404
MICHAEL J. BELL ET AL.
It has been found that the assimilation of temperature and salinity data
below 1000 metres depth can have major impacts on the barotropic flow and
the meridional overturning in the FOAM system. The version of the FOAM
system implemented in 1997 deliberately excluded observational data below
1000 metres depth because of the deleterious impact of occasional deep
observations in the Gulf Stream region (Bell 1994). With the advent of the
Argo system it is highly desirable to assimilate both temperature and salinity
data at all depths (see next sub-section). It is important for the quality control
of the Argo data to detect suspect observations, particularly those with depth
independent offsets.
Small-scale noise in ocean forecasts is undesirable for several reasons.
Storkey (2004) describes how biases in model integrations can develop from
small-scale noise when upwind vertical advection schemes are employed. He
found that for these advection schemes reducing the horizontal viscosity
below a certain limit led to significant biases within the thermocline.
3.2
Assessments of impact
In order to prioritise developments one would like to be able to predict
what the impact of a given development is likely to be. Should one give
highest priority to the use of additional observational data, to improvements
to the assimilation scheme or to the dynamical model?
Figure 3 shows the impact on verification statistics of assimilating Argo
profile data into the FOAM 1
o model. The statistics are root mean square
differences between profile observations and model fields valid the day
before the observations (i.e. fields in which the observations have not been
assimilated). All the model integrations covered the period January to May
2003, were forced by 6-hourly NWP fluxes and were started from the
operational analysis for 1
st January 2003. A “control” integration assimilated
no data; a second integration assimilated only salinity profile data from
Argo; a third assimilated only temperature profile data from Argo and the
final integration assimilated both temperature and salinity profile data. No
other data were assimilated and an early version of the new assimilation
scheme was used.
It is clear that the Argo data have a major beneficial impact on the model
fields but several points of detail are worth noting. First much of the impact
in the deeper temperature and salinity fields arises from corrections to biases
in the model fields which had accumulated in the operational model since
1995 when the integrations were initialised. Second the assimilation scheme
does not attempt to conserve T/S properties (Troccoli & Haines 1999). It is
likely that assimilation of temperature data only using T/S conservation
ideas could produce better salinity analyses. Third, assimilation of salinity
data only degrades the temperature fields compared to the control and
similarly assimilation of temperature data only degrades the salinity fields.
MICHAEL J. BELL ET AL.
It has been found that the assimilation of temperature and salinity data
below 1000 metres depth can have major impacts on the barotropic flow and
the meridional overturning in the FOAM system. The version of the FOAM
system implemented in 1997 deliberately excluded observational data below
1000 metres depth because of the deleterious impact of occasional deep
observations in the Gulf Stream region (Bell 1994). With the advent of the
Argo system it is highly desirable to assimilate both temperature and salinity
data at all depths (see next sub-section). It is important for the quality control
of the Argo data to detect suspect observations, particularly those with depth
independent offsets.
Small-scale noise in ocean forecasts is undesirable for several reasons.
Storkey (2004) describes how biases in model integrations can develop from
small-scale noise when upwind vertical advection schemes are employed. He
found that for these advection schemes reducing the horizontal viscosity
below a certain limit led to significant biases within the thermocline.
3.2
Assessments of impact
In order to prioritise developments one would like to be able to predict
what the impact of a given development is likely to be. Should one give
highest priority to the use of additional observational data, to improvements
to the assimilation scheme or to the dynamical model?
Figure 3 shows the impact on verification statistics of assimilating Argo
profile data into the FOAM 1
o model. The statistics are root mean square
differences between profile observations and model fields valid the day
before the observations (i.e. fields in which the observations have not been
assimilated). All the model integrations covered the period January to May
2003, were forced by 6-hourly NWP fluxes and were started from the
operational analysis for 1
st January 2003. A “control” integration assimilated
no data; a second integration assimilated only salinity profile data from
Argo; a third assimilated only temperature profile data from Argo and the
final integration assimilated both temperature and salinity profile data. No
other data were assimilated and an early version of the new assimilation
scheme was used.
It is clear that the Argo data have a major beneficial impact on the model
fields but several points of detail are worth noting. First much of the impact
in the deeper temperature and salinity fields arises from corrections to biases
in the model fields which had accumulated in the operational model since
1995 when the integrations were initialised. Second the assimilation scheme
does not attempt to conserve T/S properties (Troccoli & Haines 1999). It is
likely that assimilation of temperature data only using T/S conservation
ideas could produce better salinity analyses. Third, assimilation of salinity
data only degrades the temperature fields compared to the control and
similarly assimilation of temperature data only degrades the salinity fields.