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College of Arts and Science

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Browsing College of Arts and Science by Author "Arnal, Louise"

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    Hybrid forecasting: blending climate predictions with AI models
    (Copernicus Publications [Commercial Publisher], European Geosciences Union [Society Publisher], 2023) Slater, Louise; Arnal, Louise; Boucher, Marie-Amélie; Chang, Annie Y.-Y.; Moulds, Simon; Murphy, Conor; Nearing, Grey; Shalev, Guy; Shen, Chaopeng; Speight, Linda; Villarini, Gabriele; Wilby, Robert L.; Wood, Andrew; Zappa, Massimiliano
    Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine learning) methods to harness and integrate a broad variety of predictions from dynamical, physics-based models – such as numerical weather prediction, climate, land, hydrology, and Earth system models – into a final prediction product. They are recognized as a promising way of enhancing the prediction skill of meteorological and hydroclimatic variables and events, including rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. Hybrid forecasting methods are now receiving growing attention due to advances in weather and climate prediction systems at subseasonal to decadal scales, a better appreciation of the strengths of AI, and expanding access to computational resources and methods. Such systems are attractive because they may avoid the need to run a computationally expensive offline land model, can minimize the effect of biases that exist within dynamical outputs, benefit from the strengths of machine learning, and can learn from large datasets, while combining different sources of predictability with varying time horizons. Here we review recent developments in hybrid hydroclimatic forecasting and outline key challenges and opportunities for further research. These include obtaining physically explainable results, assimilating human influences from novel data sources, integrating new ensemble techniques to improve predictive skill, creating seamless prediction schemes that merge short to long lead times, incorporating initial land surface and ocean/ice conditions, acknowledging spatial variability in landscape and atmospheric forcing, and increasing the operational uptake of hybrid prediction schemes.
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    The Impact of Meteorological Forcing Uncertainty on Hydrological Modeling: A Global Analysis of Cryosphere Basins
    (Wiley [Commercial Publisher], American Geophysical Union [Client Organisation], 2023) Tang, Guoqiang; Clark, Martyn; Knoben, Wouter; Liu, Hongli; Gharari, Shervan; Arnal, Louise; Beck, Hylke; Wood, Andrew W.; Newman, Andrew J.; Papalexiou, Simon Michael
    Meteorological forcing is a major source of uncertainty in hydrological modeling. The recent development of probabilistic large-domain meteorological data sets enables convenient uncertainty characterization, which however is rarely explored in large-domain research. This study analyzes how uncertainties in meteorological forcing data affect hydrological modeling in 289 representative cryosphere basins by forcing the Structure for Unifying Multiple Modeling Alternatives (SUMMA) and mizuRoute models with precipitation and air temperature ensembles from the Ensemble Meteorological Data set for Planet Earth (EM-Earth). EM-Earth probabilistic estimates are used in ensemble simulation for uncertainty analysis. The results reveal the magnitude, spatial distribution, and scale effect of uncertainties in meteorological, snow, runoff, soil water, and energy variables. There are three main findings. (a) The uncertainties in precipitation and temperature lead to substantial uncertainties in hydrological model outputs, some of which exceed 100% of the magnitude of the output variables themselves. (b) The uncertainties of different variables show distinct scale effects caused by spatial averaging or temporal averaging. (c) Precipitation uncertainties have the dominant impact for most basins and variables, while air temperature uncertainties are also nonnegligible, sometimes contributing more to modeling uncertainties than precipitation uncertainties. We find that three snow-related variables (snow water equivalent, snowfall amount, and snowfall fraction) can be used to estimate the impact of air temperature uncertainties for different model output variables. In summary, this study provides insight into the impact of probabilistic data sets on hydrological modeling and quantifies the uncertainties in cryosphere basin modeling that stem from the meteorological forcing data.
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    The Virtual Water Gallery: Changing Attitudes through Art
    (European Geosciences Union, 2023) Arnal, Louise; Clark, Martyn P.; Dumanski, Stacey
    Water is life. Water-related challenges, such as droughts, floods, wildfires, water quality degradation, permafrost thaw and glacier melt, exacerbated by climate change, affect everyone. Yet, it is challenging to communicate science on difficult, highly volatile topics such as water and climate change. Conceptualizing water-related environmental and social issues in novel ways, with engagement between diverse audiences may lead to comprehensive solutions to these complex challenges. Art can be a catalyst in the co-creation of new knowledge for the benefit of society. The Virtual Water Gallery (VWG) is a transdisciplinary science and art project of the Global Water Futures (GWF) program. Launched in 2020, the VWG aims to provide a collaborative space for dialogues between water experts, artists, and the wider public, to explore water challenges. As part of this project, 13 artists representing women’s, men’s and Indigenous voices across Canada were paired with teams of GWF scientists to co-explore specific water challenges in various Canadian ecoregions and communities. These collaborations led to the co-creation of artworks exhibited online on the VWG (www.virtualwatergallery.ca) in 2021. The VWG recently came to life in 2022 with an in-person exhibition in Canmore, Alberta, Canada. Surveys were developed to capture changes in perspectives regarding climate change and water challenges through this art-science exhibit. Participants of the VWG (artists and scientists), visitors to the online gallery, and visitors to the in-person exhibition in Canmore were all invited to take part in those surveys. The preliminary results from the surveys suggest that participants experienced changes in behaviour regarding water-related climate change mitigation, and that the degree of change depends on factors such as age, income and lived experience (i.e., floods and droughts). The results help elucidate how art viewers engage with art based on science and how science messages can be more effectively communicated through art.