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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bell, M.J., M.J. Martin, and N.K. Nichols, 2002: Assimilation of data into an ocean model with systematic errors near the equator. The Met. Office, Ocean Applications Tech. Note.No. 27, March 2001, 27 pp and Submitted to Q. J. R. Meteorol. Soc.
Dee, D., and A. da Silva, 1998: Data assimilation in the presence of forecast bias. Q. J. R. Meteorol. Soc., 124, 269–295.
Fox, A.D., and K. Haines, 2003: Interpretation of Water Mass Transformations diagnosed from Data Assimilation. J. Phys Oceanogr. 33, 485–498.
Levitus, S., and T.P. Boyer, 1994: World Ocean Atlas 1994. Technical Report, US Dept. of Commerce, NOAA.
Marshall, J., D. Jamous, and J. Nilsson, 1999: Reconciling ‘thermodynamic’ and ‘dynamic’ methods of computation of water-mass transformation rates. Deep Sea Res. I, 46, 545–572.
Nurser, A.J.G., R. Marsh, and R.G. Williams, 1999: Diagnosing water mass formation from air-sea fluxes and surface mixing. J. Phys. Oceanogr., 29, 1468–1487.
Reynolds, R. W., and T. M. Smith, 1994: Improved global sea surface temperature analyses using optimum interpolation. J. Climate, 7, 929–948.
Segschneider J., D.L.T. Anderson, J. Vialard, M. Balmaseda, T.N. Stockdale, A. Troccoli, and K. Haines, 2001: Initialization of seasonal forecasts assimilating sea level and temperature observations. J. Climate, 14, 4292–4307.
Speer, K.G., 1997: A note on average cross-isopycnal mixing in the North Atlantic ocean. Deep-Sea Res. I, 44, 1981–1990.
Troccoli, A., and K. Haines, 1999: Use of the Temperature-Salinity relation in a data assimilation context. J. Atmos. Ocean Tech., 16, 2011–2025.
Troccoli A., M. Balmaseda, J. Segschneider, J. Vialard, D.L.T. Anderson, K. Haines, T. Stockdale, F. Vitart, and Fox A.D., 2002: Salinity adjustments in the presence of temperature data assimilation. Mon. Weather Rev., 130, 89–102.
Walin G., 1982: On the relation between sea-surface heat flow and thermal circulation in the ocean. Tellus 34, 187–195.
Webb, D.J., A.C. Coward, B.A. de Cuevas, and C.S. Gwilliam, 1998: A multiprocessor ocean general circulation model using message passing. J Atmos Ocean Tech. 14, 175–183.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Science+Business Media Dordrecht
About this paper
Cite this paper
Haines, K. (2003). Assimilation of Hydrographic Data and Analysis of Model Bias. In: Swinbank, R., Shutyaev, V., Lahoz, W.A. (eds) Data Assimilation for the Earth System. NATO Science Series, vol 26. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0029-1_27
Download citation
DOI: https://doi.org/10.1007/978-94-010-0029-1_27
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-1593-9
Online ISBN: 978-94-010-0029-1
eBook Packages: Springer Book Archive