Canada’s Contributions to the SWOT Mission–Terrestrial Hydrology(SWOT-C TH)

The origins of the Surface Water and Ocean Topography (SWOT) mission date back to the mid-1970s with the launch of GOES-3 and SEASAT. These missions were then followed in 1992 by the Topex-Poseidon satellite, then by Jason-1 (2001), OSTM/Jason-2 (2008), and Jason 3 (2016), a series of joint satellite missions between NASA and CNES with a goal to monitor global ocean circulation. The proposed new SWOT mission will provide 120-km-wide swath interferometric coverage with a 20-km-wide gap at the nadir. The SWOT measurements will consist of water surface elevations and water surface slopes covering nearly all of the earth’s land surface at least once every 21 days. In 2010, NASA invited the Canadian Space Agency to contribute, and Canadian scientists welcomed the invitation to join the SWOT Science Definition Team and contribute to the experiments. The Canadian segment of the mission is known as the “SWOT-C” project. The SWOT satellite mission will provide unique opportunities in the Canadian context for water managers in both the public domain and in the private sector. This paper provides an overview of recent scientific progress by the SWOT-C Terrestrial Hydrology team, outlining current plans and progress towards applications and calibration post-launch

How well do covariates perform when adjusting for sampling bias in online COVID-19 research? Insights from multiverse analyses

COVID-19 research has relied heavily on convenience-based samples, which—though often necessary—are susceptible to important sampling biases. We begin with a theoretical overview and introduction to the dynamics that underlie sampling bias. We then empirically examine sampling bias in online COVID-19 surveys and evaluate the degree to which common statistical adjustments for demographic covariates successfully attenuate such bias. This registered study analysed responses to identical questions from three convenience and three largely representative samples (total N = 13,731) collected online in Canada within the International COVID-19 Awareness and Responses Evaluation Study (www.icarestudy.com). We compared samples on 11 behavioural and psychological outcomes (e.g., adherence to COVID-19 prevention measures, vaccine intentions) across three time points and employed multiverse-style analyses to examine how 512 combinations of demographic covariates (e.g., sex, age, education, income, ethnicity) impacted sampling discrepancies on these outcomes. Significant discrepancies emerged between samples on 73% of outcomes. Participants in the convenience samples held more positive thoughts towards and engaged in more COVID-19 prevention behaviours. Covariates attenuated sampling differences in only 55% of cases and increased differences in 45%. No covariate performed reliably well. Our results suggest that online convenience samples may display more positive dispositions towards COVID-19 prevention behaviours being studied than would samples drawn using more representative means. Adjusting results for demographic covariates frequently increased rather than decreased bias, suggesting that researchers should be cautious when interpreting adjusted findings. Using multiverse-style analyses as extended sensitivity analyses is recommended