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      Rainfall Frequency Analysis Based on Long‐Term High‐Resolution Radar Rainfall Fields: Spatial Heterogeneities and Temporal Nonstationarities

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          Abstract

          Rainfall frequency analysis methods are developed and implemented based on high‐resolution radar rainfall data sets, with the Baltimore metropolitan area serving as the principal study region. Analyses focus on spatial heterogeneities and time trends in sub‐daily rainfall extremes. The 22‐year radar rainfall data set for the Baltimore study region combines reflectivity‐based rainfall fields during the period from 2000 to 2011 and polarimetric rainfall fields for the period from 2012 to 2021. Rainfall frequency analyses are based on non‐stationary formulations of peaks‐over‐threshold and annual peak methods. Increasing trends in short‐duration rainfall extremes are inferred from both peaks‐over‐threshold and annual peak analyses for the period from 2000 to 2021. There are pronounced spatial gradients in short‐duration rainfall extremes over the study region, with peak values of rainfall between Baltimore City and Chesapeake Bay. Spatial gradients in 100‐year, 1 hr rainfall over 20 km length scale are comparable to time trends over 20 years. Rainfall analyses address the broad challenge of assessing changing properties of short‐duration rainfall in urban regions. Analyses of high‐resolution rainfall fields show that sub‐daily rainfall extremes are only weakly related to daily extremes, pointing to difficulties in inferring climatological properties of sub‐daily rainfall from daily rainfall analyses. Changing measurement properties are a key challenge for application of radar rainfall data sets to detection of time trends. Mean field bias correction of radar rainfall fields using rain gauge observations is an important tool for improving radar rainfall fields and provides a useful tool for addressing problems associated with changing radar measurement properties.

          Key Points

          • Rainfall frequency analysis tools based on long‐term, high‐resolution radar rainfall fields are developed

          • Sub‐daily rainfall extremes for the Baltimore study region exhibit increasing trends over 22‐year period of record

          • Sub‐daily rainfall extremes exhibited pronounced spatial heterogeneities over the Baltimore study region

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          Most cited references92

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          An Introduction to Statistical Modeling of Extreme Values

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            The future intensification of hourly precipitation extremes

            Climate change is causing increases in extreme rainfall across the United States. This study uses observations and high-resolution modelling to show that rainfall changes related to rising temperatures depend on the available atmospheric moisture.
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              A Review of Current Investigations of Urban-Induced Rainfall and Recommendations for the Future

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                Author and article information

                Contributors
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                Journal
                Water Resources Research
                Water Resources Research
                American Geophysical Union (AGU)
                0043-1397
                1944-7973
                March 2024
                March 06 2024
                March 2024
                : 60
                : 3
                Affiliations
                [1 ] Civil & Environmental Engineering Princeton University Princeton NJ USA
                [2 ] Department of Geography and Environmental Systems University of Maryland Baltimore County Baltimore MD USA
                [3 ] Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA
                Article
                10.1029/2023WR035640
                fa2978b5-63ac-4f79-a856-9dddc579884a
                © 2024

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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