, the relationship between changing annual mean wind speed and interannual variability is not consistent among the different data sets. NCEP-1 and NARR exhibit some tendency toward declining (increasing) annual mean wind speeds being associated with decreased (increased) interannual variability, but this is not the case for the other data sets considered. Possible causes of the differences in temporal trends from the eight data sources analyzed are provided. Motivation and Objectives[2] Wind speed time series have been subject to far fewer trend analyses than temperature and precipitation records [Gower, 2002;Keimig and Bradley, 2002;McAvaney et al., 2001;McVicar et al., 2008; Tomasin, 1999, 2003;Pryor and Barthelmie, 2003;Tuller, 2004;Brazdil et al., 2009], in part because of data homogeneity issues [Thomas et al., 2008;Tuller, 2004;DeGaetano, 1998]. However, understanding how evolution of the global climate system has been manifest as changes in near-surface wind regimes in the past and how near-surface wind speed regimes might alter in the future is of great relevance to the insurance industry [Changnon et al., 1999;Thornes, 1991], the construction and maritime industries [Ambrose and Vergun, 1997;Caires and Sterl, 2005;Caires et al., 2006], surface energy balance estimation [Rayner, 2007], the community charged with mitigating coastal erosion [Bijl, 1997;Viles and Goudie, 2003], the agricultural industry [O'Neal et al., 2005], forest and infrastructure protection communities [Jungo et al., 2002], and the burgeoning wind energy industry [Pryor et al., 2006b]. With respect to the latter, it is worth noting that during 2005-2008 over 18,000 MW of wind energy developments came online in the continental United States, increasing installed capacity to over 25 GW (AWEA wind ene...

We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs Climatic Change (2013) driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.

[1] In the last 25 years of the 20th century most major land regions experienced a summer warming trend, but the central U.S. cooled by 0.2 -0.8 K. In contrast most climate projections using GCMs show warming for all continental interiors including North America. We examined this discrepancy by using a regional climate model and found a circulation-precipitation coupling under enhanced greenhouse gas concentrations that occurs on scales too small for current GCMs to resolve well. Results show a local minimum of warming in the central U.S. (a ''warming hole'') associated with changes in low-level circulations that lead to replenishment of seasonally depleted soil moisture, thereby increasing late-summer evapotranspiration and suppressing daytime maximum temperatures. These regional-scale feedback processes may partly explain the observed late 20th century temperature trend in the central U.S. and potentially could reduce the magnitude of future greenhouse warming in the region.

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