From May 24 to May 27, I had the opportunity to attend the 2026 Canadian Geophysical Union (CGU) conference, in Halifax, NS, which would not have been possible without the QCS Conference Travel Award. This year, it was a joint conference with the International Association of Hydrogeologists Canada (IAH-CNC), and explored the synergies of cutting-edge hydrological research, with new developments in hydrogeological science, particularly around permafrost hydrology and hydrogeology in cold regions.
I was fortuitously given a last-minute opportunity to present a talk in the “Observation and Modelling of Snow and Glacier Processes” session, where I discussed the combined effects of elevation and snow cover biases in driving reanalysis and LDAS soil temperature biases over SNOTEL stations in mountainous regions of the western United States. The session focused on snowpack hydrology, the impacts of snow and ice on the land surface energy balance, regional to continental scale estimates of snow cover and SWE, as well as connections between snow and frozen ground dynamics. My focus on the connections between reanalysis snow cover, land model parameterizations of snow processes, and soil temperature estimates had strong synergies with a talk on improving snowfall estimates and snowpack simulations in British Columbia, as well as a talk exploring spatiotemporal trends in snow droughts which made use of ERA5-Land SWE. I also presented a poster later in the day on the same topic during the Hydrology and Hydrogeology Poster session.
Having the opportunity to present during both sessions afforded me a greater chance to network and increased the visibility of my research. My poster booth was situated next to another poster from our research group which explored the use of machine learning to bias-correct reanalysis soil moisture estimates – and the results from that study have strong relevance to the work I am doing. It was convenient to be able to talk with the community about the connections between our research projects, and their ties to regional to large-scale hydrological studies.
During the conference, I also had the opportunity to attend a session on cold regions hydrological processes, which included talks on permafrost hydrology, the impact of new snow parameterizations on simulated snow cover in mountainous regions, and the impacts of climate change in permafrost regions on groundwater recharge rates. In addition, I was able to attend an interdisciplinary session focused on assessing the response of ground water and recharge to climatic changes, as the bias-corrected soil temperature product I presented on at last year’s CGU conference has been incorporated into the Canada1Water Project and the HydroGeosphere model, both of which were heavily featured in the session.
The conference presented an excellent opportunity to speak with several folks from Natural Resources Canada (NRCAN), as well as Environment and Climate Change Canada (ECCC), who were extremely interested in the results from my research. The bias corrected soil temperature product, described in a soon to be published manuscript, entitled “Application of machine learning to improve reanalysis soil temperatures over the extratropical northern hemisphere”, has been used in an NRCAN study investigating the permafrost distribution over the Carcajou watershed. Understanding the impacts of land model parameterizations on snow cover estimates and soil temperatures, and the linkages between the two are extremely important for improving permafrost simulations. The same manuscript compiled an extensive historical record of soil temperature from over 2600 stations, including over 200 stations from agricultural soil climate networks across Canada, which have traditionally been undervalued for model validation. ECCC was particularly interested in the validation work I have done over Canada, as they are in the process of validating an updated version of the Canadian Precipitation Analysis which incorporates a newly updated land surface scheme. My recent research focused on SNOTEL stations over mountainous regions of the western US also has strong relevance to ECCC’s efforts to improve simulations of SWE and snow cover in British Columbia.
I left CGU this year with several new connections at NRCAN and ECCC and given my cross-disciplinary research exploring the impacts of land model parameterizations on large-scale snow and soil temperature estimates, my research is extremely relevant to both organizations. I plan to continue to network with the key contacts I made during the conference and explore future possibilities for collaboration with NRCAN and ECCC.