Publications on Automatic Differentiation of Atmospheric GCMs

Simon Blessing, Richard Greatbatch, Klaus Fraedrich, and Frank Lunkeit. Interpreting the atmospheric circulation trend during the last half of the 20th century: Application of an adjoint model. J. Climate., 21(18):4629-4646, September 2008.
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Simon Blessing. Adjoint Modelling for Assimilation and Diagnosis on Climate Timescales. PhD thesis, University of Hamburg, Germany, April 2008.
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N. Sugiura, T. Awaji, S. Masuda, T. Mochizuki, T. Toyoda, T. Miyama, H. Igarashi, and Y. Ishikawa. Development of a four-dimensional variational coupled data assimilation system for enhanced analysis and prediction of seasonal to interannual climate variations. J. Geophys. Res., 113, 2008.
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T. Kaminski, S. Blessing, R. Giering, M. Scholze, and M. Voßbeck. Testing the use of adjoints for estimation of GCM parameters on climate time-scales. Meteorol. Z., 16(6):643-652, 2007.

D.N. Daescu and I.M. Navon. Efficiency of a pod-based reduced second-order adjoint model in 4d-var data assimilation. Int. J. Numer. Methods Fluids, 53(6):985-1004, 2007.
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U. Achatz and G. Schmitz. Shear and static instability of inertia-gravity wave packets: Short-term modal and nonmodal growth. J. Atmos. Sci., 63:397-413, 2006.

X. Huang, Q. Xiao, W. Huang, D. Barker, J. G. Michalakes, J. Bray, Z. Ma, Y. Guo, H. Lin, and Y. Kuo. Preliminary results of WRF 4D-Var. In Proceedings of 7th annual WRF Users' Workshop, Boulder, California, USA, 2006. National Center for Atmospheric Research.
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Y. Xiao, M. Xue, W. Martin, and J. Gao. Development of Adjoint for a Complex Atmospheric Model, the ARPS, using TAF. In H. Martin Bücker, George F. Corliss, Paul Hovland, Uwe Naumann, and Boyana Norris, editors, Automatic Differentiation: Applications, Theory, and Implementations, volume 50 of Lecture Notes in Computational Science and Engineering, pages 263-272. Springer, New York, NY, 2005.
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Describes generation of tangent-linear and adjoint models of the Fortran-90 regional weather forecast model ARPS.

U. Achatz. On the role of optimal perturbations in the instability of monochromatic gravity waves. Physics Of Fluids, 17(9), 2005.
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R. Giering, T. Kaminski, R. Todling, R. Errico, R. Gelaro, and N. Winslow. Generating tangent linear and adjoint versions of NASA/GMAO's Fortran-90 global weather forecast model. In H. M. Bücker, G. Corliss, P. Hovland, U. Naumann, and B. Norris, editors, Automatic Differentiation: Applications, Theory, and Implementations, volume 50 of Lecture Notes in Computational Science and Engineering, pages 275-284. Springer, New York, NY, 2005.
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Describes generation of the tangent linear and adjoint versions of a state-of-the-art Fortran-90 weather forecast model.

M. Zupanski, D. Zupanski, T. Vukicevic, K. Eis, and T.I.V. Haar. CIRA/CSU Four-Dimensional Variational Data Assimilation System. Monthly Weather Review, 133(4):829-843, 2005.
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Q. Xiao, Z. Ma, W. Huang, X. Huang, D. Barker, Y. Kuo, and J. G. Michalakes. Development of the WRF Tangent Linear and Adjoint Models:. Nonlinear and Linear Evolution of Initial Perturbations and. Adjoint Sensitivity Analysis at high-southern latitudes. In Proceedings of 6th WRF / 15th MM5 Users' Workshop, Boulder, California, USA, 2005. National Center for Atmospheric Research.
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S. Akella and I.M. Navon. A comparative study of the performance of high resolution advection schemes in the context of data assimilation. Int. J. Numer. Meth. Fluids, 51(7):719-748, 2005.
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S. Blessing, K. Fraedrich, and F. Lunkeit. Climate diagnostics by adjoint modelling: A feasibility study. In H. Fischer, T. Kumke, G. Lohmann, G. Flöser, H. Miller, H. von Storch, and J. F. W. Negendank, editors, The KIHZ project: Towards a synthesis of Holocene Proxy Data and Climate Models, pages 383-396, Heidelberg, 2004. Springer.
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D.N. Daescu and I.M. Navon. Adaptive observations in the context of 4d-var data assimilation. Meteorology And Atmospheric Physics, 85(4):205-226, 2004.
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Shu-Chih Yang, M. Corazza, and E. Kalnay. Errors of the day, bred vectors and singular vectors: implications for ensemble forecasting and data assimilation. In 20th Conference on Weather Analysis and Forecasting/16th Conference on Numerical Weather Prediction Symposium on Forecasting the Weather and Climate of the Atmosphere and Ocean. American Meteorological Society, 2004.
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N. Grieger, G. Schmitz, and U. Achatz. The dependence of the nonmigrating diurnal tide in the mesosphere and lower thermosphere on stationary planetary waves. Journal of Atmospheric and Solar-Terrestrial Physics, 66:733-754, 2004.
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Tangent linear and adjoint of a GCM have been generated by TAMC.

Y.Q. Zhu, R. Todling, J. Guo, S.E. Cohn, I.M. Navon, and Y. Yang. The geos-3 retrospective data assimilation system: The 6-hour lag case. Mon. Wea. Rev., 131(9):2129-2150, 2003.
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Part of the model's adjoint was hand written and part by TAMC

R. Giering, T. Kaminski, R. Todling, and S.-J. Lin. Generating the tangent linear and adjoint models of the DAO finite volume GCM's dynamical core by means of TAF. Geophysical Research Abstracts, 5:11680, 2003.
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R. Todling, R. Giering, T. Kaminski, Y. Zhu, and J Guo. Retrospective data assimilation for GEOS-4. Geophysical Research Abstracts, 5:11354, 2003.
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A. Benedetti, G.L. Stephens, and T. Vukicevic. Variational assimilation of radar reflectivities in a cirrus model. i: Model description and adjoint sensitivity studies. Q. J. R. Meteorol. Soc., 129(587):277-300, 2003.
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F.-X. LeDimet, I.M. Navon, and D.N. Daescu. Second order information in data assimilation. Mon. Wea. Rev., 130(3):629-648, 2002.
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T. Nehrkorn, G. D. Modica, M. Cemiglia, F. H. Ruggiero, J. G. Michalakes, and X. Zou. 4DVAR Development Using an Automatic Code Generator: Application to MM5v3. In Proceedings of Twelfth PSU/NCAR Mesoscale Model Users' Workshop, Boulder, California, USA, 2002. National Center for Atmospheric Research.
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F. H. Ruggiero, G. D. Modica, T. Nehrkorn, M. Cemiglia, J. G. Michalakes, and X. Zou. MM5-Based 4DVAR: Current Status and Future Plans. In Proceedings of Twelfth PSU/NCAR Mesoscale Model Users' Workshop, Boulder, California, USA, 2002. National Center for Atmospheric Research.
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M. Zupanski, D. Zupanski, D.F. Parrish, E. Rogers, and G. Dimego. Four-dimensional variational data assimilation for the blizzard of 2000. Mon. Wea. Rev., 130(8):1967-1988, 2002.
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D. Zupanski, M. Zupanski, E. Rogers, D.F. Parrish, and G.J. Dimego. Fine-Resolution 4DVAR Data Assimilation For The Great Plains Tornado Outbreak Of 3 May 1999. Weather Forecast., 17(3):506-525, 2002.
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M. Grecu and E.N. Anagnostou. Use of passive microwave observations in a radar rainfall- profiling algorithm. J. Appl. Meteorol., 41(7):702-715, 2002.
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T. Nehrkorn, G. D. Modica, M. Cemiglia, F. H. Ruggiero, J. G. Michalakes, and X. Zou. MM5 adjoint development using TAMC: Experiences with an automatic code generator. In Proceedings of 14th Conference on Numerical Weather Prediction, pages 481-484. American Meteorological Society, 2001.
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F. H. Ruggiero, G. D. Modica, T. Nehrkorn, M. Cemiglia, J. G. Michalakes, and X. Zou. A MM5-Based Four-Dimensional Variational Analysis System Developed for Distributed Memory Multiprocessor Computers. In Proceedings of 14th Conference on Numerical Weather Prediction. American Meteorological Society, 2001.
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Y. Tang and W.W. Hsieh. Coupling neural networks to incomplete dynamical systems via variational data assimilation. Mon. Wea. Rev., 129:818-834, 2001.
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T. Vukicevic, M. Steyskal, and M. Hecht. Properties of advection algorithms in the context of variational data assimilation. Mon. Wea. Rev., 129(5):1221-1231, 2001.
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S. Blessing. Development and applications of an adjoint GCM. Master's thesis, University of Hamburg, Germany, 2000.
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D. J. Lea, M. R. Allen, and T. W. N. Haine. Sensitivity analysis of the climate of a chaotic system. Tellus, 52A:523-532, 2000.
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