Search Results

You are looking at 1 - 3 of 3 items for :

  • Risk assessment x
  • All content x
Clear All
Eleanor J. Burke, Chris D. Jones, and Charles D. Koven

, and suggested there might be an additional warming of 0.04°–0.23°C (68% range). MacDougall et al. (2012) , Koven et al. (2011) , and Schaefer et al. (2011) developed their land surface schemes to include a simple representation of permafrost-carbon and quantified the permafrost-carbon lost, but they incorporated a more limited uncertainty assessment. MacDougall et al. (2012) coupled their land surface scheme with a global climate model of intermediate complexity and found an additional

Full access
A. Anav, P. Friedlingstein, M. Kidston, L. Bopp, P. Ciais, P. Cox, C. Jones, M. Jung, R. Myneni, and Z. Zhu

projection of climate change, an assessment of their accuracy reproducing several variables for the present climate is required. In fact, the ability of a climate model to reproduce the present-day mean climate and its variation adds confidence to projections of future climate change ( Reifen and Toumi 2009 ). Nevertheless, good skills reproducing the present climate do not necessarily guarantee that the selected model is going to generate a reliable prediction of future climate ( Reichler and Kim 2008

Full access
Nathan P. Gillett, Vivek K. Arora, Damon Matthews, and Myles R. Allen

the uncertainty are shown in Fig. 7b . The calculated 5%–95% confidence range for TCR of 0.9–2.3 K lies mainly within the 1.0–3.5-K range reported by Hegerl et al. (2007) based on the assessment of previous such analyses and is somewhat narrower than the range of TCR in the models used here ( Fig. 7a ). It is broader than that determined by Gillett et al. (2012) using a single model, likely first due to our taking account of model uncertainty in the derivation of the regression coefficients

Full access