Uncertainty introduced by internal climate variability in the projected climate change impacts on Canadian crop yields
Budong Qian, Qi Jing, Ward Smith, Brian Grant, Alex Cannon, Xuebin Zhang (2020) Uncertainty introduced by internal climate variability in the projected climate change impacts on Canadian crop yields. Oral Presentation, American Meteorological Society Annual Meetings 20202, January 10 -16, 2020, Boston, USA.
Internal climate variability is one of the three major sources of uncertainty in climate projections. Consequently, this uncertainty cascades into uncertainty in crop yield projections along with the crop model structural uncertainty. Quantification of the uncertainty in crop yield projections is typically ascertained using multiple crop models and using an ensemble of climate scenarios, from multiple global climate models (GCMs), under different forcing scenarios. The quantification of the uncertainty due to internal climate variability, however, is seldom ascertained. For this study, we utilized climate scenarios from 20 GCMs in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and together with 25 runs in a large ensemble of simulations by CanESM2 and CanRCM4, a global climate model and a regional climate model developed in Canada, as inputs to the crop models in the Decision Support System for Agrotechnology Transfer (DSSAT v4.7) to estimate future crop production changes. The large ensemble of simulations by CanESM2 and CanRCM4 were run with slightly different initial conditions for evaluating internal climate variability in climate projections. With the crop models and the indicated climate scenarios, we simulated both potential (no water or nitrogen stress) and rainfed (no nitrogen stress) yields for canola, maize and spring wheat under the baseline climate of 2006 -2015 and future climates at the global warming levels at 1.5, 2.0, 2.5 and 3.0 °C above the preindustrial level. Our results indicate that the projected changes of potential yields due to GCMs represent a larger uncertainty than the uncertainty attributed to internal climate variability. The uncertainty due to GCMs increases at higher warming levels while it remained mostly consistent for internal climate variability. Projected changes of rainfed yields demonstrate a similar uncertainty as the potential yields but with a larger uncertainty due to internal climate variability. The uncertainty in rainfed maize yields due to internal climate variability was much larger than that due to GCMs at all three warming levels. This agrees well with large internal climate variability in precipitation that represents a significant irreducible uncertainty in crop yield projections.