Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model
We document a pilot stochastic re-analysis computed by assimilating sea surface temperature (SST) anomalies into the ocean component of the coupled Norwegian Climate Prediction Model (NorCPM) for the period 1950–2010 (doi:10.11582/2016.00002). NorCPM is based on the Norwegian Earth System Model and...
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ftdoajarticles:oai:doaj.org/article:a5c8c11bf66f4d4381fd9bff7e11117e 2023-05-15T17:24:23+02:00 Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model François Counillon Noel Keenlyside Ingo Bethke Yiguo Wang Sebastien Billeau Mao Lin Shen Mats Bentsen 2016-12-01T00:00:00Z https://doi.org/10.3402/tellusa.v68.32437 https://doaj.org/article/a5c8c11bf66f4d4381fd9bff7e11117e EN eng Stockholm University Press http://www.tellusa.net/index.php/tellusa/article/view/32437/50299 https://doaj.org/toc/1600-0870 1600-0870 doi:10.3402/tellusa.v68.32437 https://doaj.org/article/a5c8c11bf66f4d4381fd9bff7e11117e Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 68, Iss 0, Pp 1-17 (2016) Ocean re-analysis EnKF isopycnal ocean model SST coupled re-analysis weakly coupled data assimilation NorCPM Flow dependent assimilation Oceanography GC1-1581 Meteorology. Climatology QC851-999 article 2016 ftdoajarticles https://doi.org/10.3402/tellusa.v68.32437 2022-12-30T22:22:53Z We document a pilot stochastic re-analysis computed by assimilating sea surface temperature (SST) anomalies into the ocean component of the coupled Norwegian Climate Prediction Model (NorCPM) for the period 1950–2010 (doi:10.11582/2016.00002). NorCPM is based on the Norwegian Earth System Model and uses the ensemble Kalman filter for data assimilation (DA). Here, we assimilate SST from the stochastic HadISST2 historical reconstruction. The accuracy, reliability and drift are investigated using both assimilated and independent observations. NorCPM is slightly overdispersive against assimilated observations but shows stable performance through the analysis period. It demonstrates skills against independent measurements: sea surface height, heat and salt content, in particular in the Equatorial and North Pacific, the North Atlantic Subpolar Gyre (SPG) region and the Nordic Seas. Furthermore, NorCPM provides a reliable monitoring of the SPG index and represents the vertical temperature variability there, in good agreement with observations. The monitoring of the Atlantic meridional overturning circulation is also encouraging. The benefit of using a flow-dependent assimilation method and constructing the covariance in isopycnal coordinates are investigated in the SPG region. Isopycnal coordinates discretisation is found to better capture the vertical structure than standard depth-coordinate discretisation, because it leads to a deeper influence of the assimilated surface observations. The vertical covariance shows a pronounced seasonal and decadal variability that highlights the benefit of flow-dependent DA method. This study demonstrates the potential of NorCPM to compute an ocean re-analysis for the 19th and 20th centuries when SST observations are available. Article in Journal/Newspaper Nordic Seas North Atlantic Directory of Open Access Journals: DOAJ Articles Pacific Tellus A: Dynamic Meteorology and Oceanography 68 1 32437 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Ocean re-analysis EnKF isopycnal ocean model SST coupled re-analysis weakly coupled data assimilation NorCPM Flow dependent assimilation Oceanography GC1-1581 Meteorology. Climatology QC851-999 |
spellingShingle |
Ocean re-analysis EnKF isopycnal ocean model SST coupled re-analysis weakly coupled data assimilation NorCPM Flow dependent assimilation Oceanography GC1-1581 Meteorology. Climatology QC851-999 François Counillon Noel Keenlyside Ingo Bethke Yiguo Wang Sebastien Billeau Mao Lin Shen Mats Bentsen Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model |
topic_facet |
Ocean re-analysis EnKF isopycnal ocean model SST coupled re-analysis weakly coupled data assimilation NorCPM Flow dependent assimilation Oceanography GC1-1581 Meteorology. Climatology QC851-999 |
description |
We document a pilot stochastic re-analysis computed by assimilating sea surface temperature (SST) anomalies into the ocean component of the coupled Norwegian Climate Prediction Model (NorCPM) for the period 1950–2010 (doi:10.11582/2016.00002). NorCPM is based on the Norwegian Earth System Model and uses the ensemble Kalman filter for data assimilation (DA). Here, we assimilate SST from the stochastic HadISST2 historical reconstruction. The accuracy, reliability and drift are investigated using both assimilated and independent observations. NorCPM is slightly overdispersive against assimilated observations but shows stable performance through the analysis period. It demonstrates skills against independent measurements: sea surface height, heat and salt content, in particular in the Equatorial and North Pacific, the North Atlantic Subpolar Gyre (SPG) region and the Nordic Seas. Furthermore, NorCPM provides a reliable monitoring of the SPG index and represents the vertical temperature variability there, in good agreement with observations. The monitoring of the Atlantic meridional overturning circulation is also encouraging. The benefit of using a flow-dependent assimilation method and constructing the covariance in isopycnal coordinates are investigated in the SPG region. Isopycnal coordinates discretisation is found to better capture the vertical structure than standard depth-coordinate discretisation, because it leads to a deeper influence of the assimilated surface observations. The vertical covariance shows a pronounced seasonal and decadal variability that highlights the benefit of flow-dependent DA method. This study demonstrates the potential of NorCPM to compute an ocean re-analysis for the 19th and 20th centuries when SST observations are available. |
format |
Article in Journal/Newspaper |
author |
François Counillon Noel Keenlyside Ingo Bethke Yiguo Wang Sebastien Billeau Mao Lin Shen Mats Bentsen |
author_facet |
François Counillon Noel Keenlyside Ingo Bethke Yiguo Wang Sebastien Billeau Mao Lin Shen Mats Bentsen |
author_sort |
François Counillon |
title |
Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model |
title_short |
Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model |
title_full |
Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model |
title_fullStr |
Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model |
title_full_unstemmed |
Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model |
title_sort |
flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the norwegian climate prediction model |
publisher |
Stockholm University Press |
publishDate |
2016 |
url |
https://doi.org/10.3402/tellusa.v68.32437 https://doaj.org/article/a5c8c11bf66f4d4381fd9bff7e11117e |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
Nordic Seas North Atlantic |
genre_facet |
Nordic Seas North Atlantic |
op_source |
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 68, Iss 0, Pp 1-17 (2016) |
op_relation |
http://www.tellusa.net/index.php/tellusa/article/view/32437/50299 https://doaj.org/toc/1600-0870 1600-0870 doi:10.3402/tellusa.v68.32437 https://doaj.org/article/a5c8c11bf66f4d4381fd9bff7e11117e |
op_doi |
https://doi.org/10.3402/tellusa.v68.32437 |
container_title |
Tellus A: Dynamic Meteorology and Oceanography |
container_volume |
68 |
container_issue |
1 |
container_start_page |
32437 |
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1766115373491421184 |