Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United States
Global warming is likely to provoke extreme storms in the eastern United States (eUS), ultimately affecting the probabilistic distribution of the dates of daily maximum precipitation. In this study, probabilistic properties of timing of annual maximum precipitation (AMP) were studied using circular...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/14/2/366 |
| _version_ | 1797622419079299072 |
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| author | Ali Aljoda Nirajan Dhakal |
| author_facet | Ali Aljoda Nirajan Dhakal |
| author_sort | Ali Aljoda |
| collection | DOAJ |
| description | Global warming is likely to provoke extreme storms in the eastern United States (eUS), ultimately affecting the probabilistic distribution of the dates of daily maximum precipitation. In this study, probabilistic properties of timing of annual maximum precipitation (AMP) were studied using circular statistics at 583 sites in the eUS (1950–2019). A kernel circular density method was applied to examine distributional modes of timing of AMP. The results of circular median show that seasonality is pronounced across the eUS with many locations having their median date of occurrence in summer, and AMP seasonality is strong in the East North Central region. Similarly, results of circular density method applied to the distribution of AMP timing shows that around 90% of the sites have two or three modes of AMP seasonality in the eUS. Comparison of seasonality between two historical records of equal length (1950–1984 and 1985–2019) shows great spatial variability across the eUS. Temporal changes in seasonal modes for AMP dates revealed four different cases of seasonality changes: (i) weakening of seasonality, (ii) strengthening of seasonality, (iii) strong seasonality for both the old and recent periods, (iv) or uniform or no preferred seasonality for both periods. While a spatial coherence of seasonality changes was not observed, majority of sites showed strong seasonality (case iii) for old and recent periods mainly during summer and fall seasons. |
| first_indexed | 2024-03-11T09:10:01Z |
| format | Article |
| id | doaj.art-76a775501f934345b183b3c9542b209a |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-11T09:10:01Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-76a775501f934345b183b3c9542b209a2023-11-16T19:03:51ZengMDPI AGAtmosphere2073-44332023-02-0114236610.3390/atmos14020366Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United StatesAli Aljoda0Nirajan Dhakal1Environmental and Health Sciences Program, Spelman College, Atlanta, GA 30314-4399, USAEnvironmental and Health Sciences Program, Spelman College, Atlanta, GA 30314-4399, USAGlobal warming is likely to provoke extreme storms in the eastern United States (eUS), ultimately affecting the probabilistic distribution of the dates of daily maximum precipitation. In this study, probabilistic properties of timing of annual maximum precipitation (AMP) were studied using circular statistics at 583 sites in the eUS (1950–2019). A kernel circular density method was applied to examine distributional modes of timing of AMP. The results of circular median show that seasonality is pronounced across the eUS with many locations having their median date of occurrence in summer, and AMP seasonality is strong in the East North Central region. Similarly, results of circular density method applied to the distribution of AMP timing shows that around 90% of the sites have two or three modes of AMP seasonality in the eUS. Comparison of seasonality between two historical records of equal length (1950–1984 and 1985–2019) shows great spatial variability across the eUS. Temporal changes in seasonal modes for AMP dates revealed four different cases of seasonality changes: (i) weakening of seasonality, (ii) strengthening of seasonality, (iii) strong seasonality for both the old and recent periods, (iv) or uniform or no preferred seasonality for both periods. While a spatial coherence of seasonality changes was not observed, majority of sites showed strong seasonality (case iii) for old and recent periods mainly during summer and fall seasons.https://www.mdpi.com/2073-4433/14/2/366extreme precipitationseasonalitycircular statisticsnon-stationarity |
| spellingShingle | Ali Aljoda Nirajan Dhakal Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United States Atmosphere extreme precipitation seasonality circular statistics non-stationarity |
| title | Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United States |
| title_full | Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United States |
| title_fullStr | Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United States |
| title_full_unstemmed | Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United States |
| title_short | Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United States |
| title_sort | examining seasonality based on probabilistic properties of extreme precipitation timing in the eastern united states |
| topic | extreme precipitation seasonality circular statistics non-stationarity |
| url | https://www.mdpi.com/2073-4433/14/2/366 |
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