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Preprints
https://doi.org/10.5194/egusphere-2023-3094
https://doi.org/10.5194/egusphere-2023-3094
14 Mar 2024
 | 14 Mar 2024

Algorithmically Detected Rain-on-Snow Flood Events in Different Climate Datasets: A Case Study of the Susquehanna River Basin

Colin M. Zarzycki, Benjamin D. Ascher, Alan M. Rhoades, and Rachel R. McCrary

Abstract. Rain-on-snow (RoS) events in regions of ephemeral snowpack – such as the northeastern United States – can be key drivers of cool-season flooding. We describe an automated algorithm for detecting basin-scale RoS events in gridded climate data by generating an area-averaged time-series and then searching for periods of concurrent precipitation, surface runoff, and snowmelt exceeding pre-defined thresholds. When evaluated using historical data over the Susquehanna River Basin (SRB), the technique credibly finds RoS events in published literature and flags events that are followed by anomalously high streamflow as measured by gage data along the river. When comparing four different datasets representing the same 21-year period, we find large differences in RoS event magnitude and frequency, primarily driven by differences in estimated surface runoff and snowmelt. Using dataset-specific thresholds improves agreement between datasets but does not account for all discrepancies. We show that factors such as meteorological forcing and coupling frequency as well as choice of land surface model play roles in how data products capture these compound extremes and suggest care is to be taken when climate datasets are used by stakeholders for operational decision-making.

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Journal article(s) based on this preprint

30 Sep 2024
Algorithmically detected rain-on-snow flood events in different climate datasets: a case study of the Susquehanna River basin
Colin M. Zarzycki, Benjamin D. Ascher, Alan M. Rhoades, and Rachel R. McCrary
Nat. Hazards Earth Syst. Sci., 24, 3315–3335, https://doi.org/10.5194/nhess-24-3315-2024,https://doi.org/10.5194/nhess-24-3315-2024, 2024
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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We developed an automated workflow to detect rain-on-snow events, which cause flooding in the...
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