Does increased resolution alone add value in regional climate model simulations of climate extremes? A multi-scale study over Western Canada

In this talk, Charles will discuss the ability of a regional climate model to represent observed extreme climate events and also examine the impact of increased model resolution on such extremes. Two climate simulations over Western Canada were conducted with the Canadian Regional Climate Model (CRCM4) at 15 kilometre (CRCM15) and 45 kilometre (CRCM45) horizontal resolution driven by large-scale reanalysis forcing over the period 1973-1995. The simulations were validated against ANUSPLIN, a daily observational gridded surface temperature and precipitation product with a nominal resolution of 10 km. A range of climate extremes were examined, comprising the 10th and 90th percentiles of daily maximum and minimum temperatures, the 90th percentile of daily precipitation (PR90), and the 27 core CLIMDEX indices. Model performance over three hydrological basins in British Columbia (Upper Peace, Nechako, and Upper Columbia), and at the grid locations of 28 meteorological stations within the basins, was also assessed.

As discussed in earlier work using CRCM45, the model exhibits cool and wet biases over most of the study region, which are also reflected in the extreme indices. While the higher sensitivity of CRCM15 to resolved topography and coastlines is clear from spatial maps, generally speaking, this does not result in a reduction of biases in seasonal temperature and precipitation extremes relative to ANUSPLIN. Nevertheless, added value in CRCM15, particularly for PR90, is detected at basin scales in certain seasons. At the station scale, errors in both configurations are evident due to grid-scale averaging. However, averaging PR90 from CRCM15 up to the 45 km grid results in a reduction of errors at most stations in the Upper Columbia basin compared to both CRCM versions and even ANUSPLIN. This result highlights the beneficial effect of spatial averaging in imperfect high-resolution climate models. Such upscaling can help reduce both spurious small-scale climate variability and differences between topographic data sets used in models and gridded observational products. Charles will end the talk with an illustration that exhibits the subtlety of finding appropriate metrics for the added value of high-resolution climate simulations. .

Bio: Charles Curry is a Research Associate with the Canadian Sea Ice and Snow Evolution Network and Adjunct Professor in the School of Earth and Ocean Sciences at the University of Victoria. He has been engaged in Earth system and regional climate modeling since 2003, holding various research posts at UVic and Environment Canada. His research interests include the effects of climate change on the hydrological cycle in Western North America, observed and modelled climate extremes, the behaviour and downscaling of surface winds, simulations of global climate engineering, and the biogeochemical and radiative modelling of greenhouse gases. He has provided expert advice to industry and various stakeholders on some of these issues, and maintains an interest in the effective communication of climate science to the public.