The design of the baseline experiment benefitted from discussions with Pierre Gauthier of Université du Québec, Montréal; Carla Cardinali of ECMWF; Stéphane Laroche of Environment Canada; and Florence Rabier of Météo-France. The authors thank Yannick Trémolet of ECMWF for his work in developing the adjoint of the GSI analysis scheme used in GEOS-5, and Judy St-James and Monique Tanguay of Environment Canada for their help in developing the GDPS and conducting experiments. We thank Ron Errico of GMAO for many hours of insightful discussions about the work. We thank Carla Cardinali and two anonymous reviewers for their comments and suggestions that improved the paper significantly. This work was supported by the NASA Modeling, Analysis and Prediction program (MAP/04-0000-0080) and by the Naval Research Laboratory and the Office of Naval Research, under Program Element 0602435N, Project Number BE-435-037.
Baker, N. , and R. Daley , 2000: Observation and background adjoint sensitivity in the adaptive observation-targeting problem. Quart. J. Roy. Meteor. Soc., 126 , 1431–1454.
Cardinali, C. , 2009: Monitoring the observation impact on the short-range forecast. Quart. J. Roy. Meteor. Soc., 135 , 239–250.
Courtier, P. , J-N. Thépaut , and A. Hollingsworth , 1994: A strategy for operational implementation of 4D-Var, using an incremental approach. Quart. J. Roy. Meteor. Soc., 120 , 1367–1387.
Daescu, D. N. , 2009: On the deterministic observation impact guidance: A geometrical perspective. Mon. Wea. Rev., 137 , 3567–3574.
Daescu, D. N. , and R. Todling , 2009: Adjoint estimation of the variation in a model functional output due to assimilation of data. Mon. Wea. Rev., 137 , 1705–1716.
Gelaro, R. , and Y. Zhu , 2009: Examination of observation impacts derived from observing system experiments (OSEs) and adjoint models. Tellus, 61A , 179–193.
Gelaro, R. , C. A. Reynolds , R. H. Langland , and G. D. Rohaly , 2000: A predictability study using geostationary satellite wind observations during NORPEX. Mon. Wea. Rev., 128 , 3789–3807.
Gelaro, R. , T. E. Rosmond , and R. Daley , 2002: Singular vector calculations with an analysis error variance metric. Mon. Wea. Rev., 130 , 1166–1186.
Gelaro, R. , Y. Zhu , and R. M. Errico , 2007: Examination of various-order adjoint-based approximations of observation impact. Meteor. Z., 16 , 685–692.
Hilton, F. , N. C. Atkinson , S. J. English , and J. R. Eyre , 2009: Assimilation of IASI at the Met Office and assessment of its impact through observing system experiments. Quart. J. Roy. Meteor. Soc., 135 , 495–505.
Kelly, G. , J-N. Thépaut , R. Buizza , and C. Cardinali , 2007: The value of observations. I: Data denial experiments for the Atlantic and Pacific. Quart. J. Roy. Meteor. Soc., 133 , 1803–1815.
Langland, R. H. , and N. Baker , 2004: Estimation of observation impact using the NRL atmospheric variational data assimilation adjoint system. Tellus, 56 , 189–201.
Le Marshall, J. , and Coauthors , 2006: Improving global analysis and forecasting with AIRS. Bull. Amer. Meteor. Soc., 87 , 891–894.
Mo, T. , 2007: Post-launch calibration of the NOAA-18 Advanced Microwave Sounding Unit-A. IEEE Trans. Geosci. Remote Sens., 45 , 1928–1937.
Morss, R. E. , 1999: Adaptive observations: Idealized sampling strategies for improving numerical weather prediction. Ph.D. thesis, Massachusetts Institute of Technology, 225 pp. [Available from Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139].
Rabier, F. , E. Klinker , P. Courtier , and A. Hollingsworth , 1996: Sensitivity of forecast errors to initial conditions. Quart. J. Roy. Meteor. Soc., 122 , 121–150.
Todling, R. , 2009: An approach to assess observation impact based on observation-minus-forecast residuals. Proc. Workshop on Diagnostics of Data Assimilation System Performance, Reading, UK, ECMWF, 199–202.
Trémolet, Y. , 2008: Computation of observation sensitivity and observation impact in incremental variational data assimilation. Tellus, 60A , 964–978.