Suriano et al. (2025) Temporal trends and large-scale atmospheric and oceanic forcings of central U.S. snowfall producing weather systems, 1948–2021

Identification

• Journal: Climate Dynamics
• Year: 2025
• Date: 2025-09-29
• Authors: Zachary J. Suriano, Gregory B. Goodrich, Charles Loewy, Jamie Uz
• DOI: 10.1007/s00382-025-07832-3

Research Groups

• Department of Earth, Environmental and Atmospheric Sciences, Western Kentucky University, Bowling Green, KY, USA
• Department of Biology, University of Nebraska Omaha, Omaha, NE, USA

Short Summary

This study investigates the temporal trends and large-scale atmospheric and oceanic forcings of snowfall-producing weather systems in the central U.S. from 1948 to 2021, revealing significant changes in synoptic weather type frequencies, inherent meteorological characteristics, and their links to teleconnection indices.

Objective

• Identify the temporal and spatial trends in synoptic-scale weather patterns and their snowfall in the central United States.
• Evaluate how the internal meteorological conditions of snowfall-producing weather patterns are varying and/or changing over time.
• Quantify and explain the statistical and physical correlations between the frequency, intensity, and internal conditions of snowfall-producing synoptic weather patterns and large-scale modes of atmospheric and oceanic variations.

Study Configuration

• Spatial Scale: Central United States, specifically Iowa (IA), Kansas (KS), Missouri (MO), Nebraska (NE), South Dakota (SD), and the southern half of Minnesota (MN).
• Temporal Scale: November 1948 to April 2021 (73-year period).

Methodology and Data

• Models used:
  • Temporal Synoptic Index (TSI) classification procedure.
  • Unrotated P-mode Principal Component Analysis (PCA).
  • Within groups average linkage clustering.
  • ECMWF ERA5 hourly reanalysis for synoptic weather type (SWT) composites and daily averaged meteorological conditions.
• Data sources:
  • Daily snowfall data: Global Historical Climatological Network (GHCN) daily dataset from 134 observation stations.
  • Hourly meteorological observations (temperature, dew point temperature, sea level pressure, cloud cover, u/v wind vectors) for TSI: GHCN-hourly dataset from Omaha, NE.
  • Teleconnection data (Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Niño 3.4 index, Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), Pacific/North American Pattern (PNA), Global Mean Land/Ocean Temperature (GMT) index): NOAA Physical Sciences Library.

Main Results

• Ten distinct synoptic weather types (SWTs) were identified as contributing to seasonal snowfall in the central U.S., with the majority associated with closed surface lows.
• Five SWTs exhibited significant linear trends in seasonal snow day frequency, SWT frequencies, and/or percentages of SWTs resulting in snowfall over the 73-year period.
  • SWT 4 frequency and snow days decreased, but snowfall magnitude per event increased in the northern domain (e.g., 0.7–1.4 mm yr⁻¹ increase in a zone from northcentral NE into southern MN, approximately 80 mm additional seasonal snowfall).
  • SWT 5 frequency and snow days increased (42% increase in frequency, approximately 75% increase in snow days), leading to broad snowfall increases in the western domain (0.6–1.1 mm yr⁻¹ in western NE).
  • SWT 1 showed decreased frequency but increased percentage of occurrences leading to snowfall, with snowfall increases of 2.0–2.5 mm yr⁻¹ in western/northern NE, eastern SD, and parts of east-central IA (up to 161 mm additional seasonal snowfall).
  • SWT 3 and SWT 6 exhibited mixed trends, with significant increases in northern SD (e.g., >3.0 mm yr⁻¹ for SWT 3, up to 235 mm additional) and significant decreases in southcentral SD, central NE, northeastern KS, and much of IA (e.g., >2.5 mm yr⁻¹ reduction).
• Nearly all SWTs exhibited significant changes in inherent meteorological characteristics over time, including sea-level pressure, air temperature, and dew point temperature.
  • SWTs 6 and 9 showed widespread significant increases in sea-level pressure (at least 0.025 hPa yr⁻¹) in the southeastern quadrant.
  • SWT 8 showed decreased sea-level pressure (up to 0.04 hPa yr⁻¹) over central regions.
  • Nine of ten SWTs showed relatively large areas with significant increases in air temperatures (at least 0.02 °C yr⁻¹, some exceeding 0.045 °C yr⁻¹).
  • Many SWTs also exhibited increases in dew point temperatures (e.g., SWTs 2 and 3 >0.03 °C yr⁻¹ across northern U.S./southern Canada; SWT 7 widespread increases).
• March snow day frequency and the percentage of days resulting in snowfall significantly decreased across all SWTs.
• The interannual frequency of SWTs and snow day frequencies were significantly related to several large-scale teleconnection indices (AMO, AO, NAO, Niño 3.4, PNA, GMT), indicating their role in forcing regional snowfall variability.

Contributions

• Provides the first quantitative evaluation of how changes in snowfall-producing weather systems contribute to observed snowfall trends in the central U.S.
• Offers a detailed synoptic climatological analysis of snowfall trends, intra-synoptic type variability, and large-scale atmospheric/oceanic forcings for the central U.S.
• Establishes connections between regional snowfall variability and trends and changes in specific synoptic weather types' frequencies and their inherent meteorological characteristics.
• Quantifies statistical and physical correlations between SWTs and major teleconnection indices, enhancing understanding of forcing mechanisms.
• Delivers insights for improved understanding and forecasting of regional hydroclimatic processes.

Funding

• Ogden College of Science and Engineering at Western Kentucky University
• Office of Research and Creative Activity at the University of Nebraska Omaha

Citation

@article{Suriano2025Temporal,
  author = {Suriano, Zachary J. and Goodrich, Gregory B. and Loewy, Charles and Uz, Jamie},
  title = {Temporal trends and large-scale atmospheric and oceanic forcings of central U.S. snowfall producing weather systems, 1948–2021},
  journal = {Climate Dynamics},
  year = {2025},
  doi = {10.1007/s00382-025-07832-3},
  url = {https://doi.org/10.1007/s00382-025-07832-3}
}