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<p>Extreme precipitation results from interactions among atmospheric moisture, instability, and dynamics, with their relative importance varying regionally and seasonally under climate change. This study quantifies the contributions of precipitable water (PW), convective available potential energy (CAPE), and vertically integrated moisture divergence (VIMD) to annual maximum precipitation (AMP) across North America through a comparative analysis using ERA5-based atmospheric variables and precipitation data from both ERA5 and gauge observations. Using a nonstationary generalized extreme value framework, we assess the nonstationary behavior of AMP events with these drivers and their combinations as covariates. Results show that VIMD, representing moisture convergence, is the most influential driver across 46% of grid cells. PW dominates AMP in coastal and moisture-rich regions such as the Gulf of Mexico, Great Lakes, and West Coast, while CAPE plays a significant role in southwestern regions characterized by atmospheric instability. Seasonal analysis shows extreme events are most prevalent in spring and fall, with orographic regions in the western and northeastern North America experiencing the highest concentration of extreme values due to localized atmospheric effects. A parallel analysis using gauge-based precipitation from 6018 stations across North America confirms the spatial patterns and dominant atmospheric drivers identified with ERA5, while revealing greater spatial heterogeneity and more frequent selection of complex multi-variable models, suggesting station observations better capture localized atmospheric variability. These findings underscore the necessity of incorporating multiple atmospheric variables into Probable Maximum Precipitation estimation methodologies, moving beyond single-variable approaches to enhance accuracy and reliability.</p>

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Dynamic and thermodynamic drivers of extreme precipitation under nonstationarity: implications for probable maximum precipitation across North America

  • 期刊论文

  • 发表日期：

    2026年1月3日

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  • Md Robiul Islam,
  • M. Reza Najafi

摘要

Extreme precipitation results from interactions among atmospheric moisture, instability, and dynamics, with their relative importance varying regionally and seasonally under climate change. This study quantifies the contributions of precipitable water (PW), convective available potential energy (CAPE), and vertically integrated moisture divergence (VIMD) to annual maximum precipitation (AMP) across North America through a comparative analysis using ERA5-based atmospheric variables and precipitation data from both ERA5 and gauge observations. Using a nonstationary generalized extreme value framework, we assess the nonstationary behavior of AMP events with these drivers and their combinations as covariates. Results show that VIMD, representing moisture convergence, is the most influential driver across 46% of grid cells. PW dominates AMP in coastal and moisture-rich regions such as the Gulf of Mexico, Great Lakes, and West Coast, while CAPE plays a significant role in southwestern regions characterized by atmospheric instability. Seasonal analysis shows extreme events are most prevalent in spring and fall, with orographic regions in the western and northeastern North America experiencing the highest concentration of extreme values due to localized atmospheric effects. A parallel analysis using gauge-based precipitation from 6018 stations across North America confirms the spatial patterns and dominant atmospheric drivers identified with ERA5, while revealing greater spatial heterogeneity and more frequent selection of complex multi-variable models, suggesting station observations better capture localized atmospheric variability. These findings underscore the necessity of incorporating multiple atmospheric variables into Probable Maximum Precipitation estimation methodologies, moving beyond single-variable approaches to enhance accuracy and reliability.