Quantifying the uncertainty introduced by internal climate variability in the projected Canadian crop yield changes
Budong Qian, Qi Jing, Ward Smith, Brian Grant, Alex Cannon, Xuebin Zhang (2020) Quantifying the uncertainty introduced by internal climate variability in the projected Canadian crop yield changes. Oral presentation, iCROPM2020, February 2-5, 2020, Montpellier, France.
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. Although internal climate variability is one of the three major sources of uncertainty in climate projections, the uncertainty due to internal climate variability is seldom quantified for crop yield projections. For this study, we utilized climate scenarios from 25 runs in a large ensemble of simulations by CanESM2 and CanRCM4, a global climate model and a regional climate model developed in Canada, in comparison with 20 GCMs in the Coupled Model Intercomparison Project Phase 5 (CMIP5), as inputs to the crop models in the Decision Support System for Agrotechnology Transfer (DSSAT v4.6) 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 and nitrogen stresses) 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 showed that the projected changes of potential yields for all three crops due to GCMs represent a larger uncertainty than the uncertainty attributed to internal climate variability at all warming levels. Projected changes of rainfed yields demonstrate a similar but larger uncertainty compared to the potential yields, indicating the effects of a large uncertainty in the projected precipitation changes. We also found that the uncertainty due to internal climate variability in the projected rainfed yields is often comparable to that associated with GCMs at the warming level of 1.5 °C, implying the need of accounting for the uncertainty related to internal climate variability in the projected crop yield changes for the near future, such as the time period reaching the climate target of 1.5 °C.