Operational Assimilation of Spectral Wave Data From the Sofar Spotter Network
Abstract Historically, the sparseness of in situ open‐ocean wave and weather observations has severely limited the forecast skill of weather over the ocean with major social and economic consequences for coastal communities and maritime industries. Ocean surface waves, specifically, are important fo...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-08-01
|
| Series: | Geophysical Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2022GL098973 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850198443564204032 |
|---|---|
| author | Isabel A. Houghton Christie Hegermiller Camille Teicheira Pieter B. Smit |
| author_facet | Isabel A. Houghton Christie Hegermiller Camille Teicheira Pieter B. Smit |
| author_sort | Isabel A. Houghton |
| collection | DOAJ |
| description | Abstract Historically, the sparseness of in situ open‐ocean wave and weather observations has severely limited the forecast skill of weather over the ocean with major social and economic consequences for coastal communities and maritime industries. Ocean surface waves, specifically, are important for the interaction between atmosphere and ocean, and thus key in modeling weather and climate processes. Here, we investigate the improvements achievable from a large distributed sensor network combined with advances in assimilation strategies. Wave spectra from a global network of over 600 Sofar Spotter buoys are assimilated into an operational global wave forecast via optimal interpolation to update model spectra to best fit observations. We demonstrate end‐to‐end improvements in forecast skill of significant wave height of 38%, and up to 45% for other bulk parameters. This shows distributed observations of the air‐sea interface, with advances in assimilation strategies, can reduce uncertainty in forecasts to dramatically improve earth system modeling. |
| format | Article |
| id | doaj-art-c3d02aeb488f42708dfdacf42a8ce747 |
| institution | OA Journals |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2022-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-c3d02aeb488f42708dfdacf42a8ce7472025-08-20T02:12:53ZengWileyGeophysical Research Letters0094-82761944-80072022-08-014915n/an/a10.1029/2022GL098973Operational Assimilation of Spectral Wave Data From the Sofar Spotter NetworkIsabel A. Houghton0Christie Hegermiller1Camille Teicheira2Pieter B. Smit3Sofar Ocean Technologies San Francisco CA USASofar Ocean Technologies San Francisco CA USASofar Ocean Technologies San Francisco CA USASofar Ocean Technologies San Francisco CA USAAbstract Historically, the sparseness of in situ open‐ocean wave and weather observations has severely limited the forecast skill of weather over the ocean with major social and economic consequences for coastal communities and maritime industries. Ocean surface waves, specifically, are important for the interaction between atmosphere and ocean, and thus key in modeling weather and climate processes. Here, we investigate the improvements achievable from a large distributed sensor network combined with advances in assimilation strategies. Wave spectra from a global network of over 600 Sofar Spotter buoys are assimilated into an operational global wave forecast via optimal interpolation to update model spectra to best fit observations. We demonstrate end‐to‐end improvements in forecast skill of significant wave height of 38%, and up to 45% for other bulk parameters. This shows distributed observations of the air‐sea interface, with advances in assimilation strategies, can reduce uncertainty in forecasts to dramatically improve earth system modeling.https://doi.org/10.1029/2022GL098973data assimilationwave modelingdistributed sensingwave buoyswave spectra observationsair‐sea interface |
| spellingShingle | Isabel A. Houghton Christie Hegermiller Camille Teicheira Pieter B. Smit Operational Assimilation of Spectral Wave Data From the Sofar Spotter Network Geophysical Research Letters data assimilation wave modeling distributed sensing wave buoys wave spectra observations air‐sea interface |
| title | Operational Assimilation of Spectral Wave Data From the Sofar Spotter Network |
| title_full | Operational Assimilation of Spectral Wave Data From the Sofar Spotter Network |
| title_fullStr | Operational Assimilation of Spectral Wave Data From the Sofar Spotter Network |
| title_full_unstemmed | Operational Assimilation of Spectral Wave Data From the Sofar Spotter Network |
| title_short | Operational Assimilation of Spectral Wave Data From the Sofar Spotter Network |
| title_sort | operational assimilation of spectral wave data from the sofar spotter network |
| topic | data assimilation wave modeling distributed sensing wave buoys wave spectra observations air‐sea interface |
| url | https://doi.org/10.1029/2022GL098973 |
| work_keys_str_mv | AT isabelahoughton operationalassimilationofspectralwavedatafromthesofarspotternetwork AT christiehegermiller operationalassimilationofspectralwavedatafromthesofarspotternetwork AT camilleteicheira operationalassimilationofspectralwavedatafromthesofarspotternetwork AT pieterbsmit operationalassimilationofspectralwavedatafromthesofarspotternetwork |