The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East Coast
The present study extends the applicability of a statistical model for prediction of storm surge originally developed for The Battery, NY in two ways: I. the statistical model is used as a biascorrection for operationally produced dynamical surge forecasts, and II. the statistical model is applied t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-02-01
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| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2077-1312/3/1/73 |
| _version_ | 1818724819514949632 |
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| author | Haydee Salmun Andrea Molod |
| author_facet | Haydee Salmun Andrea Molod |
| author_sort | Haydee Salmun |
| collection | DOAJ |
| description | The present study extends the applicability of a statistical model for prediction of storm surge originally developed for The Battery, NY in two ways: I. the statistical model is used as a biascorrection for operationally produced dynamical surge forecasts, and II. the statistical model is applied to the region of the east coast of the U.S. susceptible to winter extratropical storms. The statistical prediction is based on a regression relation between the “storm maximum” storm surge and the storm composite significant wave height predicted ata nearby location. The use of the statistical surge prediction as an alternative bias correction for the National Oceanic and Atmospheric Administration (NOAA) operational storm surge forecasts is shownhere to be statistically equivalent to the existing bias correctiontechnique and potentially applicable for much longer forecast lead times as well as for storm surge climate prediction. Applying the statistical model to locations along the east coast shows that the regression relation can be “trained” with data from tide gauge measurements and near-shore buoys along the coast from North Carolina to Maine, and that it provides accurate estimates of storm surge. |
| first_indexed | 2024-12-17T21:32:28Z |
| format | Article |
| id | doaj.art-7c6829d212f74a3ebf2403296e8ce485 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-12-17T21:32:28Z |
| publishDate | 2015-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-7c6829d212f74a3ebf2403296e8ce4852022-12-21T21:31:50ZengMDPI AGJournal of Marine Science and Engineering2077-13122015-02-0131738610.3390/jmse3010073jmse3010073The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East CoastHaydee Salmun0Andrea Molod1Department of Geography, Hunter College of the City University of New York, 695 Park Ave., New York, NY 10065, USAEarth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, USAThe present study extends the applicability of a statistical model for prediction of storm surge originally developed for The Battery, NY in two ways: I. the statistical model is used as a biascorrection for operationally produced dynamical surge forecasts, and II. the statistical model is applied to the region of the east coast of the U.S. susceptible to winter extratropical storms. The statistical prediction is based on a regression relation between the “storm maximum” storm surge and the storm composite significant wave height predicted ata nearby location. The use of the statistical surge prediction as an alternative bias correction for the National Oceanic and Atmospheric Administration (NOAA) operational storm surge forecasts is shownhere to be statistically equivalent to the existing bias correctiontechnique and potentially applicable for much longer forecast lead times as well as for storm surge climate prediction. Applying the statistical model to locations along the east coast shows that the regression relation can be “trained” with data from tide gauge measurements and near-shore buoys along the coast from North Carolina to Maine, and that it provides accurate estimates of storm surge.http://www.mdpi.com/2077-1312/3/1/73extratropical stormsstorm surgestatistical methodsbias correction |
| spellingShingle | Haydee Salmun Andrea Molod The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East Coast Journal of Marine Science and Engineering extratropical storms storm surge statistical methods bias correction |
| title | The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East Coast |
| title_full | The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East Coast |
| title_fullStr | The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East Coast |
| title_full_unstemmed | The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East Coast |
| title_short | The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East Coast |
| title_sort | use of a statistical model of storm surge as a bias correction for dynamical surge models and its applicability along the u s east coast |
| topic | extratropical storms storm surge statistical methods bias correction |
| url | http://www.mdpi.com/2077-1312/3/1/73 |
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