Hwang et al. (2025) Unfolding North American spring weather extremes along a scale ladder

Identification

• Journal: Scientific Reports
• Year: 2025
• Date: 2025-11-05
• Authors: Jaeyoung Hwang, Zhenyu You, Yi Deng, Hera Kim
• DOI: 10.1038/s41598-025-22366-8

Research Groups

• School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
• Department of Atmospheric and Climate Science, University of Washington, Seattle, WA, USA

Short Summary

This study delineates the multi-layered dynamics of North American spring weather extremes by identifying four leading subseasonal modes of variability. These modes are shown to modulate the occurrence frequencies of wet, dry, and wind extremes by up to twofold and exhibit distinct decadal-scale activity changes, providing a dynamics-based framework for understanding and predicting long-term extreme weather variability.

Objective

• To comprehensively delineate the statistical and dynamical nature of spring subseasonal variability over North America.
• To integrate this subseasonal variability into a conceptual "scale ladder" to effectively unfold the multi-layered dynamics of spring weather extremes, focusing on their spatial variations and activity changes across decadal timescales.

Study Configuration

• Spatial Scale: North America, with a focus on the eastern North Pacific-North America sector (170°W–70°W; 20°N–70°N) for subseasonal mode identification. Global context for some climatological analyses.
• Temporal Scale: Boreal springs (March-April-May) over the period of 1979–2023 (45 years). Analysis spans subseasonal (10–30 days), synoptic (2–10 days), mesoscale (sub-daily/hourly), and decadal timescales.

Methodology and Data

• Models used:
  • Empirical Orthogonal Function (EOF) analysis for identifying leading subseasonal modes.
  • Composite analysis for assessing impacts of EOF modes on surface extremes and smaller-scale variability.
  • Quantile regression analysis for robustness checks.
  • Lagrangian blocking index for atmospheric blocking identification.
  • Petterssen’s two-dimensional kinematic frontogenesis function for frontogenesis assessment.
• Data sources:
  • ERA5 (5th generation reanalysis of the European Centre for Medium-Range Weather Forecasts) for hourly and 6-hourly atmospheric variables (e.g., 500 hPa geopotential height, 10 m wind speed, pressure velocity, specific humidity, potential temperature).
  • CPC (Climate Prediction Center) global gauge-based daily precipitation data.
  • MCS (Mesoscale Convective System) tracking data (from Zenodo).
  • PDO (Pacific Decadal Oscillation) index (from NOAA NCEI).

Main Results

• Four leading modes of springtime subseasonal variability were identified over North America, explaining 60% of the total variability. These modes are characterized by localized geopotential anomalies over the North Pacific and northeastern North America, and two branches of zonally propagating Rossby wave packets.
• These subseasonal modes significantly modulate the activity of wet, dry, and wind extremes across North America, causing up to a twofold change in their occurrence frequencies.
• The modes exhibit distinct "active" and "muted" periods over four decades, leading to decadal-scale changes in the frequency of weather extremes (e.g., 6 out of 10 years with elevated hydrological extremes during Mode 4's active decade vs. 2 during its muted decade in the south-central United States).
• Subseasonal modes influence local synoptic- and mesoscale variability, with amplifications of up to approximately 25% for synoptic variability and 45% for mesoscale variability in affected regions.
• Changes in large-scale dynamical and thermodynamic environments (e.g., moisture transport, pressure velocity, frontogenesis) associated with subseasonal modes are consistent with corresponding changes in synoptic- and mesoscale variabilities and surface extremes.
• Notable relationships were observed between MJO phases and Modes 1, 3, and 4, and between the PDO index and Modes 2, 3, and 4, suggesting connections to atmosphere-ocean coupled variability and potential anthropogenic forcing.

Contributions

• Introduces and outlines a novel "scale ladder" conceptual framework for systematically dissecting the multi-layered dynamics of regional weather extremes.
• Provides a dynamics-based guideline for understanding the causes of long-term changes in extremes and identifying potential sources of predictability across various timescales.
• Integrates known ideas of scale interaction into a systematic method, emphasizing the critical role of subseasonal variability as a bridge between large-scale climate forcings and local extreme weather events.
• Demonstrates how this multi-scale perspective can be applied to diagnose observed extremes, understand model biases, and identify predictability sources.

Funding

• U.S. National Science Foundation (NSF) through Grant AGS-2032532
• U.S. National Oceanic and Atmospheric Administration (NOAA) through Grant NA22OAR4310606

Citation

@article{Hwang2025Unfolding,
  author = {Hwang, Jaeyoung and You, Zhenyu and Deng, Yi and Kim, Hera},
  title = {Unfolding North American spring weather extremes along a scale ladder},
  journal = {Scientific Reports},
  year = {2025},
  doi = {10.1038/s41598-025-22366-8},
  url = {https://doi.org/10.1038/s41598-025-22366-8}
}