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Risser, Mark D., Wehner, Michael F., O’Brien, John P., Patricola, Christina M., O’Brien, Travis A., Collins, William D. 
ORCID: https://orcid.org/0000-0002-4463-9848, Paciorek, Christopher J. and Huang, Huanping
(2021)
Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation.
Climate Dynamics, 56 (9-10).
pp. 3205-3230.
ISSN 0930-7575
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Abstract
While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.
| Item Type: | Article |
|---|---|
| Additional Information: | Data availability: The precipitation data supporting this article are based on publicly available measurements from the National Centers for Environmental Information (ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/). Support for the Twentieth Century Reanalysis Project version 3 dataset is provided by the US Department of Energy, Office of Science Biological and Environmental Research (BER), by the National Oceanic and Atmospheric Administration Climate Program Office, and by the NOAA Earth System Research Laboratory Physical Sciences Division. ELI data are available at https://portal.nersc.gov/archive/home/projects/cascade/www/ELI. |
| Uncontrolled Keywords: | southern oscillation,extreme value analysis,natural variability,north atlantic oscillation,pacific–north american pattern,spatial statistics,station data,atmospheric science,sdg 13 - climate action ,/dk/atira/pure/subjectarea/asjc/1900/1902 |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 10 Jul 2026 08:28 |
| Last Modified: | 12 Jul 2026 23:02 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/103813 |
| DOI: | 10.1007/s00382-021-05638-7 |
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