A 16-Year Climatology of WPC-Analyzed Drylines and Their Association with Severe Convection

Abstract A 16-yr (2007–22) climatology of drylines is presented. Constructed using NOAA Weather Prediction Center (WPC) surface analyses, this climatology addresses the limitations of season, time of day, and region of previous dryline studies by using the full surface analysis archive to include drylines throughout the entire day at 3-h increments for the entire year over the contiguous United States. Severe storm reports and NWS-issued severe thunderstorms and tornado warnings are used to associate individual drylines with severe (or potentially severe) convection. March–June are the months with the greatest frequency of drylines and dryline-associated severe thunderstorms. Regardless of season, average dryline longitude over the course of a day mimics the conceptual model of daily dryline evolution with an eastward shift during the day and westward retreat overnight. The overwhelming majority of WPC-analyzed drylines are located in the southern Great Plains, particularly southwest Texas through the Texas Panhandle, and on average are furthest west in summer and furthest east in winter. A significant increase in the number of analyzed drylines and dryline days per year is identified in the WPC surface analysis archive. This increase is consistent across all analysis times and between drylines associated with and without severe convection. However, using a machine learning model to automate dryline detection, no statistically significant trend is found over this same analysis period. Thus, the increase in WPC-analyzed drylines during the 16-yr period is likely to be the result of nonmeteorological factors. Significance Statement Past studies of the dryline, a boundary important to severe convective storms and the hydrology of the central United States, have only focused on the spring months. This study conducts the first year-round climatology of the dryline and their association with severe storms using 16 years of Weather Prediction Center (WPC) surface analyses. There is a significant increase in dryline frequency over the 16-yr analysis period, but this is attributed to nonmeteorological factors by comparison to an automated dryline identification model. Future work will expand this climatology back through the twentieth century and expand the analysis on the variability of drylines and their association with severe storms.

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Publication Details

Journal
Journal of Applied Meteorology and Climatology
Published
2025-03-18
DOI
https://doi.org/10.1175/jamc-d-24-0124.1
Primary Topic
Food Drying and Modeling
Type
article
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article

A 16-Year Climatology of WPC-Analyzed Drylines and Their Association with Severe Convection

Michael J. Hosek, Kimberly A. Hoogewind, John T. Allen, Andrew D. Justin et al.
Journal of Applied Meteorology and Climatology
Food Drying and Modeling
article

A 16-Year Climatology of WPC-Analyzed Drylines and Their Association with Severe Convection

Michael J. Hosek, Kimberly A. Hoogewind, John T. Allen, Andrew D. Justin, Adam J. Clark
article en

Abstract

Abstract A 16-yr (2007–22) climatology of drylines is presented. Constructed using NOAA Weather Prediction Center (WPC) surface analyses, this climatology addresses the limitations of season, time of day, and region of previous dryline studies by using the full surface analysis archive to include drylines throughout the entire day at 3-h increments for the entire year over the contiguous United States. Severe storm reports and NWS-issued severe thunderstorms and tornado warnings are used to associate individual drylines with severe (or potentially severe) convection. March–June are the months with the greatest frequency of drylines and dryline-associated severe thunderstorms. Regardless of season, average dryline longitude over the course of a day mimics the conceptual model of daily dryline evolution with an eastward shift during the day and westward retreat overnight. The overwhelming majority of WPC-analyzed drylines are located in the southern Great Plains, particularly southwest Texas through the Texas Panhandle, and on average are furthest west in summer and furthest east in winter. A significant increase in the number of analyzed drylines and dryline days per year is identified in the WPC surface analysis archive. This increase is consistent across all analysis times and between drylines associated with and without severe convection. However, using a machine learning model to automate dryline detection, no statistically significant trend is found over this same analysis period. Thus, the increase in WPC-analyzed drylines during the 16-yr period is likely to be the result of nonmeteorological factors. Significance Statement Past studies of the dryline, a boundary important to severe convective storms and the hydrology of the central United States, have only focused on the spring months. This study conducts the first year-round climatology of the dryline and their association with severe storms using 16 years of Weather Prediction Center (WPC) surface analyses. There is a significant increase in dryline frequency over the 16-yr analysis period, but this is attributed to nonmeteorological factors by comparison to an automated dryline identification model. Future work will expand this climatology back through the twentieth century and expand the analysis on the variability of drylines and their association with severe storms.

Journal of Applied Meteorology and ClimatologyVol. 64(4)
Central Michigan University (US), Cooperative Institute for Mesoscale Meteorological Studies (US), NOAA National Severe Storms Laboratory (US), University of Oklahoma (US)
Openalex Percentile: Top 95%
Food Drying and Modeling
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