Novel climates—emerging conditions with no analog in the observational record—are an open problem in ecological modelling. Detecting extrapolation into novel conditions is a critical step in evaluating bioclimatic projections of how species and ecosystems will respond to climate change. However, biologically-informed novelty detection methods remain elusive for many modeling algorithms. To assist with bioclimatic model design and evaluation, we present a first-approximation assessment of general novelty based on a simple and consistent characterization of climate. We build on the seminal global analysis of Williams et al. (2007, PNAS) by assessing of end-of-21st-century novelty for North America at high spatial resolution and by refining their standardized Euclidean distance into an intuitive Mahalanobian metric called sigma dissimilarity.
Like Williams et al. (2007), we found extensive novelty in end-of-21st-century projections for the warm southern margin of the continent as well as the western Arctic. In addition, we detected localized novelty in lower topographic positions at all latitudes: by the end of the 21st century, novel climates are projected to emerge at low elevations in 80% and 99% of ecoregions in the RCP4.5 and RCP8.5 emissions scenarios, respectively. Novel climates are limited to 7% of the continent’s area in RCP4.5, but are much more extensive in RCP8.5 (40% of area). These three risk factors for novel climates—regional susceptibility, topographic position, and the magnitude of projected climate change—represent a priori evaluation criteria for the credibility of bioclimatic projections. Our findings indicate that novel climates can emerge in any landscape. Interpreting climatic novelty in the context of non-linear biological responses to climate is an important challenge for future research.