| 29 Jun 2026
The consistent in-situ global gridded temperature and salinity dataset, CORA OA 1960–2024
Abstract. Gridded ocean products play a pivotal role in oceanographic and climate research, providing a framework for the cross- validation and calibration of satellite observations and in-situ data. This paper describes the latest evolution of the global gridded ocean objective analysis fields for temperature and salinity, distributed by the Copernicus Marine Service. It accounts for the update of the objective analysis first guess using monthly fields derived from the temporal interpolation of World Ocean Atlas 2023 (WOA23) decadal temperature and salinity climatologies. The new product provides monthly objective analysis fields for temperature and salinity with a 0.5° horizontal resolution and 187 vertical levels covering depths from 0 to 5500 m. The time series spans from 1960 to December of the previous year. A full reprocessing is conducted every November, while an interim update covering the first six months of the current year is released each June. This product was compared with other reference 3D temperature and salinity datasets, as well as SST and SSS products. It exhibits strong consistency with all reference data, particularly over the 1985–2024 period. Notably, the product proved robust against the "Argo fast salty drift" frequently detected in other datasets after 2016. The gridded product is freely accessible on the Copernicus Marine data store (https://data.marine.copernicus.eu/) under the ID INSITU_GLO_PHY_TS_OA_MY_013_052.
Overall comment
This is a timely paper which honestly presents the temperature and salinity analysis product CORA
Great care is given in the reference time evolving mean field over which the objective mapping is done.
The product is very smooth in time, once spatially averaged, which suggests that with the mapping scales and parameters used the data density was insufficient to fully cover the relevant space and time scales globally before the post-200 Argo and other network period (at least, when one gets below the surface).
This dooes not come as a surprise and is correctly taken into account into the error budget I believe. Thus the average for the earlier period (once it is spatially averaged over a basin, and for T below the surface) is mostly the climatology product used (from the decadal NODC climatology) except after 2000.
What is really interesting is the comparison done with other products. What is presented and discussed is mostly visual and qualitative (except for a table with the trends). I suggest that this could be made more quantitative, and in addition to trends, the authos could provide rms differences between the different time series (for example on figure 5 and 6, or even for the OHC), estimates of detrended variability for the different products (at least spatial averages, but why not also examples of spatial maps).
Minor comments
Bottom of page 3: it would be interesting to know to which extent the data set is MEOP-based, thus qualified/adjusted, and to which extent it is not the case. I was aware of turtle data in the southwest Indian Ocean for example, not in MEOP, and presenting large salinity biases. I believe that I see some of their tracks on Fig3 top right panel), but the worse biased ones (in salinity) might have been filtered out. Although it is a small number of bad data, it can locally degrade the product (towards lower S).
Lines 106: a bit strange. Should it be instead of Tclim, Sclim, Tstd and Sstd. (otherwise what are Tstd and Sstd?). As there is a combination of two terms, not obvious to the reader what is the proportion of the data that is filtered out in this step. I believe that it should be reported somewhere (maybe a percentage as a function of the depth?)
Lines 125-129 duplicated in lines 130-133.
Figure 4: there is a change of data density increasing just after 2000m before the early 1990s (also near 800m). Is it linked to the change of grid spacing with depth and the criterium on maximum vertical data spacing. If the case, I would argue that it is rather arbitrary, and would suggest (for later versions) to revise the selection criteria on line 177. In the figure 4 caption, for the lower panel, it indicates the median of the profiles anomalies, whereas on line 163, this is described as the ‘objective analysis profiles’. Is it the same thing and thus after mapping analysis, or before the mapping.
On Figure 5, means are not estimated over the same period for the ISAS20 product than for the others (thus shifted negative (and even for the IAPV4 product with the last two years missing). It gives some visual impression of disagreement (for example for ISAS20) that should be avoided. Instead of anomalies, as these are basin-scale averages, why not present instead of anomalies total SST on Figure 5 (as is done on figure 6 for SSS). For the Southern Ocean, I am wondering whether the different products use different defaults for temperature under sea ice, and how is the spatial average done. Is SST in all products, a foundation SST? And how is it estimated if not directly measured?
On Fig. 6, IAP presents a strange large negative peak in SSS in 2001, not seen in all the other products, coming from Pacific and Indian Ocean north of 35°S. Any reason? This suggests some bug (TAO or Rama uncorrected and bised mooring data, perhaps?). Also, in caption, add that deep ocean is areas with bottom depth > 1500 m.
On most figures, when referring to the Southern Ocean, the panel title reads ‘South ocean’, which should be changed. On other panels, ocean is not capitalized. It should be: Atlantic Ocean, etc…
Some comparison mentioned at the beginning, such as SSS with the Sammartino et al product, are not really described (they appear on one figure).