Fine‐resolution climate projections enhance regional climate change impact studies

Abstract

A new data set enhances the abilities of researchers and decision‐makers to assess possible future climates, explore societal impacts, and approach policy responses from a risk‐based perspective. The data set, which consists of a library of 112 fine‐resolution climate projections, based on 16 climate models and three greenhouse gas emissions scenarios, is now publicly available. Monthly climate projections from 1950 to 2099 were downscaled to a spatial resolution of ⅛° (about 140 square kilometers per grid cell) covering the conterminous United States and portions of Canada and Mexico. For the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, climate modeling groups produced hundreds of simulations of past and future climates. The colocation of these simulations in a single archive (at the Program for Climate Model Diagnosis and Intercomparison at Lawrence Livermore National Laboratory (LLNL), established to facilitate assessment of general circulation models, or GCMs) and the conversion of all results to a common data format have made probabilistic, multi‐model projections and impact assessments practical. A remaining issue is that the spatial scale of climate model output is typically too coarse for regional impact studies. Multiple downscaling approaches exist for deriving regional climate from coarse‐resolution model output; these approaches are typically applied on an ad hoc basis to a particular region.

The role of meteorological processes in the description of uncertainty for climate change decision-making

“…We provide an assessment of the Maurer et al (2007) BCSD CMIP3 precipitation projections for the Great Lakes region. A more recent analysis of CMIP5 models suggests no significant improvement in the mean representation of North American precipitation (Sheffield et al 2013), so the use of CMIP5 does not substantially change our conclusions.…”

“…The downscaled version we assess, the Bias Corrected and Spatially Downscaled (BCSD) climate projections (Maurer et al 2007), referenced in our study as the BCSD or downscaled data, was provided to the user community as potentially useful in a wide range of applications. The BCSD methodology consists of (1) a bias correction procedure that uses quantile mapping to correct model biases based on an observed 1950-1999 climatology and (2) a spatial downscaling interpolation of the monthly bias-corrected models based on a high-resolution (1/8°) observed data set (Maurer et al 2007;Maurer et al 2002).…”

Climate Change and Groundwater: Vulnerability, Adaptation and Mitigation Opportunities in India

“…As these competing demands intensify under climate change, effective governance for balancing water demand will become essential, particularly in the face of strong pressure to priorities industrial uses over other uses such as drinking, agricultural supplies. The Stockholm Environment Institute estimates that, based on only a moderate climate change, by 2025 the proportion of the world's population living in countries of significant water stress will increase from approximately 34 percent to 63 percent [9]. The consequences for water supply include smaller flows in springs and rivers, and decreasing groundwater level.…”

Analysis of Scenarios to Adapt to Climate Change Impacts in the Rio Conchos Basin

“…This research uses statistically downscaled temperature and precipitation from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset (Maurer et al 2007) for emission scenarios A2 and A1B. Statistically downscaled results from five GCMs were selected: CGCM31 (Canada), CCSM3 (US), ECHAM5 (Germany), MIROC3.2 (Japan), and HadCM3 (UK).…”