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Extreme hot spells can have significant impacts on human society and ecosystems, and therefore it is important to assess how these extreme events will evolve in a changing climate. In this study, the impact of climate change on hot days, hot spells, and heat waves, over 10 climatic regions covering Canada, based on 11 regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program for the June to August summer period is presented. These simulations were produced with six RCMs driven by four Atmosphere-Ocean General Circulation Models (AOGCM), for the A2 emission scenario, for the current 1970-1999 and future 2040-2069 periods. Two types of hot days, namely HD-1 and HD-2, defined respectively as days with only daily maximum temperature (Tmax) and both Tmax and daily minimum temperature (Tmin) exceeding their respective thresholds (i.e., period-of-record 90th percentile of Tmax and Tmin values), are considered in the study. Analogous to these hot days, two types of hot spells, namely HS-1 and HS-2, are identified as spells of consecutive HD-1 and HD-2 type hot days. In the study, heat waves are defined as periods of three or more consecutive days, with Tmax above 32 °C threshold. Results suggest future increases in the number of both types of hot days and hot spell events for the 10 climatic regions considered. However, the projected changes show high spatial variability and are highly dependent on the RCM and driving AOGCM combination. Extreme hot spell events such as HS-2 type hot spells of longer duration are expected to experience relatively larger increases compared to hot spells of moderate duration, implying considerable heat related environmental and health risks. Regionally, the Great Lakes, West Coast, Northern Plains, and Maritimes regions are found to be more affected due to increases in the frequency and severity of hot spells and/or heat wave characteristics, requiring more in depth studies for these regions to facilitate appropriate adaptation measures. [ABSTRACT FROM AUTHOR]

During the 1970s, Laguna Mar Chiquita (Argentina) experienced a dramatic hydroclimatic anomaly, with a substantial rise in its level. Precipitations are the dominant driving factor in lake level fluctuations. The present study investigates the potential role of remote forcing through global sea surface temperature (SST) fields in modulating recent hydroclimatic variability in Southeastern South America and especially over the Laguna Mar Chiquita region. Daily precipitation and temperature are extracted from a multi-member LMDz atmospheric general circulation model (AGCM) ensemble of simulations forced by HadISST1 observed time-varying global SST and sea-ice boundary conditions from 1950 to 2005. The various members of the ensemble are only different in their atmospheric initial conditions. Statistical downscaling (SD) is used to adjust precipitation and temperature from LMDz ensemble mean at the station scale over the basin. A coupled basin-lake hydrological model ( cpHM) is then using the LMDz-downscaled (LMDz-SD) climate variables as input to simulate the lake behavior. The results indicate that the long-term lake level trend is fairly well depicted by the LMDz-SD- cpHM simulations. The 1970s level rise and high-level conditions are generally well captured in timing and in magnitude when SST-forced AGCM-SD variables are used to drive the cpHM. As the LMDz simulations are forced solely with the observed sea surface conditions, the global SST seems to have an influence on the lake level variations of Laguna Mar Chiquita. As well, this study shows that the AGCM-SD- cpHM model chain is a useful approach for evaluating long-term lake level fluctuations in response to the projected climate changes. [ABSTRACT FROM AUTHOR]

Sea-ice cover over the Hudson Bay (HB) exhibits large variability in the freeze-up season normally starting in November. Its influence on the climate over eastern Canada has been studied with the Canadian Regional Climate Model (CRCM) in three steps. First, a 30-year continuous simulation from 1970 to 1999 was performed as a control run to evaluate the simulated climate variability over eastern Canada, in particularly variability associated with the North Atlantic oscillation (NAO). Then, 50 additional 1 month experiments were performed with modified sea-surface conditions prescribed over the HB. These integrations allowed us to quantify the contribution of HB sea-ice anomalies versus large scale NAO atmospheric variability (as defined by prescribed lateral boundary conditions) in inducing climate variability over eastern Canada. Results show that the NAO is the dominant factor controlling climate variability over eastern Canada. The contribution of HB sea-ice anomalies is significant only in the immediate coastal region. Under the influence of different phases of NAO, HB sea-ice anomalies do co-vary with temperature and precipitation anomalies downstream of the HB over eastern Canada. The ultimate cause of this co-variability is NAO variability which forces variability in both HB sea-ice cover as well as temperature/precipitation over eastern Canada. [ABSTRACT FROM AUTHOR]

This work is a first step in the analysis of uncertainty sources in the RCM-simulated climate over North America. Three main sets of sensitivity studies were carried out: the first estimates the magnitude of internal variability, which is needed to evaluate the significance of changes in the simulated climate induced by any model modification. The second is devoted to the role of CRCM configuration as a source of uncertainty, in particular the sensitivity to nesting technique, domain size, and driving reanalysis. The third study aims to assess the relative importance of the previously estimated sensitivities by performing two additional sensitivity experiments: one, in which the reanalysis driving data is replaced by data generated by the second generation Coupled Global Climate Model (CGCM2), and another, in which a different CRCM version is used. Results show that the internal variability, triggered by differences in initial conditions, is much smaller than the sensitivity to any other source. Results also show that levels of uncertainty originating from liberty of choices in the definition of configuration parameters are comparable among themselves and are smaller than those due to the choice of CGCM or CRCM version used. These results suggest that uncertainty originated by the CRCM configuration latitude (freedom of choice among domain sizes, nesting techniques and reanalysis dataset), although important, does not seem to be a major obstacle to climate downscaling. Finally, with the aim of evaluating the combined effect of the different uncertainties, the ensemble spread is estimated for a subset of the analysed simulations. Results show that downscaled surface temperature is in general more uncertain in the northern regions, while precipitation is more uncertain in the central and eastern US. [ABSTRACT FROM AUTHOR]