A new method for constraining the ocean in coupled system model for long reanalysis and climate predictions

Nansen and Bjerknes scientists have for the first time demonstrated the capability - thanks to an advanced data assimilation method - to constrain ocean variability in key regions (e.g. North Atlantic, Equatorial and North Pacific) of a fully coupled Earth system model just using sea surface temperatures. This result opens new possibilities for a long fully coupled reanalysis dating back to 1850 and test thoroughly the skills of decadal predictions by the Norwegian Climate Prediction model. The research team lead by Dr. François Counillon have published the paper Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model in Tellus A. The study demonstrates the importance of using dynamical covariances data assimilation method – meaning that corrections changes with the state of the system - and that constructing  the assimilation framework in isopycnal coordinate enhances its efficiency when assimilating surface observations.

Subpolar Gyre index in NorCPM (red), FREE (blue) and observations (black line) (see full explanation in the paper (Figure 6)). The darker shading represents the first and third quartile of the model ensemble and the lighter shading represents the ensemble envelope (min/max).Subpolar Gyre index in NorCPM (red), FREE (blue) and observations (black line) (see full explanation in the paper (Figure 6)). The darker shading represents the first and third quartile of the model ensemble and the lighter shading represents the ensemble envelope (min/max).The authors have demonstrated a pilot stochastic re-analysis computed by assimilating SST anomalies into the ocean model component of the coupled Norwegian Climate Prediction Model (NorCPM) for the period 1950-2010. NorCPM model is based on the Norwegian Earth System Model and the authors have used the ensemble Kalman filter for data assimilation. The stochastic HadISST2 historical reconstruction SST data have been assimilated into NorESM. The accuracy, reliability and drift have been investigated using both assimilated and independent observations. NorCPM is slightly overdispersive against assimilated observations but shows stable performance through the entire analysis period. The new method demonstrates skills against independent oceanic measurements such as sea surface height, heat and salt content, in particular in the Equatorial and North Pacific, the North Atlantic Subpolar Gyre (SPG) region (see figure) and the Nordic Seas. Furthermore, NorCPM provides a reliable reconstruction of the SPG index and represents the vertical temperature variability in the Subpolar gyre, in good agreement with independent observations. The ability to reproduce 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, here through the SST data. The vertical covariance shows a pronounced seasonal and decadal variability that highlights the benefit of flow-dependent data assimilation method developed by the scientists. This study demonstrates the potential of NorCPM to compute an improved ocean re-analysis data set for the 19th and 20th centuries when SST observations are available.

Citation: Francois Counillon, Noel Keenlyside, Ingo Bethke, Yiguo Wang, Sebastien Billeau, Mao Lin Shen and
 Mats Bentsen. (2016): Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model, Tellus A 2016, 68, 32437, http://dx.doi.org/10.3402/tellusa.v68.32437.

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