Abstract
GLORYS12 is a global eddy-resolving physical ocean and sea ice reanalysis at 1/12° horizontal resolution covering the 1993-present altimetry period, designed and implemented in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). The model component is the NEMO platform driven at the surface by atmospheric conditions from the ECMWF ERA-Interim reanalysis. Ocean observations are assimilated by means of a reduced-order Kalman filter. Along track altimeter sea level anomaly, satellite sea surface temperature and sea ice concentration, as well as in situ temperature and salinity vertical profiles are jointly assimilated. A 3D-VAR scheme provides an additional correction for the slowly-evolving large-scale biases in temperature and salinity. The performance of the reanalysis shows a clear dependency on the time-dependent in situ observation system. The general assessment of GLORYS12 highlights a level of performance at the state-of-the-art and the capacity of the system to capture the main expected climatic interannual variability signals for ocean and sea ice, the general circulation and the inter-basins exchanges. In terms of trends, GLORYS12 shows a higher than observed warming trend together with a slightly lower than observed global mean sea level rise. Comparisons made with an experiment carried out on the same platform without assimilation show the benefit of data assimilation in controlling water mass properties and sea ice cover and their low frequency variability. Moreover, GLORYS12 represents particularly well the small-scale variability of surface dynamics and compares well with independent (non-assimilated) data. Comparisons made with a twin experiment carried out at 1/4° resolution allows characterizing and quantifying the strengthened contribution of the 1/12° resolution onto the downscaled dynamics. GLORYS12 provides a reliable physical ocean state for climate variability and supports applications such as seasonal forecasts. In addition, this reanalysis has strong assets to serve regional applications and provide relevant physical conditions for applications such as marine biogeochemistry. In the near future, GLORYS12 will be maintained to be as close as possible to real time and could therefore provide relevant and continuous reference past ocean states for many operational applications.
Highlights
The Copernicus Marine Environment Monitoring Service provides regular and systematic reference information on the physical state, variability and dynamics of the ocean, sea ice and marine ecosystems, for the global ocean and the European regional seas
We plan to continue developing modelling and assimilation techniques to provide the best estimate of global oceanic stratification and circulation at high resolution, to refine the description of key quantities, and to evaluate them by comparing with assimilated and independent datasets
The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation
Summary
The Copernicus Marine Environment Monitoring Service (http:// marine.copernicus.eu, hereafter referred to as Copernicus Marine Service or CMEMS) provides regular and systematic reference information on the physical state, variability and dynamics of the ocean, sea ice and marine ecosystems, for the global ocean and the European regional seas. A fresh bias is present at the surface which is stronger in the 1990s, while a very strong salty bias appears in the first 500 m and increases in time (Figures 1E,F) These biases are reduced in GLORYS12, but they slightly remain in the form of a seasonal bias in temperature, showing a potential error in the FIGURE 3 | Time evolution of SLA data assimilation statistics averaged over the whole domain: (A) data number, (B) mean innovations, (C) RMS of the SLA data (in black), RMS of residuals (in red), RMS of residuals divided by RMS of SLA observations (in light grey, with the scale on the right). The Antarctic sea ice extent in spring 2016 attained a record minimum (Turner et al, 2017) for the 1993–2016 period, presenting an abrupt departure from the slowly but steadily expanding until several monthly record high in 2014 Combined with this high variability, the resulting weak positive trend found in all reanalyses and all observations is not significant (95%-level confidence).
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