3. The Ocean Observations and Quality Control

3.1 Subsurface data

3.2 Sea level data

3.3 Sea Surface temperature

3.1 Subsurface data

Subsurface temperature observations that are available in near-real-time are currently provided by the TAO/TRITON and PIRATA arrays in the equatorial region (McPhaden 1998, Servain et al 1998) and the global Volunteer Observing Ship (VOS) programme which provides XBT (eXpandable BathyThermographs) measurements mainly along merchant shipping routes. More recently, observations are provided by the ARGO network of drifting profilers. Salinity data is available from ARGO and from the TRITON moorings.

Prior to 2004, the temperature and salinity profiles come from the quality controlled ENACT/ENSEMBLES data set (Ingleby and Huddleston 2006). From January 2005, the observations come from the GTS (Global Telecommunication System). An automatic quality control procedure (an extension of Smith et al., 1991) is then performed in several stages:

1. Daily averaging. First of all, daily averages are created if applicable: if some site reports more frequently than once per day, daily averages are created (this is the case for the TRITON moorings, which report hourly).
2. Black list of coastal observations. Data in the vecinity of the coast are rejected, as a way of accounting for representativeness error
3. Background check. A level-by-level check between the distance between model values and observations in relation to the error statistics.
4. Buddy check. A consistency test between observations is peformed.
5. Super-obbing. Profiles which are close in space and time are superobbed, following the same criteria as in Smith et al., 1991.
6. Completness of profiles. in S3 there is an additional check for completeness of the profiles: a profile is considered incomplete, and therefore rejected, if the sparsity of the remaining observations in the vertical is judged insufficient to resolve the vertical temperature gradients. (An observation profile will be rejected if the temperature difference between consecutive levels is larger than 5 deg C or if it contains a vertical temperature gradient larger than 0.1 deg C/m).

The observation coverage and the quality control decisions for the different assimilation cycles can be seen here. The figures show that thanks to the ARGO system the coverage of salinity is now comparable to that of temperature, and it is almost global. In recent times the TRITON moorings in the West Pacific and Indian ocean also provide salinity in real time. The PIRATA and TAO moorings report only temperature in real time, even when the sensors are also able to measure salinity. Most of the data from XBTs and Mooring are superobbed, whilst the ARGO profiles are often partially rejected by our QC system.

3.2 Sea level data

Information about sea level is provided by the altimetric data. The altimeter information is given by maps of merged satellite product, provided by Ssalto/DUACS and distributed by AVISO. Twice a week (on Wednesday and on Saturday mornings) Maps of Sea Level Anomaly (MSLA) for a merged product combining all satellites (Envisat, Jason, Topex/Poseidon, ERS2, GFO). Prior to assimilation, these maps are smoothed to remove unrepresented features and interpolated onto the model grid. These are then interpolated in time to produce daily maps. Only the map corresponding to the centre of the assimilation window is assimilated09.03.2007 referred to a 7 year mean (1993-2000). To enable comparison with the background field a reference mean sea level is required.
In S3, this is the 7-year mean sea level from an ocean analysis spanning the period 1993-2000. The possibility of using a reference mean sea level derived from the GRACE gravity mission has also been explored, but it was found that sensitivities to the reference mean sea level are large, and could potentially introduce abrupt jumps in the analysis.

The trend in global sea level is quite substantial. If this trend is produced by thermal expansion due to global warming, it can not be represented by the ocean model: in absence of fresh water fluxes, most ocean models used for climate are volume preserving, since they make use of the Boussinesq approximation. Therefore, if not treated correctly, the trend in sea level can be a problem when assimilating altimeter observations. In S3, the global sea level trend is removed from the altimeter sea level anomalies before they are assimilated via the CH96 scheme. In S3, the global sea level trend is later assimilated as described in Balmaseda et al 2007.

3.3 Sea Surface temperature

An accurate initial SST is of great importance for the accuracy of the forecasts. In the present system, we09.03.200709.03.2007l#Reynolds">Reynolds et al 2002). The analysis is linearly interpolated to daily values before use. Because the SST analysis is produced only once a week (on Mondays, with a valid central time of the previous Wednesday), and because we need the following Wednesday to produce the interpolated value for a Thursday, this implies a delay of up to 11 days in the availability of the SST field. Daily SST fields are available in near real time from the NWP system, but these are less stable, and there are significant inconsistencies in the data from different periods. We prefer to use the higher quality data, even if it is slightly delayed. Despite using what we consider to be the best SST analysis available, there are still significant errors, estimated to be of the order of 0.3 K.

The arrival of SST information is one of the major factors for introducing a delay in the analysis. The real-time analysis does not wait for the second map of SST to be available. Instead, a daily SST product is created by adding the latest SST anomaly to the daily climatology.