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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]

ABSTRACT Spatial structures of hourly precipitation fields were studied from three simulations of the Canadian Regional Climate Model ( CRCM) and observations of the National Centers for Environmental Prediction ( NCEP) Stage IV analysis. Each precipitation structure, defined as a contiguous area of precipitation above a given threshold, was analysed through geometric characteristics (position, area, major and minor axes, eccentricity, orientation) and intensity characteristics (volume, mean and maximum intensities, precipitation distribution within the structure) for 16 climatic regions covering North America. While providing new insights on the spatial facet of precipitation, this study aimed to: (1) assess the performance of the CRCM to reproduce observed precipitation structures and (2) analyse the changes in precipitation structures between historical (1961-1990) and future (2071-2100) periods. In addition, the effect of internal variability was investigated using two CGCM-driven CRCM simulations. In order to assess the CRCM performance, a reanalysis-driven CRCM simulation was first compared with observations and then with CGCM-driven CRCM simulations. Results suggest that reanalysis-driven CRCM precipitation structures displayed intensities spatially more homogeneous than observed ones for the central and eastern United States and showed significantly lower precipitation volumes, intensities and areas. However, annual cycles of characteristic values were well reproduced. In addition, CGCM-driven CRCM showed significantly lower precipitation volumes and intensities during summer months for southeastern regions when compared to reanalysis-driven CRCM. Precipitation structures were also larger and shifted further north. Boundary conditions seemed to influence mainly central and eastern regions of North America. In future climate, results suggest more convective summer precipitations for central and eastern regions (increases in volumes, intensities and heterogeneity of structures), drier spring and summer conditions for southwestern regions (decreases in numbers of structures), wetter winter and spring conditions for northern regions (increases in numbers of structures) and wetter autumn conditions for southeastern regions (increases in volumes and intensities). [ABSTRACT FROM AUTHOR]

The snow treatment becomes an important component of Soil and Water Assessment Tool (SWAT)'s hydrology when spring flows are dominated by snow melting. However, little is known about SWAT's snow hydrology performance because most studies using SWAT were conducted in rainfall-driven catchments. To fill this gap, the present study aims to evaluate the ability of SWAT in simulating snow-melting-dominated streamflow in the Outardes Basin in Northern Quebec. SWAT performance in simulating snowmelt is evaluated against observed streamflow data and compared to simulations from the operationally used Streamflow Synthesis and Reservoir Regulation (SSARR) model over that catchment. The SWAT 5-year calibration showed a satisfactory performance at the daily and seasonal time scales with low volume biases. The SWAT validation was conducted over two (17-year and 15-year) periods. Performances were similar to the calibration period in simulating the daily and seasonal streamflows again with low model biases. The spring-snowmelt-generated peak flow was accurately simulated by SWAT both in magnitude and timing. When SWAT's results are compared to SSARR, similar performances in simulating the daily discharges were observed. SSARR simulates more accurately streamflow generated at the snowmelt onset whereas SWAT better predicts streamflow in summer, fall and winter. SWAT provided reasonable streamflow simulations for our snow-covered catchment, but refinement of the process-driven baseflow during the snowmelt onset could improve spring performances. Therefore, SWAT becomes an attractive tool for evaluating water resources management in Nordic environments when a distributed model is preferred or when water quality information (e.g. temperature) is required. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Annual maxima (AM) series of precipitation from 15 simulations of the North American Regional Climate Change Assessment Program (NARCCAP) have been analysed for gridpoints covering Canada and the northern part of United States. The NARCCAP Regional Climate Models' simulations have been classified into the following three groups based on the driving data used at the RCMs boundaries: (1) NCEP (6 simulations); (2) GCM-historical (5 simulations); and (3) GCM-future (4 simulations). Historical simulations are representative of the 1968-2000 period while future simulations cover the 2041-2070 period. A reference common grid has been defined to ease the comparison. Multi-model average intensities of AM precipitation of 6-, 12-, 24-, 72-, and 120-h for 2-, 5-, 10-, and 20-year return periods have been estimated for each simulation group. Comparison of results from NCEP and GCM-historical groups shows good overall agreement in terms of spatial distribution of AM intensities. Comparison of GCM-future and GCM-historical groups clearly shows widespread increases with median relative changes across all gridpoints ranging from 12 to 18% depending on durations and return periods. Fourteen Canadian climatic regions have been used to define regional projections and average regional changes in intense precipitation have been estimated for each duration and return period. Uncertainties on these regional values, resulting from inter-model variability, were also estimated. Results suggest that inland regions (e.g. Ontario and more specifically Southern Ontario, the Prairies, Southern Quebec) will experience the largest relative increases in AM intensities while coastal regions (e.g. Atlantic Provinces and the West Coast) will experience the smallest ones. These projections are most valuable inputs for the assessment of future impact of climate change on water infrastructures and the development of more efficient adaptation strategies. Copyright © 2011 Royal Meteorological Society [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]

In the present paper, a 5-yr baseline integration for the period 1987–91 was carried out over a Pan-Canadian domain to validate the performance of the third-generation Canadian Regional Climate Model (CRCM). The CRCM simulated the large-scale circulation over North America well; it also correctly captured the seasonal variability of surface temperature and reproduced the winter precipitation over North America realistically. However, the CRCM systematically overestimated the summer precipitation over the continent when compared with the observed values. Extensive experiments have been conducted to trace down the sources of error of summer precipitation. Particular attention has been given to the water-vapor-related physical parameterization processes such as the mass flux convection scheme in the CRCM. Experiments involving spectral nudging of the specific humidity toward the values of large-scale driving data enabled the authors to link overestimation with abundant water vapor accumulated in the lower boundary layer resulting from an excessive amount of moisture stored in the soil. A strong boundary layer mixing process from the third generation of the Canadian Atmospheric General Circulation Model was then implemented into the CRCM along with an adjustment to the soil water holding capacity. A final analysis of a 14-month experiment showed that these modifications significantly improved the simulation of summer precipitation over North America without adversely affecting the simulation of winter precipitation. [ABSTRACT FROM AUTHOR]