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Assimilation of Hydrographic Data and Analysis of Model Bias

  • Keith Haines
Part of the NATO Science Series book series (NAIV, volume 26)

Abstract

In this chapter we look at the assimilation of subsurface temperature profile data. Particular attention will be paid to covariances with salinity, and to the analysis of model bias in these fields. Up to now most subsurface data consists of temperature (T) profiles only without coincident salinity, although in the near future the ARGO float program will provide regular salinity measurements and the algorithms described here will need to be augmented. As discussed earlier in chapter Altimeter Covariances and Errors Treatment, section 1, the vast majority of T profile data from Expendable bathythermographs (XBTs) or from moorings tend to be of limited depth. These data are the main resource for ocean assimilation for seasonal forecasting activities and we shall illustrate the methods used by reference to results from the European Centre for Medium-range Weather Forecasts (ECMWF) seasonal forecasting system.

Keywords

Data Assimilation Surface Heat Flux Heat Budget Seasonal Forecast Assimilation Experiment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2003

Authors and Affiliations

  • Keith Haines
    • 1
  1. 1.Environmental Systems Science CentreReading UniversityReadingUK

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