Chances of Short-Term Cooling Estimated from a Selection of CMIP5-Based Climate Scenarios during 2006–35 over Canada - Grenier, Patrick; De Elía, Ramón; Chaumont, Diane (Journal of Climate, 2015)
Abstract The path toward a warmer global climate is not smooth, but, rather, is made up of a succession of positive and negative temperature trends, with cooling having more chance to occur the shorter the time scale considered. In this paper, estimates of the probabilities of short-term cooling ( P cool ) during the period 2006–35 are performed for 5146 locations across Canada. Probabilities of cooling over durations from 5 to 25 yr come from an ensemble of 60 climate scenarios, based on three different methods using a gridded observational product and CMIP5 climate simulations. These methods treat interannual variability differently, and an analysis in hindcast mode suggests they are relatively reliable. Unsurprisingly, longer durations imply smaller P cool values; in the case of annual temperatures, the interdecile range of P cool values across Canada is, for example, ~2%–18% for 25 yr and ~40%–46% for 5 yr. Results vary slightly with the scenario design method, with similar geographical patterns emerging. With regards to seasonal influence, spring and winter are generally associated with higher P cool values. Geographical P cool patterns and their seasonality are explained in terms of the interannual variability over background trend ratio. This study emphasizes the importance of natural variability superimposed on anthropogenically forced long-term trends and the fact that regional and local short-term cooling trends are to be expected with nonnegligible probabilities.

Challenges in the Quest for Added Value of Regional Climate Dynamical Downscaling - Di Luca, Alejandro; De Elía, Ramón; Laprise, René (Current Climate Change Reports, 2015)

Potential for small scale added value of RCM’s downscaled climate change signal - Di Luca, Alejandro; De Elía, Ramón; Laprise, René (Climate Dynamics, 2013)

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations - Di Luca, Alejandro; De Elía, Ramón; Laprise, René (Climate Dynamics, 2012)

Decomposing Temperature Extremes Errors in CMIP5 and CMIP6 Models - Di Luca, Alejandro; Pitman, Andrew J.; de Elía, Ramón (Geophysical Research Letters, 2020)
Abstract We quantify the skill of Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6 models to represent daily temperature extremes. We find CMIP models systematically exaggerate the magnitude of daily temperature anomalies for both cold and hot extremes. We assess the contribution to a daily temperature extreme from four terms: the long‐term mean annual cycle, the diurnal cycle, synoptic variability, and seasonal variability for both cold and hot extremes. These four terms are combined, and the overall performance of individual climate models assessed. This identifies those models that can simulate temperature extremes well and simulate them well for the right reasons. The new error metric shows that increases in horizontal resolution usually lead to a better performance particularly for the coarser resolution models. The CMIP6 improvements relative to CMIP5 are systematic across most land regions and are only partially explained by the increase in horizontal resolution, and other differences must therefore help explain the higher CMIP6 skill. , Key Points CMIP5 and CMIP6 models exaggerate the magnitude of daily temperature anomalies for hot days and cold nights extremes Higher‐resolution models improve the simulation of temperature extremes largely due to better simulation of synoptic scales CMIP6 outperforms the simulation of temperature extremes compared to CMIP5 beyond the benefits given by the higher resolution

Contribution of mean climate to hot temperature extremes for present and future climates - Di Luca, Alejandro; De Elía, Ramón; Bador, Margot; Argüeso, Daniel (Weather and Climate Extremes, 2020)

Investigation of regional climate models’ internal variability with a ten-member ensemble of 10-year simulations over a large domain - Lucas-Picher, Philippe; Caya, Daniel; De Elía, Ramón; Laprise, René (Climate Dynamics, 2008)

Quantifying the overall added value of dynamical downscaling and the contribution from different spatial scales - Di Luca, Alejandro; Argüeso, Daniel; Evans, Jason P.; De Elía, Ramón; Laprise, René (Journal of Geophysical Research: Atmospheres, 2016)
Abstract This study evaluates the added value in the representation of surface climate variables from an ensemble of regional climate model (RCM) simulations by comparing the relative skill of the RCM simulations and their driving data over a wide range of RCM experimental setups and climate statistics. The methodology is specifically designed to compare results across different variables and metrics, and it incorporates a rigorous approach to separate the added value occurring at different spatial scales. Results show that the RCMs' added value strongly depends on the type of driving data, the climate variable, and the region of interest but depends rather weakly on the choice of the statistical measure, the season, and the RCM physical configuration. Decomposing climate statistics according to different spatial scales shows that improvements are coming from the small scales when considering the representation of spatial patterns, but from the large‐scale contribution in the case of absolute values. Our results also show that a large part of the added value can be attained using some simple postprocessing methods. , Key Points A rigorous methodology that allows evaluating the overall benefits of high‐resolution simulations The most reliable source of added value is the better representation of the spatial variability Substantial added value can also be attained using simple postprocessing methods

Objective Calibration of Regional Climate Models: Application over Europe and North America - Bellprat, Omar; Kotlarski, Sven; Lüthi, Daniel; De Elía, Ramón; Frigon, Anne; Laprise, René; Schär, Christoph (Journal of Climate, 2016)
Abstract An important source of model uncertainty in climate models arises from unconfined model parameters in physical parameterizations. These parameters are commonly estimated on the basis of manual adjustments (expert tuning), which carries the risk of overtuning the parameters for a specific climate region or time period. This issue is particularly germane in the case of regional climate models (RCMs), which are often developed and used in one or a few geographical regions only. This study addresses the role of objective parameter calibration in this context. Using a previously developed objective calibration methodology, an RCM is calibrated over two regions (Europe and North America) and is used to investigate the transferability of the results. A total of eight different model parameters are calibrated, using a metamodel to account for parameter interactions. The study demonstrates that the calibration is effective in reducing model biases in both domains. For Europe, this concerns in particular a pronounced reduction of the summer warm bias and the associated overestimation of interannual temperature variability that have persisted through previous expert tuning efforts and are common in many global and regional climate models. The key process responsible for this improvement is an increased hydraulic conductivity. Higher hydraulic conductivity increases the water availability at the land surface and leads to increased evaporative cooling, stronger low cloud formation, and associated reduced incoming shortwave radiation. The calibrated parameter values are found to be almost identical for both domains; that is, the parameter calibration is transferable between the two regions. This is a promising result and indicates that models may be more universal than previously considered.

Considerations of Domain Size and Large-Scale Driving for Nested Regional Climate Models: Impact on Internal Variability and Ability at Developing Small-Scale Details - Laprise, René; Kornic, Dragana; Rapaić, Maja; Šeparović, Leo; Leduc, Martin; Nikiema, Oumarou; Di Luca, Alejandro; Diaconescu, Emilia; Alexandru, Adelina; Lucas-Picher, Philippe; De Elía, Ramón; Caya, Daniel; et al. (Climate Change, 2012)