Abstract
In this chapter we focus on the observations that are available for operational, real-time applications in meteorology, i.e., for numerical weather prediction (NWP). Many in situ observations can be treated as point-wise measurements. Their influence on the analysis is expected to be localized and smoothed according to the specified background error covariance structures (chapters Mathematical Concepts of Data Assimilation, Nichols; Error Statistics in Data Assimilation: Estimation and Modelling, Buehner). Most remotely-sensed sounding data, on the other hand, are integrated measurements that cannot be treated as point-wise observations. This is an important distinction which needs to be accounted for by the analysis scheme. Therefore, we expand the discussion of observation operators to integrals, and examine how such data can be expected to influence the analysis. In operational meteorology, the most prominent examples of integral observations are measurements of infrared and microwave radiation from satellite instruments. Other, recent examples include ground-based GPS (Global Positioning Satellites) and radio-occultation data. The related issues of quality control and data thinning are also covered. Assimilation of time-sequences of observations is discussed. This chapter complements chapters The Global Observing System (Thépaut and Andersson) and Research Satellites (Lahoz).
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Andersson, E., M. Fisher, R. Munro and A. McNally, 2000. Diagnosis of background errors for radiances and other observable quantities in a variational data assimilation scheme, and the explanation of a case of poor convergence. Q. J. R. Meteorol. Soc., 126, 1455–1472.
Andersson, E., A. Hollingsworth, G. Kelly, P. Lönnberg, J. Pailleux and Z. Zhang, 1991. Global observing system experiments on operational statistical retrievals of satellite sounding data. Mon. Weather Rev., 119, 1851–1864.
Andersson, E. and H. Järvinen, 1999. Variational quality control. Q. J. R. Meteorol. Soc. 125, 697–722.
Andersson, E., J. Pailleux, J.-N. Thépaut, J. Eyre, A.P. McNally, G. Kelly and P. Courtier, 1994. Use of cloud-cleared radiances in three/four-dimensional variational data assimilation. Q. J. R. Meteorol. Soc., 120, 627–653.
Bauer, P., P. Lopez, A. Benedetti, D. Salmond and E. Moreau, 2006a. Implementation of 1D+4D-Var assimilation of precipitation affected microwave radiances at ECMWF. I: 1D-Var. Q. J. R. Meteorol. Soc., 132, 2307–2332.
Bauer, P., P. Lopez, D. Salmond, A. Benedetti, S. Saarinen and M. Bonazzola, 2006b. Implementation of 1D+4D-Var assimilation of precipitation affected microwave radiances at ECMWF. II: 4D-Var. Q. J. R. Meteorol. Soc., 132, 2307–2332.
Bengtsson, L., 1980. On the use of a time sequence of surface pressures in four-dimensional data assimilation. Tellus, 32, 189–197.
Bouttier, F. and G. Kelly, 2001. Observing-system experiments in the ECMWF 4-DVAR assimilation system. Q. J. R. Meteorol. Soc., 127, 1469–1488.
Cardinali, C., S. Pezzulli and E. Andersson, 2004. Influence matrix diagnostic of a data assimilation system. Q. J. R. Meteorol. Soc., 130, 2767–2786.
Chapnik, B., G. Desroziers, F. Rabier and O. Talagrand, 2006. Diagnosis and tuning of observational error in a quasi operational data assimilation setting. Q. J. R. Meteorol. Soc., 132, 543–565.
Chédin, A. and N.A. Scott, 1985. Initialization of the radiative transfer equation inversion problem from a pattern recognition type approach. In Advances in Remote Sensing Retrieval Methods. Application to the satellites of the TIROS-N series, A. Deepak (ed.), Academic Press, New York, pp 495–515.
Dee, D.P., L. Rukhovets, R. Todling, A.M. da Silva and J.W. Larson, 2001. An adaptive buddy check for observational quality control. Q. J. R. Meteorol. Soc., 127, 2451–2471.
Desroziers, G., L. Berre, B. Chapnik and P. Poli, 2005. Diagnosis of observation, background and analysis-error statistics in observation space. Q. J. R. Meteorol. Soc., 131, 3385–3396.
Dharssi, I., A.C. Lorenc and N.B. Ingleby, 1992. Treatment of gross errors using maximum probability theory. Q. J. R. Meteorol. Soc., 118, 1017–1036.
Eyre, J.R., 1989. Inversion of cloudy satellite sounding radiances by nonlinear optimal estimation. Q. J. R. Meteorol. Soc., 115, 1001–1037.
Eyre, J.R., 1991. A fast radiative transfer model for satellite sounding systems. ECMWF Tech. Memo, 176, available from ECMWF.
Eyre, J.R. and A.C. Lorenc, 1989. Direct use of satellite sounding radiances in numerical weather prediction. Meteorol. Mag., 118, 13–16.
Fisher, M. and P. Courtier, 1995. Estimating the covariance matrices of analysis and forecast error in variational data assimilation. ECMWF Tech. Memo., 220, available from ECMWF.
Fleming, H.E., M.D. Goldberg and D.S. Crosby, 1986. Minimum variance simultaneous retrieval of temperature and water vapor from satellite radiance measurements. In Proceedings of 2nd Conference on “Satellite Meteorology – Remote Sensing and Applications”, Williamsburg, American Meteorological Society, Boston, pp 20–23.
Flobert, J.-F., E. Andersson, A. Chédin, A. Hollingsworth, G. Kelly, J. Pailleux and N.A. Scott, 1991. Global data assimilation and forecast experiments using the Improved Initialization Inversion method for satellite soundings. Mon. Weather Rev., 119, 1881–1914.
Gelman, A., J.B. Carlin, H.S. Stern and D.B. Rubin, 1995. Bayesian Data Analysis. Texts in Statistical Science, Chapman and Hall, London.
Healy, S.B., J.R. Eyre, M. Hamrud and J.-N. Thépaut, 2006. Assimilating GPS radio occultation measurements with two-dimensional bending angle observation operators. EUMETSAT/ECMWF Fellowship Programme Research Reports, 16, p. 21.
Hólm, E.V., A. Untch, A. Simmons, R. Saunders, F. Bouttier and E. Andersson, 1999. Multivariate ozone assimilation in four-dimensional data assimilation. In Proceeding SODA Workshop on “Chemical Data Assimilation”, de Bilt, The Netherlands, 9–10 December 1998, pp 89–94.
Huber, P.J., 1977. Robust Statistical Methods. Society for Industrial and Applied Mathematics, Pennsylvania, USA.
Ingleby, N.B. and A.C. Lorenc, 1993. Bayesian quality control using multivariate normal distributions. Q. J. R. Meteorol. Soc., 119, 1195–1225.
Järvinen, H., E. Andersson and F. Bouttier, 1998. Variational assimilation of time sequences of surface observations with serially correlated errors. ECMWF Tech. Memo., 266, available from ECMWF.
Järvinen, H. and P. Undén, 1997. Observation screening and first guess quality control in the ECMWF 3D-Var data assimilation system. ECMWF Tech. Memo., 236, available from ECMWF.
Köpken, C., G. Kelly and J.-N. Thépaut, 2004. Assimilation of Meteosat radiance data within the 4D-Var system at ECMWF: Assimilation experiments and forecast impact. Q. J. R. Meteorol. Soc., 130, 2277–2292.
Lorenc, A.C., 1986. Analysis methods for numerical weather prediction. Q. J. R. Meteorol. Soc., 112, 1177–1194.
McNally, A.P., E. Andersson, G.A. Kelly and R.W. Saunders, 1999. The use of raw TOVS/ATOVS radiances in the ECMWF 4D-Var assimilation system. ECMWF Newsletter, 83, pp 2–7.
McNally, A.P., J.C. Derber, W. Wu and B.B. Katz, 2000. The use of TOVS level-1B radiances in the NCEP SSI analysis system. Q. J. R. Meteorol. Soc., 126, 689–724.
Munro, R., G. Kelly, M. Rohn and R. Saunders, 1999. Assimilation of geostationary water vapour radiance data at ECMWF. Technical Proceeding of the 10th international, Boulder, Colorado, 27 January–2 February 1999.
Poli, P., P. Moll, F. Rabier, G. Desroziers, B. Chapnik, L. Berre, S.B. Healy, E. Andersson and F.-Z. El Guelai, 2007. Forecast impact studies of zenith total delay data from European near real-time GPS stations in Meteo-France 4DVar. J. Geophys. Res., 112, 10.1029/2006JD007430.
Rabier, F., H. Järvinen, E. Klinker, J.F. Mahfouf and A. Simmons, 2000. The ECMWF operational implementation of four-dimensional variational assimilation. Part I: Experimental results with simplified physics. Q. J. R. Meteorol. Soc. 126, 1143–1170.
Rabier, F., E. Klinker, P. Courtier and A. Hollingsworth, 1996. Sensitivity of forecast errors to initial conditions. Q. J. R. Meteorol. Soc., 122, 121–150.
Rabier, F., J.-N. Thépaut and P. Courtier, 1998. Extended assimilation and forecast experiments with a four-dimensional variational assimilation system. Q. J. R. Meteorol. Soc., 124, 1861–1887.
Reale, A.L., D.G. Gray, M.W. Chalfant, A. Swaroop and A. Nappi, 1986. Higher resolution operational satellite retrievals. Preprints, 2nd Conference on “Satellite Meteorology/Remote Sensing and Applications”, Williamsburg, 13–16 May 1986, American Meteorological Society, Boston, pp 16–19.
Riishøjgaard, L.P., 1996. On four-dimensional variational assimilation of ozone data in weather prediction models. Q. J. R. Meteorol. Soc. 122, 1545–1571.
Rodgers, C.D., 1976. Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation. Rev. Geophys. Space Phys., 14, 609–624.
Rodgers, C.D., 1990. Characterization and error analysis of profiles retrieved from remote sounding measurements. J. Geophys. Res., 95, 5587–5595.
Saunders, R., M. Matricardi and P. Brunel, 1999. An improved fast radiative transfer model for assimilation of satellite radiance observations. Q. J. R. Meteorol. Soc. 125, 1407–1426.
Simmons, A.J. and A. Hollingsworth, 2002. Some aspects of the improvement in skill of numerical weather prediction. Q. J. R. Meteorol. Soc. 128, 647–677.
Thépaut, J.-N., P. Courtier, G. Belaud and G. Lemaître, 1996. Dynamical structure functions in a four-dimensional variational assimilation: A case study. Q. J. R. Meteorol. Soc. 122, 535–561.
Thépaut, J.-N., R.N. Hoffman and P. Courtier, 1993. Interactions of dynamics and observations in a four-dimensional variational assimilation. Mon. Weather Rev., 121, 3393–3414.
WMO, 2004. Proceedings of the 3rd WMO Workshop on the Impact of Various Observing Systems on Numerical Weather Prediction, Alpbach 9–12 March 2004. Böttger, M. and Pailleux, J. (eds.) WMO/TD No. 1228.
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Andersson, E., Thépaut, JN. (2010). Assimilation of Operational Data. In: Lahoz, W., Khattatov, B., Menard, R. (eds) Data Assimilation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74703-1_11
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