Natural versus anthropogenic forcing of variability in prairie hydroclimate

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The objective of the proposed research program is to advance our understanding of the modes and forcing of hydroclimatic variability in the past and near future in Canada's western interior. Historically, climate extremes in this region have been Canada's most costly natural disasters. The scientific approach will include the statistical analysis of instrumental weather and water records, tree-ring data from more than 165 sites that circumscribe the Prairie Ecozone, and outputs from global and regional climate models. We will improve our tree-ring reconstruction of hydrology and climate by a) monitoring radial growth response to weather variables, b) deriving new climate proxies (wood anatomy, early- and late-wood width and density) from our large tree-ring archive, and c) enhancing the signals of excess and cold season precipitation. The proposed research represents a first attempt in western North American to link xylem phenology (xylogenesis) and dendroclimatology. Another innovation is blending data from climate proxies and models, enabling us to interpret the modes of hydroclimatic variability expressed across our tree-ring network in relation to model simulations of the regional hydro-climatology, and the large-scale forcing of climate variability (teleconnections). The paleo-climatic perspective provides significant context for the detection and interpretation of emerging trends in short instrumental records that fall within oscillations of the hydroclimate. Our work has various applications in the fields of climate change science, statistical hydrology and water resource management, with opportunities for collaboration with natural scientists and engineers, and with social scientists investigating the reaction of communities and governance institutions to climate variability and change. The proposed research program is therefore novel in terms of advancing climate science while delivering findings (e.g. historical and projected probability distributions for drought and excessive moisture) such that they can inform decision making to prevent or limit adverse impacts of climate change.