Metop First Generation AVHRR FRAC SST Reanalysis Version 1
The first full-mission global AVHRR FRAC sea surface temperature (SST) dataset with a nominal 1.1 km resolution at nadir was produced from three Metop First Generation (FG) satellites: Metop-A (2006-on), -B (2012-on) and -C (2018-on), using the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) SST...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/20/4046 |
| _version_ | 1797513262813675520 |
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| author | Victor Pryamitsyn Boris Petrenko Alexander Ignatov Yury Kihai |
| author_facet | Victor Pryamitsyn Boris Petrenko Alexander Ignatov Yury Kihai |
| author_sort | Victor Pryamitsyn |
| collection | DOAJ |
| description | The first full-mission global AVHRR FRAC sea surface temperature (SST) dataset with a nominal 1.1 km resolution at nadir was produced from three Metop First Generation (FG) satellites: Metop-A (2006-on), -B (2012-on) and -C (2018-on), using the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) SST enterprise system. Historical reprocessing (‘Reanalysis-1’, RAN1) starts at the beginning of each mission and continues into near-real time (NRT). ACSPO generates two SST products, one with global regression (GR; highly sensitive to skin SST), and another one with piecewise regression (PWR; proxy for depth SST) algorithms. Small residual effects of orbital and sensor instabilities on SST retrievals are mitigated by retraining the regression coefficients daily, using matchups with drifting and tropical moored buoys within moving time windows. In RAN, the training windows are centered at the processed day. In NRT, the same size windows are employed but delayed in time, ending four to ten days prior to the processed day. Delayed-mode RAN reprocessing follows the NRT with a two-month lag, resulting in a higher quality and a more consistent SST record. In addition to its completeness, the newly created Metop-FG RAN1 SST dataset shows very close agreement with in situ data (including the fully independent Argo floats), well within the NOAA specifications for accuracy (global mean bias; ±0.2 K) and precision (global standard deviation; 0.6 K) in a ~20% clear-sky domain (percent of clear-sky SST pixels to the total of ice-free ocean). All performance statistics are stable in time, and consistent across the three platforms. The Metop-FG RAN1 data set is archived at the NASA JPL PO.DAAC and NOAA NCEI. This paper documents the newly created dataset and evaluates its performance. |
| first_indexed | 2024-03-10T06:14:12Z |
| format | Article |
| id | doaj.art-54fdde3e24e74b5fac75e9321d6d605c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T06:14:12Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-54fdde3e24e74b5fac75e9321d6d605c2023-11-22T19:53:19ZengMDPI AGRemote Sensing2072-42922021-10-011320404610.3390/rs13204046Metop First Generation AVHRR FRAC SST Reanalysis Version 1Victor Pryamitsyn0Boris Petrenko1Alexander Ignatov2Yury Kihai3NOAA STAR, 5830 University Research Court, College Park, MD 20740, USANOAA STAR, 5830 University Research Court, College Park, MD 20740, USANOAA STAR, 5830 University Research Court, College Park, MD 20740, USANOAA STAR, 5830 University Research Court, College Park, MD 20740, USAThe first full-mission global AVHRR FRAC sea surface temperature (SST) dataset with a nominal 1.1 km resolution at nadir was produced from three Metop First Generation (FG) satellites: Metop-A (2006-on), -B (2012-on) and -C (2018-on), using the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) SST enterprise system. Historical reprocessing (‘Reanalysis-1’, RAN1) starts at the beginning of each mission and continues into near-real time (NRT). ACSPO generates two SST products, one with global regression (GR; highly sensitive to skin SST), and another one with piecewise regression (PWR; proxy for depth SST) algorithms. Small residual effects of orbital and sensor instabilities on SST retrievals are mitigated by retraining the regression coefficients daily, using matchups with drifting and tropical moored buoys within moving time windows. In RAN, the training windows are centered at the processed day. In NRT, the same size windows are employed but delayed in time, ending four to ten days prior to the processed day. Delayed-mode RAN reprocessing follows the NRT with a two-month lag, resulting in a higher quality and a more consistent SST record. In addition to its completeness, the newly created Metop-FG RAN1 SST dataset shows very close agreement with in situ data (including the fully independent Argo floats), well within the NOAA specifications for accuracy (global mean bias; ±0.2 K) and precision (global standard deviation; 0.6 K) in a ~20% clear-sky domain (percent of clear-sky SST pixels to the total of ice-free ocean). All performance statistics are stable in time, and consistent across the three platforms. The Metop-FG RAN1 data set is archived at the NASA JPL PO.DAAC and NOAA NCEI. This paper documents the newly created dataset and evaluates its performance.https://www.mdpi.com/2072-4292/13/20/4046MetopAVHRRFRACSSTReanalysisRAN1 |
| spellingShingle | Victor Pryamitsyn Boris Petrenko Alexander Ignatov Yury Kihai Metop First Generation AVHRR FRAC SST Reanalysis Version 1 Remote Sensing Metop AVHRR FRAC SST Reanalysis RAN1 |
| title | Metop First Generation AVHRR FRAC SST Reanalysis Version 1 |
| title_full | Metop First Generation AVHRR FRAC SST Reanalysis Version 1 |
| title_fullStr | Metop First Generation AVHRR FRAC SST Reanalysis Version 1 |
| title_full_unstemmed | Metop First Generation AVHRR FRAC SST Reanalysis Version 1 |
| title_short | Metop First Generation AVHRR FRAC SST Reanalysis Version 1 |
| title_sort | metop first generation avhrr frac sst reanalysis version 1 |
| topic | Metop AVHRR FRAC SST Reanalysis RAN1 |
| url | https://www.mdpi.com/2072-4292/13/20/4046 |
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