Can Simple Metrics Identify the Process(es) Driving Extreme Precipitation?
This work seeks an automatic algorithm to determine the primary meteorological cause(s) of individual extreme precipitation events. Such determinations have been made before, but required a by-hand analysis of each separate event. This is very time-consuming and the field would benefit from an autom...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Climate |
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| Online Access: | https://www.mdpi.com/2225-1154/11/4/88 |
| _version_ | 1797605847089545216 |
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| author | Leif M. Swenson |
| author_facet | Leif M. Swenson |
| author_sort | Leif M. Swenson |
| collection | DOAJ |
| description | This work seeks an automatic algorithm to determine the primary meteorological cause(s) of individual extreme precipitation events. Such determinations have been made before, but required a by-hand analysis of each separate event. This is very time-consuming and the field would benefit from an automatic process. This is especially relevant when comparing different datasets to determine which ones most closely hew towards reality. This paper tests three simple metrics over the continental United States using the European Center for Medium-Range Weather Forecasting’s (ECMWF) atmospheric reanalysis (ERA5). The metrics tested measure and compare the strength of three meteorological processes associated with extreme precipitation: fronts, convection, and cyclones. A multivariate statistical technique as well as individual case studies show evidence that the three meteorological processes of interest cannot be isolated from one another using these simple physical metrics. This shows the difficulty in finding “pure” cases of these precipitation-generating processes and suggests approaching these processes with an eye toward mixed-type events. |
| first_indexed | 2024-03-11T05:07:53Z |
| format | Article |
| id | doaj.art-45c5aeeedd184a5cb2ad72a1ac5812e8 |
| institution | Directory Open Access Journal |
| issn | 2225-1154 |
| language | English |
| last_indexed | 2024-03-11T05:07:53Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Climate |
| spelling | doaj.art-45c5aeeedd184a5cb2ad72a1ac5812e82023-11-17T18:48:26ZengMDPI AGClimate2225-11542023-04-011148810.3390/cli11040088Can Simple Metrics Identify the Process(es) Driving Extreme Precipitation?Leif M. Swenson0Atmospheric Science Program, Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USAThis work seeks an automatic algorithm to determine the primary meteorological cause(s) of individual extreme precipitation events. Such determinations have been made before, but required a by-hand analysis of each separate event. This is very time-consuming and the field would benefit from an automatic process. This is especially relevant when comparing different datasets to determine which ones most closely hew towards reality. This paper tests three simple metrics over the continental United States using the European Center for Medium-Range Weather Forecasting’s (ECMWF) atmospheric reanalysis (ERA5). The metrics tested measure and compare the strength of three meteorological processes associated with extreme precipitation: fronts, convection, and cyclones. A multivariate statistical technique as well as individual case studies show evidence that the three meteorological processes of interest cannot be isolated from one another using these simple physical metrics. This shows the difficulty in finding “pure” cases of these precipitation-generating processes and suggests approaching these processes with an eye toward mixed-type events.https://www.mdpi.com/2225-1154/11/4/88extreme precipitationclimatemidlatitude weatherreanalysis |
| spellingShingle | Leif M. Swenson Can Simple Metrics Identify the Process(es) Driving Extreme Precipitation? Climate extreme precipitation climate midlatitude weather reanalysis |
| title | Can Simple Metrics Identify the Process(es) Driving Extreme Precipitation? |
| title_full | Can Simple Metrics Identify the Process(es) Driving Extreme Precipitation? |
| title_fullStr | Can Simple Metrics Identify the Process(es) Driving Extreme Precipitation? |
| title_full_unstemmed | Can Simple Metrics Identify the Process(es) Driving Extreme Precipitation? |
| title_short | Can Simple Metrics Identify the Process(es) Driving Extreme Precipitation? |
| title_sort | can simple metrics identify the process es driving extreme precipitation |
| topic | extreme precipitation climate midlatitude weather reanalysis |
| url | https://www.mdpi.com/2225-1154/11/4/88 |
| work_keys_str_mv | AT leifmswenson cansimplemetricsidentifytheprocessesdrivingextremeprecipitation |