Abstract
This study evaluates General Circulation Models (GCMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for their ability in simulating historical means and extremes of daily precipitation (P), and daily maximum (Tmax), and minimum temperature (Tmin). Models are evaluated against hybrid observations at 2255 sub-basins across Alberta, Canada using established statistical metrics for the 1983–2014 period. Three extreme indices including consecutive wet days (CWD), summer days (SD), and warm nights (WN) are defined based on the peak over the threshold approach and characterized by duration and frequency. The tail behaviour of extremes is evaluated using the Generalized Pareto Distribution. Regional evaluations are also conducted for four climate sub-regions across the study area. For both mean annual precipitation and mean annual daily temperature, most GCMs more accurately reproduce the observations in northern Alberta and follow a gradient toward the south having the poorest representation in the western mountainous area. Model simulations show statistically better performance in reproducing mean annual daily Tmax than Tmin, and in reproducing annual mean duration compared to the frequency of extreme indices across the province. The Kernel density curves of duration and frequency as simulated by GCMs show closer agreement to that of observations in the case of CWD. However, it is slightly (completely) overestimated (underestimated) by GCMs for warm nights (summer days). The tail behaviour of extremes indicates that GCMs may not incorporate some local processes such as the convective parameterization scheme in the simulation of daily precipitation. Model performances in each of the four sub-regions are quite similar to their performances at the provincial scale. Bias-corrected and downscaled GCM simulations using a hybrid approach show that the downscaled GCM simulations better represent the means and extremes of P characteristics compared to Tmax and Tmin. There is no clear indication of an improved tail behaviour of GPD based on downscaled simulations.
Highlights
Simulations from the state-of-the-art General Circulation Models (GCMs) are becoming available for analysis and being included in the 6th assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) through the Coupled Model Intercomparison Project Phase 6 (CMIP6) [1]
Nie et al [44] pointed out the new cloud-fraction scheme updated in the CMIP6 version that might help to improve the simulation of temperature extremes by giving surface radiant fluxes in the low- and mid-latitudes
They found that the BCC-CSM2-MR model can simulate the warm and cold temperature extremes reasonably well
Summary
Simulations from the state-of-the-art General Circulation Models (GCMs) are becoming available for analysis and being included in the 6th assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) through the Coupled Model Intercomparison Project Phase 6 (CMIP6) [1]. CMIP6 is the set of future scenarios used to project climate evolution. The CMIP6 implemented scenarios are based on socioeconomic trajectories (i.e., shared socioeconomic pathways or SSP) [3], which work in harmony with the Representative Concentration. Multiple business-as-usual scenarios are available in CMIP6, and simulations from climate models are focused on biases, processes, and feedbacks. Evaluating the performance of CMIP6 models in reproducing the historical mean and extreme climate characteristics at a local scale is crucial and is an integral part of the confidence-building exercise for climate change projections
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
