Investigating added value of regional climate modeling in North American winter storm track simulations - Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G. (Climate Dynamics, 2018)
Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981–2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal ‘seriality’, as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.
Keywords: Gachon_Philippe

Multisite statistical downscaling model for daily precipitation combined by multivariate multiple linear regression and stochastic weather generator - Jeong, D. I.; St-Hilaire, A.; Ouarda, T. B. M. J.; Gachon, P. (Climatic Change, 2012)
This study provides a multi-site hybrid statistical downscaling procedure combining regression-based and stochastic weather generation approaches for multisite simulation of daily precipitation. In the hybrid model, the multivariate multiple linear regression (MMLR) is employed for simultaneous downscaling of deterministic series of daily precipitation occurrence and amount using large-scale reanalysis predictors over nine different observed stations in southern Québec (Canada). The multivariate normal distribution, the first-order Markov chain model, and the probability distribution mapping technique are employed for reproducing temporal variability and spatial dependency on the multisite observations of precipitation series. The regression-based MMLR model explained 16 % ~ 22 % of total variance in daily precipitation occurrence series and 13 % ~ 25 % of total variance in daily precipitation amount series of the nine observation sites. Moreover, it constantly over-represented the spatial dependency of daily precipitation occurrence and amount. In generating daily precipitation, the hybrid model showed good temporal reproduction ability for number of wet days, cross-site correlation, and probabilities of consecutive wet days, and maximum 3-days precipitation total amount for all observation sites. However, the reproducing ability of the hybrid model for spatio-temporal variations can be improved, i.e. to further increase the explained variance of the observed precipitation series, as for example by using regional-scale predictors in the MMLR model. However, in all downscaling precipitation results, the hybrid model benefits from the stochastic weather generator procedure with respect to the single use of deterministic component in the MMLR model.
Keywords: Gachon_Philippe

West African monsoon intraseasonal activity and its daily precipitation indices in regional climate models: diagnostics and challenges - Poan, E. D.; Gachon, P.; Dueymes, G.; Diaconescu, E.; Laprise, R.; Seidou Sanda, I. (Climate Dynamics, 2016)
The West African monsoon intraseasonal variability has huge socio-economic impacts on local populations but understanding and predicting it still remains a challenge for the weather prediction and climate scientific community. This paper analyses an ensemble of simulations from six regional climate models (RCMs) taking part in the coordinated regional downscaling experiment, the ECMWF ERA-Interim reanalysis (ERAI) and three satellite-based and observationally-constrained daily precipitation datasets, to assess the performance of the RCMs with regard to the intraseasonal variability. A joint analysis of seasonal-mean precipitation and the total column water vapor (also called precipitable water—PW) suggests the existence of important links at different timescales between these two variables over the Sahel and highlights the relevance of using PW to follow the monsoon seasonal cycle. RCMs that fail to represent the seasonal-mean position and amplitude of the meridional gradient of PW show the largest discrepancies with respect to seasonal-mean observed precipitation. For both ERAI and RCMs, spectral decompositions of daily PW as well as rainfall show an overestimation of low-frequency activity (at timescales longer than 10 days) at the expense of the synoptic (timescales shorter than 10 days) activity. Consequently, the effects of the African Easterly Waves and the associated mesoscale convective systems are substantially underestimated, especially over continental regions. Finally, the study investigates the skill of the models with respect to hydro-climatic indices related to the occurrence, intensity and frequency of precipitation events at the intraseasonal scale. Although most of these indices are generally better reproduced with RCMs than reanalysis products, this study indicates that RCMs still need to be improved (especially with respect to their subgrid-scale parameterization schemes) to be able to reproduce the intraseasonal variance spectrum adequately.
Keywords: Gachon_Philippe