edu.ucar.opensky::articles:42542 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T18:06:55.971325 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.net/ark:/85065/d7wm1jr8 https://doi.org/10.5066/P96CPHOT https Related Dataset #1 GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow https://doi.org/10.5281/ZENODO.10287092 https Related Dataset #2 Northern Hemisphere historical in-situ Snow Water Equivalent dataset (NorSWE, 1979-2021) https://doi.org/10.5281/ZENODO.3953310 https Related Dataset #3 SCDNA: a serially complete precipitation and temperature dataset in North America from 1979 to 2018 (Version 1.1) https://doi.org/10.5281/ZENODO.7734616 https Related Dataset #4 Canadian historical Snow Water Equivalent dataset (CanSWE, 1928-2022) https://doi.org/10.5066/P94I5TX3 https Related Software #1 dataretrieval (python): a Python package for discovering and retrieving water data available from Federal hydrologic web services https://doi.org/10.5281/zenodo.12100921 https Related Software #2 FROSTBYTE: Forecasting River Outlooks from Snow Timeseries: Building Yearly Targeted Ensembles https://doi.org/10.5281/zenodo.13381746 https Related Software #3 FROSTBYTE: Forecasting River Outlooks from Snow Timeseries: Building Yearly Targeted Ensembles FROSTBYTE: A reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America 2024-09-01T00:00:00Z publication https://n2t.net/ark:/85065/d7wm1jr8 https://doi.org/10.5194/hess-28-4127-2024 Arnal, L. author Clark, M. P. author Pietroniro, A. author Vionnet, V. author Casson, D. R. author Whitfield, P. H. author Fortin, V. author Wood, Andrew author Knoben, W. J. M. author Newton, B. author Walford, C. author UCAR/NCAR - Library publisher Seasonal streamflow forecasts provide key information for decision-making in fields such as water supply management, hydropower generation, and irrigation scheduling. The predictability of streamflow on seasonal timescales relies heavily on initial hydrological conditions, such as the presence of snow and the availability of soil moisture. In high-latitude and high-altitude headwater basins in North America, snowmelt serves as the primary source of runoff generation. This study presents and evaluates a data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America (Canada and the USA). The workflow employs snow water equivalent (SWE) measurements as predictors and streamflow observations as predictands. Gap-filling of SWE datasets is accomplished using quantile mapping from neighboring SWE and precipitation stations, and principal component analysis is used to identify independent predictor components. These components are then utilized in a regression model to generate ensemble hindcasts of streamflow volumes for 75 nival basins with limited regulation from 1979 to 2021, encompassing diverse geographies and climates. Using a hindcast evaluation approach that is user-oriented provides key insights for snow-monitoring experts, forecasters, decision-makers, and workflow developers. The analysis presented here unveils a wide spectrum of predictability and offers a glimpse into potential future changes in predictability. Late-season snowpack emerges as a key factor in predicting spring and summer volumes, while high precipitation during the target period presents challenges to forecast skill and streamflow predictability. Notably, we can predict lower-than-normal and higher-than-normal streamflows during spring to early summer with lead times of up to 5 months in some basins. Our workflow is available on GitHub as a collection of Jupyter Notebooks, facilitating broader applications in cold regions and contributing to the ongoing advancement of methodologies. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication <span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</span> None eng geoscientificInformation