Sensitivity Observing System Experiment (SOSE)—a new effective NWP-based tool in designing the global observing system
By: Gert-Jan Marseille, Ad Stoffelen and Jan Barkmeijer
References
-
Barkmeijer
, J., Buizza, R.and Palmer, T. N.. 3D-Var Hessian singu-lar vectors and their potential use in the ECMWF Ensemble Prediction System. Q. J. R. Meteorol. Soc. 125, 2333– 2351. -
Barkmeijer
, J., Iversen, T.and Palmer, T. N.. Forcing singular vectors and other sensitive model structures. Q. J. R. Meteorol. Soc. 129, 2401– 2423. -
Bergot
, T., Hello, G., Joly, A.and Malardel, S.. Adaptive observa-tions: a feasibility study. Mon. Wea. Rev. 127, 743– 765. -
Caron
, J. F., Yau, M. K., Laroche, S.and Zwack, P.. The character-istics of key analysis errors. Part I: dynamical balance and comparison with observations. Mon. Wea. Rev. 135, 249– 266. -
Cress
, A.and Wergen, W.. Impact of profile observations on the German Weather Service’s NWP system. Meteor. Zeitschrift, 91– 101. -
Daley
, R.. Atmospheric Data Analysis. Cambridge Atmospheric and Space Science Series, Cambridge University Press, Cambridge, UK. ISBN 0-521-45825-0, 457 p. -
Fisher
, M.,. Background error covariance modelling. In: Proceedings of ECMWF Seminar “Recent developments in data assimilation for atmosphere and ocean, 8-12 September 2003”, Reading, UK, 45-64. -
Gelaro
, R., Reynolds, C. A., Langland, R. H.and Rohaly, G. D.. A Predictability Study Using Geostationary Satellite Wind Observations during NORPEX.. 128, 3789- 3807. -
Hello
, G., Lalaurette, F.and Thepaut, J. N.. Estimation of key analysis errors using the adjoint technique. Q. J. R. Meteorol. Soc. 126, 621– 647. -
Isaksen
, L., Fisher, M., Andersson, E.and Barkmeijer, J.. The structure and realism of sensitivity perturbations and their interpre-tation as “Key Analysis Errors”. Q. J. R. Meteorol. Soc. 131, 3053– 3078. -
Kelly
, G.. OSEs of all main data types in the ECMWF operational system. In: Proceedings of the Third WMO Workshop on the Impact of Various Observing Systems on 1VWP, Alpbach, Austria, 63-94. -
Klinker
, E., Rabier, F.and Gelaro, R.. Estimation of key analysis errors using the adjoint technique. Q. J. R. Meteorol. Soc. 124, 1909– 1933. -
Koch
, R., Ehrendorfer, M.and Weissmann, M.. Key analysis errors and airborne LIDAR measurements of wind. http://www.pa.op.d1r.de/na-trec/KochEtA12006_poster.pdf -
Le Dimet
, F.and Talagrand, O.. Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects., 97- 110. -
Lorene
, A.. Analysis methods for numerical weather prediction. Q. J. R. Meteorol. Soc. 112, 1177– 1194. -
Marseille
, G. J.and Stoffelen, A.. Simulation of wind profiles from a space-borne Doppler wind lidar. Q. J. R. Meteorol. Soc. 129, 3079– 3098. -
Marseille
, G. J., Stoffelen, A.and Barkmeijer, J.. A cycled sen-sitivity observing system experiment on simulated Doppler wind lidar data during the 1999 Christmas storm “Martin”., DOI: 10.1111/j.1600-0870.2007.00290.x. -
Masutani
, M., Lord, S. J., Woollen, J. S., Yang, W., Sun, H., and co-authors. 2004.Global OSSE at NCEP. In: Proceedings of the Eighth Symposium on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface AMS, Seattle, USA -
Palmer
, T. N., Gelaro, R., Barkmeijer, J.and Buizza, R.. Singular vectors, metrics, and adaptive observations.. 55, 633- 653. -
Rabier
, F., Courtier, P., Herveou, M., Strauss, B.and Persson, A.. Sensitivity of forecast error to initial conditions using the adjoint model.. -
Rabier
, F., Klinker, E., Courtier, P.and Hollingsworth, A.. Sensi-tivity of forecast errors to initial conditions. Q. J. R. Meteorol. Soc. 122, 121– 150. -
Rabier
, F.,, H., Klinker, E., Mahfouf, J.-F.and Simmons, A.. The ECMWF operational implementation of four-dimensional variational assimilation. I: experimental results with simplified physics.. 126, 1143- 1170. -
Shapiro
, M.and Thorpe, A.. THORPEX International Science Plan, vs. 3. WMO/TD-No. 1246, WWRP/I’HORPEX No. 2. -
Stoffelen
, A., Pailleux, J., Källen, E., Vaughan, J. M., Isaksen, L., and co-authors. 2005. The Atmospheric dynamics mission for global wind measurement.. 86, 73- 87. -
Stoffelen
, A., Marseille, G. J., Bouttier, F., Vasiljevic, D., de Haan, S.and Cardinali, C.. Q. J. R. Meteorol. Soc. 132, 1927– 1947. -
Tan
, D. G. H., Andersson, E., Fisher, M.and Isaksen, L. 2007. Ob-serving system impact assessment using a data assimilation ensemble technique: application to the ADM-Aeolus wind profiling mission.. 133, 381- 390. -
Trémolet
, Y.. Accounting for an imperfect model in 4D-Var. Q. J. R. Meteorol. Soc. 132, 2483– 2504. -
WMO
, 2004. Current Statement of Guidance Regarding How Well Satel-lite Capabilities Meet WMO User Requirements in Ten Application Areas. WMO satellite reports.
DOI: https://doi.org/10.1111/j.1600-0870.2007.00288.x | Journal eISSN: 3035-9554
Language: English
Page range: 216 - 233
Submitted on: Jan 15, 2007
Accepted on: Oct 15, 2007
Published on: Jan 1, 2008
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
© 2008 Gert-Jan Marseille, Ad Stoffelen, Jan Barkmeijer, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.