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A procedure is proposed that enables the estimation of natural baseflow in a gauged watershed through analyses of recession curves and stream hydrographs. The analysis results in a surrogate for the recovery level of a watershed after a prolonged drought and allows the medium term prediction of runoff behaviour for water resources management. The method has been applied for the Upper Battle River Watershed in the northern Prairies of Alberta, Canada. Results show that baseflow is extremely low after a multi-year drought (2001 to 2003). The recession index indicates that one year after the climatological end of the drought the integrated watershed storage that usually sustains the baseflow is abnormally low, with associated negative impacts on available water resources. This paper describes the derivation, classification and application of a watershed specific recession index. Results show that the described procedure is relatively simple, reliable and efficient. [ABSTRACT FROM AUTHOR]

Soil quality models developed for ecodistrict polygons (EDP) and the polygons of the soil landscapes of Canada (SLC) to monitor the concentration of soil organic matter require daily climate data as an important input. The objectives of this paper are (i) to provide a method that interpolates the daily station data onto the 894 SLC polygons and 150 EDP in the province of Alberta, Canada, so that the interpolated data fit not only climate mean but also climate variability, especially for the precipitation field, and hence can be used as realistic climate input to soil quality models and (ii) to understand the variability of the Alberta daily climate, such as precipitation frequency. The procedure interpolates the station data onto a dense network of grid points and then averages the gridpoint values inside polygons. The procedure and results for maximum temperature, minimum temperature, and precipitation are reported in detail. The interpolation uses the observed daily data for the period 1 January 1961-31 December 1997 (13 514 days) within the latitude-longitude box (45°-64°N, 116°-124°W). Because the precipitation field can have a short spatial correlation length scale and large variability, a hybrid of the methods of inverse-distance weight and nearest-station assignment is developed for interpolating the precipitation data. This method can reliably calculate not only the number of precipitation days per month, but also the precipitation amount for a day. The temperature field has a long spatial correlation scale, and its data are interpolated by the inverse-distance-weight method. Cross-validation shows that the interpolated results on polygons are accurate and appropriate for soil quality models. The computing algorithm uses all the daily observed climate data; despite that, some stations have a very short time record or only summer records. [ABSTRACT FROM AUTHOR]

Key message: New genotypes of hybrid poplars from theAigeirosandTacamahacasections have great potential for increasing genetic gain from selection. The most promising traits are associated with productivity and resistance toSphaerulina musiva-induced canker while wood density can be selected for secondarily. A minimum age of 8 years is reliable to select fast-growing resistant clones in northern climates. Context: Productivity, wood density, and disease resistance of hybrid poplar clones are important traits when selecting for cultivation at an industrial scale. Aims: We studied 1978 hybrid poplar clones from 63 families, bred from poplars native (Populus balsamifera and Populus deltoides) and non-native to Canada from the Aigeiros and Tacamahaca sections, to improve economically important traits for plantations in northern Alberta. Methods: Genetic parameters for diameter at breast height (DBH), height, resistance to Sphaerulina musiva-induced canker, and wood density were determined up to age 10. Results: A mean annual increment of 16.5 m3 ha−1 year−1 was achieved at age 10 in the best-performing clones. The potential genetic gain for DBH, height, and canker resistance, 37%, 26%, and ~ 13%, respectively, was achieved when selecting the top 10% of the tested clones. The genetic effect for wood density was weak. The age-age genetic correlations identified age eight as a reliable selection age. Conclusion: The new hybrid poplar clones tested exhibited great potential for tree improvement. The next phase of selection should test a reduced number of clones on different site types, identifying stable clones for productivity and resistance, while wood density can be selected for secondarily. In northern regions, a minimum age of 8 years is reliable to select fast-growing resistant clones for commercial deployment. [ABSTRACT FROM AUTHOR]

A reliable climate dataset is the backbone for modelling the essential processes of the water cycle and predicting future conditions. Although a number of gridded climate datasets are available for the North American content which provide reasonable estimates of climatic conditions in the region, there are inherent inconsistencies in these available climate datasets (e.g., spatially and temporally varying data accuracies, meteorological parameters, lengths of records, spatial coverage, temporal resolution, etc.). These inconsistencies raise questions as to which datasets are the most suitable for the study area and how to systematically combine these datasets to produce a reliable climate dataset for climate studies and hydrological modelling. This study suggests a framework called the REFerence Reliability Evaluation System (REFRES) that systematically ranks multiple climate datasets to generate a hybrid climate dataset for a region. To demonstrate the usefulness of the proposed framework, REFRES was applied to produce a historical hybrid climate dataset for the Athabasca River basin (ARB) in Alberta, Canada. A proxy validation was also conducted to prove the applicability of the generated hybrid climate datasets to hydrologic simulations. This study evaluated five climate datasets, including the station-based gridded climate datasets ANUSPLIN (Australia National University Spline), Alberta Township, and the Pacific Climate Impacts Consortium's (PCIC) PNWNAmet (PCIC NorthWest North America meteorological dataset), a multi-source gridded dataset (Canadian Precipitation Analysis; CaPA), and a reanalysis-based dataset (North American Regional Reanalysis; NARR). The results showed that the gridded climate interpolated from station data performed better than multi-source- and reanalysis-based climate datasets. For the Athabasca River basin, Township and ANUSPLIN were ranked first for precipitation and temperature, respectively. The proxy validation also confirmed the utility of hybrid climate datasets in hydrologic simulations compared with the other five individual climate datasets investigated in this study. These results indicate that the hybrid climate dataset provides the best representation of historical climatic conditions and, thus, enhances the reliability of hydrologic simulations. [ABSTRACT FROM AUTHOR]

Research into the potential use of microalgae to produce biofuels is receiving significant attention. In the cold climates of countries like Canada, algae cultivation in open raceway pond (ORP) systems is limited to a short period of the year when pond surface water temperatures and ambient light conditions enable optimal culture growth. In this study we develop techno‐economic assessment models to predict, evaluate, and compare the techno‐economic results from three autotrophic algae cultivation scenarios to produce algae biomass. The first is a modeled ORP site located in the southern USA, which has a minimum biomass selling price (MBSP) for algae of $541 tonne−1 (T−1). The second scenario models an identical ORP system co‐located at a site near Fort Saskatchewan, a northern city in the province of Alberta, Canada. The resulting MBSP is $1288 T−1. A third scenario models a photobioreactor (PBR) cultivation system co‐located at the same northern Alberta site and shows algae production with an MBSP of $550 T−1. Each system is scaled to produce 2000 T day−1 ash‐free dry weight (AFDE) algae biomass. The study concludes that PBR systems deployed at this scale have the potential to reduce production costs significantly ($ T−1) compared to similarly sited ORP systems in Canada, despite climatic factors and high initial capital costs associated with PBR construction. Furthermore, the modeled PBR system required 0.3% of the water required by the ORP cultivation platforms (153 × 103 versus 59 527 × 103 m3) and 0.04% of the land (32 versus. 82 038 ha). © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]

Ecological analyses often incorporate high‐resolution environmental data to capture species‐environment relationships in modelling applications, and downscaled climate data are increasingly being used for such analyses. While such data products provide high precision, the accuracy of these data is seldom directly tested. Consequently, introduced bias from downscaling algorithms may propagate through analyses that incorporate these data products. Here, we utilize data from the Foothills Climate Array (FCA), a mesoscale grid of 232 weather stations in the prairies and eastern slopes of the Rocky Mountains in southern Alberta, Canada, to evaluate several publicly available downscaled climate products. We consider daily, monthly, and annual records for a suite of temperature and humidity variables. The FCA data are ideal to evaluate climate downscaling because they contain multi‐year observations and cover a range of topographic conditions, from flat prairie grass‐ and croplands to mountainous terrain. We find that the downscaling algorithms improve the accuracy of climate variables over simple interpolations of low‐resolution data, but errors are often large at validation locations (e.g., several °C for temperature variables), and downscaled datasets show notable elevational and seasonal bias for all variables. A bias adjustment analysis demonstrates that such bias can be greatly reduced with relatively simple regression‐based models, even when only a small subset of observational data are used, provided they cover a relatively large spread of elevations. We discuss our findings in the context of climate change and ecological modelling and make general recommendations for consumers of downscaled climate data products. [ABSTRACT FROM AUTHOR]

In June 2013, excessive rainfall associated with an intense weather system triggered severe flooding in southern Alberta, which became the costliest natural disaster in Canadian history. This article provides an overview of the climatological aspects and large-scale hydrometeorological features associated with the flooding event based upon information from a variety of sources, including satellite data, upper air soundings, surface observations and operational model analyses. The results show that multiple factors combined to create this unusually severe event. The event was characterized by a slow-moving upper level low pressure system west of Alberta, blocked by an upper level ridge, while an associated well-organized surface low pressure system kept southern Alberta, especially the eastern slopes of the Rocky Mountains, in continuous precipitation for up to two days. Results from air parcel trajectory analysis show that a significant amount of the moisture originated from the central Great Plains, transported into Alberta by a southeasterly low level jet. The event was first dominated by significant thunderstorm activity, and then evolved into continuous precipitation supported by the synoptic-scale low pressure system. Both the thunderstorm activity and upslope winds associated with the low pressure system produced large rainfall amounts. A comparison with previous similar events occurring in the same region suggests that the synoptic-scale features associated with the 2013 rainfall event were not particularly intense; however, its storm environment was the most convectively unstable. The system also exhibited a relatively high freezing level, which resulted in rain, rather than snow, mainly falling over the still snow-covered mountainous areas. Melting associated with this rain-on-snow scenario likely contributed to downstream flooding. Furthermore, above-normal snowfall in the preceding spring helped to maintain snow in the high-elevation areas, which facilitated the rain-on-snow event. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Surface and upper-air analyses from the ECMWF Tropical Ocean Global Atmosphere (TOGA) dataset are used to construct a climatology of 177 Alberta clippers over 15 boreal cold seasons (October–March) from 1986/87 to 2000/01. The Alberta clipper (hereafter simply clipper) occurs most frequently during December and January and substantially less frequently during October and March. These cyclones generally move southeastward from the lee of the Canadian Rockies toward or just north of Lake Superior before progressing eastward into southeastern Canada or the northeastern United States, with less than 10% of the cases in the climatology tracking south of the Great Lakes. Characteristics of the structure and evolution of clippers during a 36-h period leading up to departure of the cyclone from the lee of the Canadian Rockies and a 60-h period after departure as the cyclone traverses central and eastern North America are examined through composite analyses. Over the course of the predeparture period, a cyclone over the Gulf of Alaska approaches the west coast of North America, and through its interaction with the mountainous terrain of western North America spawns a surface lee trough, characterized by a thermal ridge at 850 hPa, to the east of the Canadian Rockies. This thermal ridge dampens considerably as the composite clipper moves into central North America away from the immediate lee of the Canadian Rockies. The composite clipper system evolves from a lee cyclone with its nonclassical thermal structure to a more classically structured midlatitude cyclone as it moves through central and eastern North America largely as a result of rotation of the low-level thermal gradient and the increasing westward tilt with height of the composite clipper over the last 36 h of the postdeparture period. The thermal gradient rotation is dynamically linked to convergence of the along-isentrope component of the Q vector and thus to the ascent that sustains the clipper and creates some of its characteristic sensible weather elements. Such dynamical forcing is a direct consequence of the persistent westward displacement of the 500-hPa vorticity maximum with respect to the composite clipper sea level pressure minimum that characterizes the postdeparture period. [ABSTRACT FROM AUTHOR]

Tree-ring based mass balance reconstructions developed for Peyto Glacier, Alberta, Canada are compared with measured conditions in the Pacific Ocean over the last century and, using reconstructions of Pacific climate indices, over the past ∼ 300 years, at interannual and decadal–interdecadal timescales. Tree-ring reconstructed winter balance totals at Peyto Glacier in La Niña, negative Pacific Decadal Oscillation (PDO) and La Niña/negative PDO years significantly exceed those in El Niño, positive PDO and El Niño/positive PDO years, respectively. The same phase pairings of reconstructed summer mass balance do not differ significantly. These findings confirm those seen in the measured mass balance records and shorter (100 years) tree-ring and instrumental climate record-based reconstructions, suggesting similar relationships have existed over the past ∼ 300 years. Maps showing the regression of Pacific sea surface temperatures (SSTs) on the seasonal mass balance series indicates that both winter and, albeit more weakly, summer mass balance series are related to ENSO-like patterns of SST variability in the Pacific Ocean at both interannual and interdecadal timescales. [ABSTRACT FROM AUTHOR]