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Dominant Modes of Seasonal Moisture Flux Variability and Their Synoptic Drivers Over the North American Prairies

Submitted:

09 December 2025

Posted:

11 December 2025

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Abstract
The North American Prairies are a region of critical importance to continental hydroclimate and agriculture, exhibiting high sensitivity to variability in atmospheric moisture transport. This study investigates the seasonal and interannual variability of integrated moisture flux over the Prairie region (246°–264°E, 49°N–53°N) using the National Centers for Environmental Prediction (NCEP) Reanalysis dataset from 1979 to 2022. We employ a combination of composite analysis and Empirical Orthogonal Function (EOF) analysis to identify the dominant modes of variability and their associated large-scale synoptic drivers. Our results confirm a strong seasonal reversal: winter moisture flux is predominantly zonal (westerly), contributing an average of 26.2% to total inbound flux, while summer flux is primarily meridional (southerly), contributing a dominant 72.6%. Composite analysis of extreme moisture years reveals that anomalously high moisture winters are associated with an intensified Aleutian Low and a strengthened pressure gradient off the North American west coast, facilitating enhanced westerly flow. Conversely, a strengthened continental high-pressure system characterizes anomalously low moisture winters by. During summer, high moisture years are driven by an enhanced southerly component of flow, likely linked to a strengthened Great Plains Low-Level Jet (GPLLJ). The first EOF mode for winter explains 36.4% of the variance in eastward flux and is characterized by a pattern consistent with the El Niño Southern Oscillation (ENSO) teleconnection pattern. These findings underscore the control of Pacific-centric circulation patterns on Prairie hydroclimate and have significant implications for predicting seasonal water availability.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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