Spatial and temporal characteristics of historical surface climate over the Northwest Territories, Canada

Climate change is putting many of the Northwest Territories (NWT) ecosystems, its people and animal populations at risk due to accelerated warming, permafrost thaw, and changing precipitation regimes. As the NWT continues to warm, at disproportionately higher rates when compared to the rest of Canada, threats to the stability of NWT’s ecosystems are expected to increase. Consequently, understanding how climate warming has changed historically and its implications on natural ecosystems requires point-to-region-specific, long-term climatic data to elucidate important drivers of observed changes relevant to decision makers at community, Indigenous, Territorial and Federal government levels. However, in situ climate data are limited temporally and spatially across the NWT. Hence, the overarching goal of this research is to enhance and improve the understanding of historical surface climate variables trends and patterns (air temperature, precipitation, and shortwave radiation) and its implications at local and regional scales in the continental NWT by using interpolated, reanalysis and remote sensing climate data. Gridded climate datasets such as interpolated and reanalysis data, can provide reliable estimates for in situ observations to compensate for data scarcity, but it is critical that researchers understand how biases in these datasets can impact runoff simulation in the NWT. Thus, the objective of this dissertation was to assess the similarity between daily in situ station observations and three gridded datasets (ANUSPLIN, ERA-Interim and MERRA-2) from 1980 to 2013 to support hydrological modelling in the NWT subarctic. The ANUSPLIN maximum and minimum temperature at eight locations aligned closely to the corresponding in situ observations and had mean daily biases of less than 0.58°C and 1.33°C, respectively. Precipitation estimates showed that the alternative datasets captured year-to-year variability, but large seasonal biases mainly during spring and summer were evident when precipitation magnitudes were estimated. In addition, this study used gridded data as a substitute for in situ observations in the Cold Regions Hydrological Model (CRHM) to simulate runoff. Simulated runoff generated when using ANUSPLIN and ERA-Interim data as inputs in CRHM captures the timing and magnitude of freshet and baseflow generally well at Scotty Creek. This study suggests that gridded datasets can provide reasonable estimates of in situ climate data in data sparse regions and reinforced that the accuracy in representing in situ observations over the NWT improves as the spatial resolution of interpolated dataset increases. This research also highlighted that when comparing datasets, it is important use multiple metrics and graphical methods to discern systematic biases. The presence of oceanic-atmospheric teleconnections patterns can influence weather patterns in northern regions which may lead to an increase in climate related wildland fires. The impact of the Arctic Dipole (AD) anomaly, a northern atmospheric teleconnection, on NWT’s surface climate has not been explored. Hence, the second objective of this dissertation used the ANUSPLIN dataset to assess the effects of the AD anomaly on local climate (air temperature, precipitation, and snowmelt) during a 66-year period (1950-2015). For all seasons, from 1950 to 2015, the occurrence of 64 strong positive and 56 strong negative AD modes were identified. The AD pattern revealed significant year-to-year fluctuation, with more frequent strong negative modes observed in the 2000s. In summer, when AD is in its strong negative mode, there is increased variance in the range of local air temperature, which is amplified in the southern, lake and foothill regions of the Taiga Plains. During strong positive AD modes, local air temperature anomalies increased (\u3e0.8°C) when compared to long-term mean temperature during summer months. Positive AD modes also lead to earlier commencement of snowmelt by an average of 3 to 5 days. The air temperature/snowmelt onset north–south amplification to the AD is linked to the position and intensity of the geopotential heights ridge axis over the continental NWT. A weak correlation was found between the AD and seasonal precipitation despite high correlation association between the AD and local air temperature in summer. Finally, the spatiotemporal patterns of incoming surface shortwave radiation (SSR) were analysed and quantified for the continental NWT to enhance understanding of northern ecosystems energy balance that are undergoing environmental changes. The third objective of this dissertation addressed this knowledge gap by assessing annual and seasonal trends in SSR receipt and to explore relationship between SSR and lake surface water temperature (LSWT) during the warm season. Consequently, the quantity of SSR that reaches Earth’s surface may vary. In this study, it is observed that SSR trends display a significant temporal and spatial dependency on NWT’s ecozones between 1980 and 2020. The annual mean SSR since 1980 decreased by ~0.8 Wm-2decade-1 in the Taiga Plains and Northern Arctic ecozones, with mixture of increasing and decreasing trends in both Taiga Shield and Southern Arctic ecozones. Seasonally, SSR decreased significantly in the summer since 1980 over the majority of the Taiga Plains ecozone, with a reduction rate that ranged between 0.6 and 14.6 Wm-2decade-1. The LSWT in small lakes was positively associated with SSR, while the LSWT in medium and large lakes showed a mix of positive and negative correlation coefficients. The linkage between total cloud cover and SSR in the NWT was largely negative for spring, summer and autumn seasons, with the Taiga Plains ecozone displaying the largest negative correlation. Long-term changes in SSR in the NWT will have an impact on the seasonal and annual energy balance of the region\u27s lakes. The impact of SSR changes on lake energy balances will have a wide range of consequences, particularly for NWT communities that rely on lakes for their transportation networks. These networks are already being adversely impacted by climate change-driven alterations in warming lake ice phenology. The collective findings of this study demonstrate the feasibility of using gridded and remote sensing datasets to characterize historical changes in local and regional weather and climate, building an understanding of northern climatology and providing best estimates of long-term trends with implications for ecosystem change in the future, such as increased rates of shrubification and frequency of wildland fires. In the absence of consistent in situ climate data, these gridded and remote sensing datasets aid our understanding of the physical links between climate change and northern ecosystems, which must be accounted for in forecast models used to predict future hydroclimate scenarios and to provide enhance climate services in northern regions. Improved understanding of how local and regional climate has changed in the NWT will inform policymakers in their efforts to develop and improve climate adaptation and mitigation policies in local communities across the territory

Global trends in timing and rates of chlorophyll-a increase in cold-temperate and temperate lakes

Associated publication: https://doi.org/10.5194/essd-14-5139-2022Lakes are key ecosystems within the global biogeosphere. However, the environmental controls on the biological productivity of lakes – including surface temperature, ice phenology, nutrient loads, and mixing regime – are increasingly altered by climate warming and land-use changes. To better characterize global trends in lake productivity, we assembled a dataset on chlorophyll-a concentrations as well as associated water quality parameters and surface solar radiation for temperate and cold-temperate lakes experiencing seasonal ice cover. We developed a method to identify periods of rapid net increase of in situ chlorophyll-a concentrations from time series data and applied it to data collected between 1964 and 2019 across 343 lakes located north of 40◦ . The data show that the spring chlorophyll-a increase periods have been occurring earlier in the year, potentially extending the growing season and increasing the annual productivity of northern lakes. The dataset on chlorophyll-a increase rates and timing can be used to analyze trends and patterns in lake productivity across the northern hemisphere or at smaller, regional scales. We illustrate some trends extracted from the dataset and encourage other researchers to use the open dataset for their own research questions. The PCI dataset and additional data files can be openly accessed at the Federated Research Data Repository at https://doi.org/10.20383/102.0488 (Adams et al., 2021).Global Water Futures (GWF), Lake Futures project || Canada First Research Excellence Fund (CFREF

Unlocking the Power of GWF Research: Introducing an AI-Driven Portal for Enhanced Accessibility and User-Friendly Experience!

This research was undertaken thanks, in part, with support from the Global Water Futures Program funded by the Canada First Research Excellence Fund (CFREF)The Canada First Research Excellence Fund provided CDN $77.8 million to the Global Water Futures Programme (GWF) to generate practical scientific knowledge on how to forecast, prepare for, and manage water futures in Canada, given the anticipated risks associated with climate change. Between 2017 and 2021, GWF has produced thousands of research outputs including peer-reviewed publications, books chapters, articles in media, conference presentations, and datasets. To make these findings more accessible, we are leveraging artificial intelligence and other open access computing resources to create a user-friendly, searchable, and accessible one stop shop interface. This research tested the feasibility of adapting the ACL Anthology Network, a popular resource in the field of Computational Linguistics, to promote GWF peer-reviewed publications, as this is one key category of research outputs. The GWF anthology output consists of over 1000 peer-reviewed publications, each accessible via a unique identifier, and includes various statistics about individual authors and publications. Our team also utilized cutting-edge technology to develop a highly efficient publication clustering project. Our approach involved implementing a BERT-based model to generate embeddings for each publication using both the title and abstract of the publication. This allowed us to capture both the broad themes and specific details of each piece of work, ensuring that the clustering model would have a robust set of data to work with. In addition, we utilized a k-means clustering model to group together similar publications based on their subject matter, making it easier for users to find articles and papers that are relevant to their interests. With this tool, users can easily filter through publications on a particular topic, saving them valuable time and effort. By leveraging these open sourced resources, we hope to share our unique approach towards publication accessibility with other large interdisciplinary projects, who could replicate this approach, thereby saving significant time and resources. This approach is particularly relevant given the significant investment in such projects by Canada and other countries. By adapting these techniques, researchers and project managers can build on the success of past projects and make further advancements in data accessibility and open access resources.Global Water Future

Rescuing Historical Climate Observations to Support Hydrological Research: A Case Study of Solar Radiation Data

The acceleration of climate change and its impact highlight the need for long-term reliable climate data at high spatiotemporal resolution to answer key science questions in cold regions hydrology. Prior to the digital age, climate records were archived on paper. For example, from the 1950s to the 1990s, solar radiation data from recording stations worldwide were published in booklets by the former Union of Soviet Socialist Republics (USSR) Hydrometeorological Service. As a result, the data are not easily accessible by most researchers. The overarching aim of this research is to develop techniques to convert paper-based climate records into a machine-readable format to support environmental research in cold regions. This study compares the performance of a proprietary optical character recognition (OCR) service with an open-source OCR tool for digitizing hydrometeorological data. We built a digitization pipeline combining different image preprocessing techniques, semantic segmentation, and an open-source OCR engine for extracting data and metadata recorded in the scanned documents. Each page contains blocks of text with station names and tables containing the climate data. The process begins with image preprocessing to reduce noise and to improve quality before the page content is segmented to detect tables and finally run through an OCR engine for text extraction. We outline the digitization process and report on initial results, including different segmentation approaches, preprocessing image algorithms, and OCR techniques to ensure accurate extraction and organization of relevant metadata from thousands of scanned climate records. We evaluated the performance of Tesseract OCR and ABBYY FineReader on text extraction. We find that although ABBY FineReader has better accuracy on the sample data, our custom extraction pipeline using Tesseract is efficient and scalable because it is flexible and allows for more customization.This work was partially funded by the Canada First Research Excellence Fund’s Global Water Futures Programme

Evaluating the Current State of Findability and Accessibility of Microplastics Data

Tia Jenkins1, Bhaleka D. Persaud1, Win Cowger2, Kathy Szigeti3, Dominique G. Roche4,5, Erin Clary6, Stephanie Slowinski1, Benjamin Lei1, Amila Abeynayaka7, Ebenezer S. Nyadjro8,9, Thomas Maes10, Leah Thornton Hampton11, Melanie Bergmann12, Julian Aherne13, Sherri A. Mason14, John F. Honek15, Fereidoun Rezanezhad1, Amy L. Lusher16, Andy M. Booth17, Rodney D. L. Smith15 and Philippe Van Cappellen1. Affiliations: 1 Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, Canada 2 Moore Institute for Plastic Pollution Research, Long Beach, CA, United States 3 Davis Centre Library, University of Waterloo, Waterloo, ON, Canada 4 Department of Biology, Carleton University, Ottawa, ON, Canada 5 Institute of Biology, University of Neuchâtel, Neuchâtel, Switzerland 6 Digital Research Alliance of Canada, Ottawa, ON, Canada 7 Institute for Global Environment Strategies (IGES), Kanagawa, Japan 8 National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI), Stennis Space Center, Starkville, MS, United States 9 Northern Gulf Institute, Mississippi State University, Stennis Space Center, Starkville, MS, United States 10 GRID-Arendal, Arendal, Norway 11 Southern California Coastal Water Research Project (SCCWRP), Costa Mesa, CA, United States 12 Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany 13 School of Environment, Trent University, Peterborough, ON, Canada 14 The Behrend College, Pennsylvania State University, Erie, PA, United States 15 Department of Chemistry, University of Waterloo, Waterloo, ON, Canada 16 Norwegian Institute for Water Research, Oslo, Norway 17 SINTEF Ocean, Trondheim, NorwayThe rapid growth in microplastic pollution research is influencing funding priorities, environmental policy, and public perceptions of risks to water quality and environmental and human health. Ensuring that environmental microplastics research data are findable, accessible, interoperable, and reusable (FAIR) is essential to inform policy and mitigation strategies. We present a bibliographic analysis of data sharing practices in the environmental microplastics research community, highlighting the state of openness of microplastics data. A stratified (by year) random subset of 785 of 6,608 microplastics articles indexed in Web of Science indicates that, since 2006, less than a third (28.5%) contained a data sharing statement. These statements further show that most often, the data were provided in the articles’ supplementary material (38.8%) and only 13.8% via a data repository. Of the 279 microplastics datasets found in online data repositories, 20.4% presented only metadata with access to the data requiring additional approval. Although increasing, the rate of microplastic data sharing still lags behind that of publication of peer-reviewed articles on environmental microplastics. About a quarter of the repository data originated from North America (12.8%) and Europe (13.4%). Marine and estuarine environments are the most frequently sampled systems (26.2%); sediments (18.8%) and water (15.3%) are the predominant media. Of the available datasets accessible, 15.4% and 18.2% do not have adequate metadata to determine the sampling location and media type, respectively. We discuss five recommendations to strengthen data sharing practices in the environmental microplastic research community. Read more at https://www.frontiersin.org/articles/10.3389/fenvs.2022.912107/fullNSERC/ECCC Alliance Grants - Plastics science for a cleaner future program, Grant ALLRP 558435-20 || The Canada First Research Excellence Fund Global Water Futures Programme || The McPike Zima Charitable || The PoF IV program “Changing Earth - Sustaining our Future” Topic 6.4 of the German Helmholtz Association || The Research Council of Norway projects REVEAL, Grant 301157 || ANDROMEDA, Grant 312262 || MicroLEACH, Grant 295174 || The Early-Career Research Fellowship from the Gulf Research Program of the US National Academies of Sciences, Engineering, and Medicine, Grant 2000012639 || European Union’s Horizon 2020 Coordination and Support Action programme, Grant 101003805 (EUROqCHARM) || The Union Horizon 2020 research and innovation programme under Marie Skłodowska-Curie, Grant 838237-OPTIMISE

My data collection is complete, now what? Connecting researchers to Data Repositories that can support Cold Regions Researchers

We also acknowledge the reviews provided by C. Dubois (Gordon Foundation), G. Veg (Polar Data Catalogue), Erin Clary (Federated Research Data Repository (FRDR)).The natural climate variability of the cold regions, together with the relatively sparse observational data sets and difficult terrain can make data collection which supports key science challenging. Notwithstanding, investments are constantly made by funders to support data collection in cold regions and as such it is important to ensure data from these regions are properly deposited and preserved according to FAIR (Findable, Accessible, Interoperable and Reusable) principles. The goal of this work is to do a comprehensive review of data repositories that can support researchers working in Canada. We evaluated the Federated Research Data Repository, Scholars Portal Dataverse, DataStream, Polar Data Catalogue, PANGAEA, and Zenodo are the repositories selected as they appear to be most popular amongst cold regions researchers. A thorough review was done on these data repository by analyzing 33 key characteristics. The findings of this work would be relevant to researchers, such as: the curation method for data depositing, dataset storage allocation, and persistent identifier support, among other characteristics of interest. It is hoped that this review will provide additional insights to the research community when they are deciding on repositories which best fits their data needs, and thus ultimately it will help to enhance access to data in cold regions.Financial support was provided by the Global Water Futures program funded by the Canada First Research Excellence Fun

Current State of Microplastic Pollution Research Data: Trends in Availability and Sources of Open Data

The rapid growth in microplastic pollution research is influencing funding priorities, environmental policy, and public perceptions of risks to water quality and environmental and human health. Ensuring that environmental microplastics research data are findable, accessible, interoperable, and reusable (FAIR) is essential to inform policy and mitigation strategies. We present a bibliographic analysis of data sharing practices in the environmental microplastics research community, highlighting the state of openness of microplastics data. A stratified (by year) random subset of 785 of 6,608 microplastics articles indexed in Web of Science indicates that, since 2006, less than a third (28.5%) contained a data sharing statement. These statements further show that most often, the data were provided in the articles’ supplementary material (38.8%) and only 13.8% via a data repository. Of the 279 microplastics datasets found in online data repositories, 20.4% presented only metadata with access to the data requiring additional approval. Although increasing, the rate of microplastic data sharing still lags behind that of publication of peer-reviewed articles on environmental microplastics. About a quarter of the repository data originated from North America (12.8%) and Europe (13.4%). Marine and estuarine environments are the most frequently sampled systems (26.2%); sediments (18.8%) and water (15.3%) are the predominant media. Of the available datasets accessible, 15.4% and 18.2% do not have adequate metadata to determine the sampling location and media type, respectively. We discuss five recommendations to strengthen data sharing practices in the environmental microplastic research community

Current State of Microplastic Pollution Research Data: Trends in Availability and Sources of Open Data

The rapid growth in microplastic pollution research is influencing funding priorities, environmental policy, and public perceptions of risks to water quality and environmental and human health. Ensuring that environmental microplastics research data are findable, accessible, interoperable, and reusable (FAIR) is essential to inform policy and mitigation strategies. We present a bibliographic analysis of data sharing practices in the environmental microplastics research community, highlighting the state of openness of microplastics data. A stratified (by year) random subset of 785 of 6,608 microplastics articles indexed in Web of Science indicates that, since 2006, less than a third (28.5%) contained a data sharing statement. These statements further show that most often, the data were provided in the articles’ supplementary material (38.8%) and only 13.8% via a data repository. Of the 279 microplastics datasets found in online data repositories, 20.4% presented only metadata with access to the data requiring additional approval. Although increasing, the rate of microplastic data sharing still lags behind that of publication of peer-reviewed articles on environmental microplastics. About a quarter of the repository data originated from North America (12.8%) and Europe (13.4%). Marine and estuarine environments are the most frequently sampled systems (26.2%); sediments (18.8%) and water (15.3%) are the predominant media. Of the available datasets accessible, 15.4% and 18.2% do not have adequate metadata to determine the sampling location and media type, respectively. We discuss five recommendations to strengthen data sharing practices in the environmental microplastic research community