Publications on TAF applications

G. Forget, J.M. Campin, P. Heimbach, C.N. Hill, R.M. Ponte, and C. Wunsch. Ecco version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation. Geosci. Model Dev. Discuss., 8:3653-3743, 2015. [ DOI | .html ]

S. Kemp, M. Scholze, T. Ziehn, and T. Kaminski. Limiting the parameter space in the carbon cycle data assimilation system (ccdas). Geoscientific Model Development, 7(4):1609-1619, 2014. [ DOI | http ]

Simon Blessing, Thomas Kaminski, Frank Lunkeit, Ion Matei, Ralf Giering, Armin Köhl, Marko Scholze, Klaus Fraedrich, and Detlef Stammer. Testing variational estimation of process parameters and initial conditions of an Earth System Model. accepted for publication in TellusA, 2014. [ .pdf ]

Alexander G. Kalmikov and Patrick Heimbach. A hessian-based method for uncertainty quantification in global ocean state estimation. SIAM J. Sci. Comput., 36(5):267–295, 2014. [ DOI ]

T. Kato, W. Knorr, M. Scholze, E. Veenendaal, T. Kaminski, J. Kattge, and N. Gobron. Simultaneous assimilation of satellite and eddy covariance data for improving terrestrial water and carbon simulations at a semi-arid woodland site in botswana. Biogeosciences, 10(2):789-802, 2013. [ DOI | http ]

E. N. Koffi, P. J. Rayner, M. Scholze, F. Chevallier, and T. Kaminski. Quantifying the constraint of biospheric process parameters by co2 concentration and flux measurement networks through a carbon cycle data assimilation system. Atmospheric Chemistry and Physics, 13(21):10555-10572, 2013. [ DOI | http ]

Chris Wilson, Kevin J. Horsburgh, Jane Williams, Jonathan Flowerdew, and Laure Zanna. Tide-surge adjoint modeling: A new technique to understand forecast uncertainty. Journal of Geophysical Research: Oceans, 2013. [ DOI | http | http ]

Keywords: sea level, adjoint, surge, sensitivity, ensemble, tide

T. Kaminski, W. Knorr, G. Schürmann, M. Scholze, P. J. Rayner, S. Zaehle, S. Blessing, W. Dorigo, V. Gayler, R. Giering, N. Gobron, J. P. Grant, M. Heimann, A. Hooker-Strout, S. Houweling, T. Kato, J. Kattge, D. Kelley, S. Kemp, E. N. Koffi, C. Köstler, P.P. Mathieu, B. Pinty, C. H. Reick, C. Rödenbeck, R. Schnur, K. Scipal, C. Sebald, T. Stacke, A. Terwisscha van Scheltinga, M. Vossbeck, H. Widmann, and T. Ziehn. The BETHY/JSBACH Carbon Cycle Data Assimilation System: experiences and challenges. J. Geophys. Res., 118:doi:10.1002/jgrg.20118, 2013. [ http | .pdf ]

Michael Buchwitz, Maximilian Reuter, Oliver Schneising, Hartmut Boesch, Sandrine Guerlet, Bart Dils, Ise Aben, Raymond Armante, Peter Bergamaschi, Thomas Blumenstock, Heinrich Bovensmann, Dominik Brunner, Brigitte Buchmann, John P Burrows, Andre Butz, Alain Chedin, Frederic Chevallier, Cyril D Crevoisier, Nicholas Deutscher, Christian Frankenberg, Otto P Hasekamp, Jens Heymann, Thomas Kaminski, Alexandra Laeng, Günter Lichtenberg, Martine De Maziere, Stefan Noel, Justus Notholt, Johannes Orphal, Christoph Popp, Robert Parker, Marko Scholze, Ralf Sussmann, Gabriele P Stiller, Thorsten Warneke, Claus Zehner, Andrey Bril, David Crisp, David Griffith, Akihiko Kuze, Christopher O'Dell, Sergey Oshchepkov, Vanessa Sherlock, Hiroshi Suto, Paul Wennberg, Debra Wunch, Tatsuya Yokota, and Yukio Yoshida. The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparison and quality assessment of near-surface sensitive satellite-derived CO2 and CH4 global data sets. submitted to Remote Sensing of Environment, page in press, 2013.

D. N. Goldberg and P. Heimbach. Parameter and state estimation with a time-dependent adjoint marine ice sheet model. The Cryosphere Discussions, 7(3):2845-2890, 2013. [ DOI | http ]

T. Kaminski, W. Knorr, M. Scholze, N. Gobron, B. Pinty, R. Giering, and P.-P. Mathieu. An Interactive Tool to Analyse the Benefit of Space Missions Sensing the Terrestrial Vegetation. Presentation at IEEE International Geosciences and Remote Sensing Symposium, Munich, July 2012. [ .ppt/.pdf ]

T. Kaminski, W. Knorr, M. Scholze, N. Gobron, B. Pinty, R. Giering, and P.-P. Mathieu. Simultaneous Assimilation of MERIS FAPAR into a Terrestrial Vegetation Model. Geophysical Research Abstracts, 14:11748, April 2012. [ .ppt/.pdf | .pdf ]

T. Kaminski, M. Scholze, and S. Houweling. Quantifying the Benefit of an Active CO2 Mission Concept in a Carbon Cycle Data Assimilation System. Geophysical Research Abstracts, 14:11973, April 2012. [ .ppt/.pdf | .pdf ]

T. Kaminski, P. J. Rayner, M. Voßbeck, M. Scholze, and E. Koffi. Observing the continental-scale carbon balance: assessment of sampling complementarity and redundancy in a terrestrial assimilation system by means of quantitative network design. Atmospheric Chemistry and Physics, 12(16):7867-7879, 2012. [ DOI | http ]

The paper presents evaluations of observational networks in the network designer. The networks are composed of three data types: direct CO2 flux measurements as well as continuous and flask samples of the atmospheric CO2 concentration

E. Koffi, P. J. Rayner, M. Scholze, and C. Beer. Atmospheric constraints on gross primary productivity and net flux: Results from a carbon-cycle data assimilation system. Glob. Biogeochem. Cyc., 26:doi:10.1029/2010GB003900, 2012. [ DOI | .pdf ]

T. Ziehn, M. Scholze, and W. Knorr. Comparison of monte carlo and adjoint inversion techniques for the efficient estimation of terrestrial ecosystem model parameters and their uncertainties. Global Biogeochemical Cycles, in review, 26:GB3025, 2012. [ http | .pdf ]

T. Kaminski, W. Knorr, M. Scholze, N. Gobron, B. Pinty, R. Giering, and P.-P. Mathieu. Consistent assimilation of MERIS FAPAR and atmospheric CO2 into a terrestrial vegetation model and interactive mission benefit analysis. Biogeosciences, 9(8):3173-3184, 2012. [ DOI | http ]

The contribution demonstrates the first simultaneous assimilation of FAPAR data and atmospheric CO2 and an application of the CCDAS framework to design of space missions with optical sensors.

M.M. Verstraete, L.A. Hunt, R.J. Scholes, M. Clerici, B. Pinty, and D.L. Nelson. Generating 275-m resolution land surface products from the multi-angle imaging spectroradiometer data. Geoscience and Remote Sensing, IEEE Transactions on, 50(10):3980-3990, 2012. [ DOI | http ]

P. E. Lewis, J. Gomez-Dans, T. Kaminski, J. Settle, T. Quaife, N. Gobron, J. Styles, and M. Berger. An Earth Observation Land Data Assimilation System (EO-LDAS). Remote Sensing of Environment, 120:219-235, 2012. [ http ]

The paper describes and applies the prototype of a system for variational assimilation of remote sensing products.

P. Rayner, E. Koffi, M. Scholze, T. Kaminski, and J.L. Dufresne. Constraining predictions of the carbon cycle using data. Phil. Trans. R. Soc. A, 369(1943):1955-1966, 2011. [ DOI | http | .pdf ]

T. Ziehn, M. Scholze, and W. Knorr. Development of an ensemble-adjoint optimization approach to derive uncertainties in net carbon fluxes. Geoscientific Model Development, 4(4):1011-1018, 2011. [ DOI | http ]

T. Ziehn, J. Kattge, W. Knorr, and M. Scholze. Improving the predictability of global co2 assimilation rates under climate change. Geophys Res Lett, (38):1513-1531, 2011. [ DOI | http | .pdf ]

T. Ziehn, W. Knorr, and M. Scholze. Investigating spatial differentiation of model parameters in a carbon cycle data assimilation system. Global Biogeochemical Cycles, 25(2):GB2021, 2011. [ http | .pdf ]

C. M. Luke. Modelling Aspects of Land-Atmosphere Interaction: Thermal Instability in Peatland Soils and Land Parameter Estimation Through Data Assimilation. PhD thesis, University of Exeter, UK, 2011. [ http ]

P. E. Lewis, J. Gomez-Dans, T. Kaminski, J. Settle, T. Quaife, N. Gobron, J. Styles, and M. Berger. Development of prototype EO land data assimilation system. page 17. University of Reading, UK, 2011. [ .pdf ]

F. Kauker, R. Gerdes, M. Karcher, T. Kaminski, R. Giering, and M. Voßbeck. August 2010 Sea Ice Outlook - AWI/FastOpt/OASys. Sea Ice Outlook web page, August 2010. [ http | .pdf ]

The Sea Ice Outlook is a kind of competition within the Arctic science community to predict the minimum sea ice extent for the upcoming September. These predictions start with the beginning of the melting season in June and are updated in monthly intervals. This document provides the third prediction in the 2010 series. As in 2009, the AWI/FastOpt/OASys team are using the variational data assimilation sytems NAOSIMDAS to initialise their forecasts.

F. Kauker, R. Gerdes, M. Karcher, T. Kaminski, R. Giering, and M. Voßbeck. July 2010 Sea Ice Outlook - AWI/FastOpt/OASys. Sea Ice Outlook web page, July 2010. [ http | .pdf ]

The Sea Ice Outlook is a kind of competition within the Arctic science community to predict the minimum sea ice extent for the upcoming September. These predictions start with the beginning of the melting season in June and are updated in monthly intervals. This document provides the second prediction in the 2010 series. As in 2009, the AWI/FastOpt/OASys team are using the variational data assimilation sytems NAOSIMDAS to initialise their forecasts.

F. Kauker, R. Gerdes, M. Karcher, T. Kaminski, R. Giering, and M. Voßbeck. June 2010 Sea Ice Outlook - AWI/FastOpt/OASys. Sea Ice Outlook web page, June 2010. [ http | .pdf ]

The Sea Ice Outlook is a kind of competition within the Arctic science community to predict the minimum sea ice extent for the upcoming September. These predictions start with the beginning of the melting season in June and are updated in monthly intervals. This document provides the first prediction in the 2010 series. As in 2009, the AWI/FastOpt/OASys team are using the variational data assimilation sytems NAOSIMDAS to initialise their forecasts.

W. Knorr, T. Kaminski, M. Scholze, N. Gobron, B. Pinty, R. Giering, and P.-P. Mathieu. Carbon cycle data assimilation with a generic phenology model. J. Geophys. Res., 115, 2010. [ DOI | http | .pdf ]

The paper demonstrates the simultaneous assimilation of FAPAR data from the MERIS sensor at a number of sites. It is the first application that includes hydrology and phenology models in the core of CCDAS rather than running them in a pre step

W. Knorr, T. Kaminski, M. Scholze, N. Gobron, B. Pinty, R. Giering, and P.-P. Mathieu. Carbon cycle data assimilation using satellite-derived fapar and a new generic global phenology scheme. Geophysical Research Abstracts, 12, 2010. [ .ppt/.pdf | .pdf ]

T. Kaminski, W. Knorr, M. Scholze, N. Gobron, B. Pinty, R. Giering, and P.-P. Mathieu. Assimilation of MERIS FAPAR into a Terrestrial Vegetation Model and Mission Design. In Proceedings of 2010 European Space Agency Living Planet Symposium, Bergen, Norway. European Space Agency, 2010. [ .pdf ]

T. Kaminski, W. Knorr, M. Scholze, N. Gobron, B. Pinty, R. Giering, and P.-P. Mathieu. Assimilation of MERIS FAPAR into a Terrestrial Vegetation Model and Mission Design. In Proceedings of ESA, iLEAPS, EGU joint Conference, Frascati, Italy, 3-5 November 2010. European Space Agency, 2010. [ .pdf ]

B. Pinty, I. Andredakis, M. Clerici, T. Kaminski, M. Taberner, P. Lewis, S. Pinnock, and S. Plummer. Relating MERIS FAPAR products to radiation transfer schemes used in climate/numerical weather prediction and carbon models. In Proceedings of ESA, iLEAPS, EGU joint Conference, Frascati, Italy, 3-5 November 2010. European Space Agency, 2010. [ .pdf ]

J. Rückelt, V. Sauerland, T. Slawig, A. Srivastav, B. Ward, and C. Patvardhan. Parameter optimization and uncertainty analysis in a model of oceanic co2 uptake using a hybrid algorithm and algorithmic differentiation. Nonlinear Analysis: Real World Applications, 11(5):3993-4009, 2010. [ DOI | http ]

L. Zanna, P. Heimbach, A.M. Moore, and E. Tziperman. Optimal growth of tropical atlantic sst anomalies. Journal Of Physical Oceanography, 40(5):983-1003, 2010. [ .pdf ]

T. Kaminski, M. Scholze, and S. Houweling. Quantifying the Benefit of A-SCOPE Data for Reducing Uncertainties in Terrestrial Carbon Fluxes in CCDAS. Tellus B, 62(5):784-796, 2010. [ DOI | http | .pdf ]

W. Knorr, T. Kaminski, M. Scholze, N. Gobron, B. Pinty, R. Giering, and P.-P. Mathieu. Local-scale Carbon Cycle Data Assimilation using satellite-derived FAPAR with a generic phenology model. In Proceedings of 8th Carbon dioxide conference at Jena, 2009. [ .ppt/.pdf | .pdf ]

M. Scholze, T. Kaminski, P. Rayner, W. Knorr, and R. Giering. Projecting terrestrial carbon cycling with uncertainties: Results from a Carbon Cycle Data Assimilation System (CCDAS). In Proceedings of 8th Carbon dioxide conference at Jena, 2009. [ .pdf ]

T. Kaminski, P. Rayner, M. Scholze, M. Voßbeck, E. Koffi, R. Giering, and S. Houweling. Supporting the improvement of the carbon observing system by quantitative network design. In Proceedings of 8th Carbon dioxide conference at Jena, 2009. [ .ppt/.pdf | .pdf ]

The paper presents the first application of the network designer plus the evaluation of a space mission

E. Koffi, P. Rayner, M. Scholze, T. Kaminski, F. Chevallier, C. Roedenbeck, M. Voßbeck, R. Giering, W. Knorr, and M. Heimann. Sensitivity of Climate Data Assimilation System to Transport models and Observational networks. In Proceedings of 8th Carbon dioxide conference at Jena, 2009. [ .pdf ]

T. Ziehn, M. Scholze, and W. Knorr. Regionalization of the key carbon storage parameter within the Carbon Cycle Data Assimilation System (CCDAS). In Proceedings of 8th Carbon dioxide conference at Jena, 2009. [ .ppt/.pdf | .pdf ]

T. Kato, M. Scholze, and W. Knorr. The impact of CO2 fertilization on the global terrestrial carbon cycle and interannual changes in CO2 studied through a carbon cycle data assimilation system. In Proceedings of 8th Carbon dioxide conference at Jena, 2009. [ .ppt/.pdf | .pdf ]

Ralf Giering, Thomas Kaminski, Bernhard Eisfeld, Nicolas Gauger, Jochen Raddatz, and Lars Reimer. Automatic Differentiation of FLOWer and MUGRIDO. In Kroll, N and Schwamborn, D and Becker, K and Rieger, H and Thiele, F, editor, MEGADESIGN AND MEGAOPT - GERMAN INITIATIVES FOR AERODYNAMIC SIMULATION AND OPTIMIZATION IN AIRCRAFT DESIGN, volume 107 of Notes on Numerical Fluid Mechanics and Multidisciplinary Design, pages 221-235, 2009. [ .pdf ]

F. Kauker, T. Kaminski, M. Karcher, R. Giering, R. Gerdes, and M. Voßbeck. Adjoint analysis of the 2007 all time arctic sea-ice minimum. Geophysical Research Letters, 2009. [ DOI | http | .pdf ]

F. Kauker, R. Gerdes, M. Karcher, T. Kaminski, R. Giering, and M. Voßbeck. Retrospective Summary Comments SIO 2009 - AWI/FastOpt/OASys. Sea Ice Outlook web page, 2009. [ http | .pdf ]

The Sea Ice Outlook is a kind of competition within the Arctic science community to predict the minimum sea ice extent for the upcoming September. These predictions start with the beginning of the melting season in June and are updated in monthly intervals. This document provides a restrospective analysis. The monthly predictions are available on the same web page. For the 2009 Sea Ice Outlook, AWI/OASys teamed up with FastOpt and used, for the first time, the variational data assimilation sytems NAOSIMDAS to initialise the forecasts.

W. Knorr, T. Kaminski, M. Scholze, N. Gobron, B. Pinty, and R. Giering. Remote Sensing Input for regional to global CO2 flux modelling. In Proceedings of 2nd MERIS/(A)ATSR User Workshop, Frascati, Italy. European Space Agency, 2008. [ .pdf ]

The paper demonstrates the assimilation of FAPAR data from the MERIS sensor at a number of sites. It is the first application that includes hydrology and phenology models in the core of CCDAS rather than running them in a pre step

T. Kaminski and P. J. Rayner. Assimilation and network design. In H. Dolman, A. Freibauer, and R. Valentini, editors, Observing the continental scale Greenhouse Gas Balance of Europe, Ecological Studies, chapter 3, pages 33-52. Springer-Verlag, New York, 2008. [ DOI | http | .pdf ]

Overview paper on quantitative network design for the carbon cycle

Fernando Sedano, Thomas Lavergne, Luis Maria Ibaêez, and Peng Gong. A neural network-based scheme coupled with the rpv model inversion package. Remote Sensing of Environment, 112(7):3271 - 3283, 2008. [ DOI | http ]

F. Kauker, T. Kaminski, M. Karcher, R. Giering, R. Gerdes, and M. Voßbeck. Adjoint analysis of the summer 2007 low in arctic sea-ice area. Geophysical Research Abstracts, 10, 2008. [ .pdf ]

A. Hooker-Stroud. Anthropogenic CO2: Seasonal Fossil Fuel Emissions in CCDAS. Master's thesis, University of Bristol, UK, 2008. [ .pdf ]

D. Kelley. Wildfires as part of the global carbon cycle: quantitative analysis using data assimilation. Master's thesis, University of Bristol, UK, 2008. [ .pdf ]

A. Köhl, D. Stammer, and B. Cornuelle. Interannual to Decadal Changes in the ECCO Global Synthesis. J. Phys. Oceanogr., 37(2):313-337, 2007. [ .pdf ]

M. Losch and P. Heimbach. Adjoint Sensitivity of an Ocean General Circulation Model to Bottom Topography. Journal Of Physical Oceanography, 37(2):377-393, 2007. [ http ]

C. Wunsch and P. Heimbach. Practical global ocean state estimation. Physica D., 230(1-2):197-208, 2007. [ DOI ]

M. Scholze, T. Kaminski, P. Rayner, W. Knorr, and R. Giering. Propagating uncertainty through prognostic CCDAS simulations. J. Geophys. Res., 112:doi:10.1029/2007JD008642, 2007. [ DOI | .pdf ]

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.

M. Sambridge, P. Rickwood, N. Rawlinson, and S. Sommacal. Automatic differentiation in geophysical inverse problems. Geophysical Journal International, 170(1):1-8, 2007. [ DOI | .pdf ]

K.F. Evans. SHDOMPPDA: A radiative transfer model for cloudy sky data assimilation. J. Atmos. Sci., 64(11):3854-3864, 2007.

I. Hoteit and A. Köhl. Efficiency of reduced-order, time-dependent adjoint data assimilation approaches. Journal Of Oceanography, 62(4):539-550, 2006. [ .pdf ]

S. Dutkiewicz, M.J. Follows, P. Heimbach, and J. Marshall. Controls on ocean productivity and air-sea carbon flux: An adjoint model sensitivity study. Geophysical Research Letters, 33(16):doi:10.1029/2005GL024987, 2006. [ http | .pdf ]

P. Heimbach G. Gebbie and C. Wunsch. Strategies for nested and eddy-resolving state estimation. J. Geophys. Res., 111(C10073), 2006. [ DOI | .pdf ]

T. Kaminski, R. Giering, and C. Othmer. Topological design based on highly efficient adjoints generated by automatic differentiation. In G. Winter, J. Périaux, W. Haase, B Galván, B. González, D. Greiner, and I Fránquiz, editors, ERCOFTAC 2006, Design an Optimisation: Methods and Applications, pages 223-226, Spain, 2006. University of Las Palmas de Gran Canaria. [ .pdf ]

TAF application to 3d CFD simulation in the automotive design process.

C. Othmer, T. Kaminski, and R. Giering. Computation of topological sensitivities in fluid dynamics: Cost function versatility. In P. Wesseling, E. O nate, and J. Périaux, editors, ECCOMAS CFD 2006. TU Delft, 2006. [ .pdf ]

TAF application to 3d CFD simulation in the automotive design process. The paper demonstrates the dependence of the optimal topology on the formulation of the cost function.

T. Lavergne, T. Kaminski, B. Pinty, M. Taberner, N. Gobron, M. M. Verstraete, M. Voßbeck, J.-L. Widlowski, and R. Giering. Application to MISR Land Products of an RPV Model Inversion Package using Adjoint and Hessian Codes. Remote Sensing of Environment, (107):362-375, 2006. [ DOI | .pdf ]

The paper describes and applies an inverse modeling package for estimation of parameters of a radiative transfer model and their uncertainty ranges. The required gradient and Hessian code have been generated by TAF.

R. Giering and T. Kaminski. Automatic sparsity detetection implemented as source-to-source transformation. In Vassil N. Alexandrov, Geert Dick van Albada, Peter M. A. Sloot, and Jack Dongarra, editors, Computational Science - ICCS 2006, volume 3394 of Lecture Notes in Computer Science, pages 591-598, Heidelberg, 2006. Springer. [ DOI | .pdf ]

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. [ .pdf ]

P. Rayner, M. Scholze, W. Knorr, T. Kaminski, R. Giering, and H. Widmann. Two decades of terrestrial Carbon fluxes from a Carbon Cycle Data Assimilation System (CCDAS). Global Biogeochemical Cycles, 19(GB2026):20 PP, 2005. [ DOI | http | .pdf ]

W. Knorr, N. Gobron, M. Scholze, P. Rayner, T. Kaminski, R. Giering, H. Widmann, and J. Kattge. Carbon and fAPAR assimilation within CCDAS. In P. Viterbo, editor, Proceedings of ECMWF/ELDAS Workshop on Land Surface Assimilation, 8-11 November 2004, pages 213-219. European Centre for Medium-Range Weather Forecasts, 2005. [ http | .pdf ]

J. P. Thomas, K. C. Hall, and E. H. Dowell. A discrete adjoint approach for modeling unsteady aerodynamic design sensitivities. AIAA Journal., 43(9):1931-1936, 2005.

A TAF generated adjoint is used to study steady and unsteady aerodynamic design sensitivities for compressible viscous flows around airfoil configurations.

P. Heimbach and C. Hill and R. Giering. An efficient exact adjoint of the parallel MIT general circulation model, generated via automatic differentiation. Future Generation Computer Systems, 21(8):1356-1371, 2005. [ http | .pdf ]

I. Hoteit, B. Cornuelle, A. Köhl, and D. Stammer. Treating strong adjoint sensitivities in tropical eddy-permitting variational data assimilation. Quarterly Journal Of The Royal Meteorological Society, 131(613):3659-3682, 2005. [ DOI | http ]

A. Köhl. Anomalies of meridional overturning: Mechanisms in the north atlantic. Journal Of Physical Oceanography, 35(8):1455-1472, 2005. [ DOI | http ]

R. Giering, T. Kaminski, and T. Slawig. Generating Efficient Derivative Code with TAF: Adjoint and Tangent Linear Euler Flow Around an Airfoil. Future Generation Computer Systems, 21(8):1345-1355, 2005. [ DOI | http | .pdf ]

We give a TAF overview and describe in some detail, how iterative solvers can be handled efficiently. As an application we demonstrate the generation of adjoint, tangent linear, and Hessian code for a CFD solver in an airfoil configuration. We also list a few other large-scale applications and their performance.

J.D. Müller and P. Cusdin. On The Performance Of Discrete Adjoint Cfd Codes Using Automatic Differentiation. International Journal For Numerical Methods In Fluids, 47(8-9):939-945, 2005. [ http ]

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. [ .pdf ]

Describes generation of tangent-linear and adjoint models of the Fortran-90 regional weather forecast model ARPS.

D. Ferreira, J. Marshall, and P. Heimbach. Estimating eddy stresses by fitting dynamics to observations using a residual-mean ocean circulation model and its adjoint. Journal Of Physical Oceanography, 35(10):1891-1910, 2005. [ http | .pdf ]

T. Kaminski, R. Giering, and M. Voßbeck. Efficient sensitivities for the spin-up phase. 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 283-291. Springer, New York, NY, 2005. [ DOI | .pdf ]

Demonstrates an alternative AD strategy for iterative solvers that evaluates the full Jacobian for the final iteration.

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. [ DOI | .pdf ]

Describes generation of the tangent linear and adjoint versions of a state-of-the-art Fortran-90 weather forecast model.

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. [ .pdf ]

B. Pak. Parameter optimization using the adjoint of a biosphere model. Abstract A11F-02. Eos Trans. AGU, 85(47), December 2004. [ .txt ]

Wolfgang Knorr and Peter Cox. CAMELS-Carbon Assimilation and Modelling of the European Land Surface. In Peter Bergamaschi, Hartmut Behrend, and Andre Jol, editors, Inverse modelling of national and EU greenhouse gas emission inventories, pages 66-69, 2004. [ .html ]

The paper describes the contribution of CCDAS to the EU FP5 project CAMELS

H. M. Bücker and R. Beucker. Using automatic differentiation for the solution of the minimum p-norm estimation problem in magnetoencephalography. Simulation Modelling Practice and Theory, 12:105-116, 2004. [ .html ]

The study uses TAF generated derivatives of a function arising in tomography of the human brain. The adjoint code takes about 3 times as long as the function code.

A. Köhl and D. Stammer. Optimal observations for variational data assimilation. J. Phys. Oceanogr., 34(3):529-542, 2004. [ http ]

M. Scholze, P. Rayner, W. Knorr, T. Kaminski, R. Giering, and H. Widmann. Non-linear parameter optimisation of a terrestrial biosphere model using atm. CO2 observations: CCDAS. Geophysical Research Abstracts, 6:06281, 2004. [ .ppt/.pdf | .pdf ]

M. Scholze, P. Rayner, W. Knorr, T. Kaminski, R. Giering, and H. Widmann. A global carbon cycle data assimilation system (CCDAS) to infer atmosphere-biosphere CO2 exchanges. Geophysical Research Abstracts, 6:07504, 2004. [ .pdf ]

D. Stammer, K. Ueyoshi, A. Köhl, W.G. Large, S.A. Josey, and C. Wunsch. Estimating air-sea fluxes of heat, freshwater, and momentum through global ocean data assimilation. J. Geophys. Res., 109(C05023), 2004. [ http ]

C. Hill, V. Bugnion, M. Follows, and J. Marshall. Evaluating carbon sequestration efficiency in an ocean circulation model by adjoint sensitivity analysis. J. Geophys. Res., 109(C11005):doi:10.1029/2002JC001598, 2004. [ http | .pdf ]

S. Sommacal. Computational petrology: Subsolidus equilibria in the upper mantle. PhD thesis, Australian National University, Canberra, 2004.

TAF is used to provide the gradient for minimisation of the Gibbs free energy function.

E. Galanti and E. Tziperman. A midlatitude-enso teleconnection mechanism via baroclinically unstable long rossby waves. Journal Of Physical Oceanography, 33(9):1877-1888, 2003. [ http | .pdf ]

The group first used TAMC and then switched to TAF

M. Hinze and T. Slawig. Adjoint gradients compared to gradients from algorithmic differentiation in instataneous control of the Navier-Stokes equations. Optimization Methods & Software, 18(3):299-315, 2003.

J. P. Thomas, K. C. Hall, and E. H. Dowell. A discrete adjoint approach for modeling unsteady aerodynamic design sensitivities. 41st AIAA Aerospace Sciences Meeting, Reno, Nevada, 2003.

A TAF generated adjoint is used to study steady and unsteady aerodynamic design sensitivities for compressible viscous flows around airfoil configurations.

R. Giering and T. Kaminski. Applying TAF to generate efficient derivative code of Fortran 77-95 programs. PAMM, 2(1):54-57, 2003. [ http | .pdf ]

Here we give an overview on how TAF approaches typical challenges of AD such as handling of badly written program code, of large memory/disk requirements, of iterative solvers or of black box routines. We also point out, where the user is required to prepare his program code prior to invoking TAF.

M. Losch and C. Wunsch. Bottom topography as a control parameter in an ocean circulation model. Journal Of Atmospheric And Oceanic Technology, 20(11):1685-1696, 2003. [ .pdf ]

T. Kaminski, R. Giering, M. Scholze, P. Rayner, and W. Knorr. A prototype of a data assimilation system based on automatic differentiation. Geophysical Research Abstracts, 5:11812, 2003. [ .ppt/.pdf | .pdf ]

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. [ .pdf ]

R. Todling, R. Giering, T. Kaminski, Y. Zhu, and J Guo. Retrospective data assimilation for GEOS-4. Geophysical Research Abstracts, 5:11354, 2003. [ .pdf ]

T. Kaminski, R. Giering, M. Scholze, P. Rayner, and W. Knorr. An example of an automatic differentiation-based modelling system. In V. Kumar, L. Gavrilova, C. J. K. Tan, and P. L'Ecuyer, editors, Computational Science - ICCSA 2003, International Conference Montreal, Canada, May 2003, Proceedings, Part II, volume 2668 of Lecture Notes in Computer Science, pages 95-104, Berlin, 2003. Springer. [ .ppt/.pdf | .pdf ]

The paper presents a prototype of a Carbon Cycle Data Assimilation System (CCDAS), which is composed of a terrestrial biosphere model (BETHY) coupled to an atmospheric transport model (TM2), corresponding derivative codes as well as a derivative-based optimisation routine. In calibration mode, we use first and second derivatives, to estimate model parameters and their uncertainties from atmospheric observations and their uncertainties. In prognostic mode, we use first derivatives, to map model parameters and their uncertainties onto prognostic quantities and their uncertainties.

M. Scholze. Model studies on the response of the terrestrial carbon cycle on climate change and variability. Examensarbeit, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 2003. [ .html | .pdf ]

P. Cusdin and J.-D. Müller. Improving the performance of code generated by automatic differentiation. Technical Report QUB-SAE-03-04, QUB School of Aeronautical Engineering, 2003.

P. Cusdin and J.-D. Müller. Automatic differentiation and sensitivity analysis methods for cfd. Technical Report QUB-SAE-03-01, QUB School of Aeronautical Engineering, 2003.

P. Cusdin and J.-D. Müller. Deriving linear and adjoint codes for cfd using automatic differentiation. Technical Report QUB-SAE-03-06, QUB School of Aeronautical Engineering, 2003.

P. Cusdin. Timelog: Timing fortran code. Technical Memorandum QUB-SAE-03-03, QUB School of Aeronautical Engineering, 2003. [ http ]

T. Lee and I. Fukumori. Interannual-To-Decadal Variations Of Tropical-Subtropical Exchange In The Pacific Ocean: Boundary Versus Interior Pycnocline Transports. J. Climate, 16(24):4022-4042, 2003. [ http ]

M. Scholze, P. Rayner, W. Knorr, T. Kaminski, and R. Giering. A prototype Carbon Cycle Data Assimilation System (CCDAS): Inferring interannual variations of vegetation-atmosphere CO2 fluxes. Abstract CG62A-05. Eos Trans. AGU, 83(47), December 2002. [ .ppt/.pdf | http ]

R. Giering and T. Kaminski. Recomputations in reverse mode AD. In George Corliss, Andreas Griewank, Christele Fauré, Laurent Hascoet, and Uwe Naumann, editors, Automatic Differentiation of Algorithms: From Simulation to Optimization, chapter 33, pages 283-291. Springer Verlag, Heidelberg, 2002. [ http | .pdf ]

P. Heimbach, C. Hill, and R. Giering. Automatic generation of efficient adjoint code for a parallel Navier-Stokes solver. In P. M. A. Sloot, C. J. K. Tan, J. J. Dongarra, and A. G. Hoekstra, editors, Computational Science - ICCS 2002, Proceedings of the International Conference on Computational Science, Amsterdam, The Netherlands, April 21-24, 2002. Part II, volume 2330 of Lecture Notes in Computer Science, pages 1019-1028, Berlin, 2002. Springer. [ http | .pdf ]

M. Hinze and T. Slawig. Adjoint gradients compared to gradients from algorithmic differentiation in instataneous control of the Navier-Stokes equations. Preprint 735-2002, Institute of Mathematics, Technische Universität Berlin, 2002. [ .html ]

The authors first used TAMC and then TAF. The model uses an iterative solver, for which, after inserting 5 TAF flow directives, TAF can generate a very efficient adjoint. The TAF generated adjoint is slightly faster than its hand coded counterpart.

D. Stammer, C. Wunsch, R. Giering, C. Eckert, P. Heimbach, J. Marotzke, A. Adcroft, C. N. Hill, and J. Marshall. The global ocean circulation during 1992-1997, estimated from ocean observations and a general circulation model. J. Geophys. Res., 107(C9):doi:10.1029/2001JC000888, 2002. [ http | .pdf ]

D. Stammer, C. Wunsch, R. Giering, C. Eckert, P. Heimbach, J. Marotzke, A. Adcroft, C. N. Hill, and J. Marshall. Volume, heat and freshwater transports of the global ocean circulation 1992-1997, estimated from a general circulation model constrained by WOCE data. J. Geophys. Res., page doi:10.1029/2001JC001115, 2002. [ http | .pdf ]

A. Adcroft, J.-M. Campin, P. Heimbach, C. Hill, and J. Marshall. The MITgcm. Online documentation, Massachusetts Institute of Technology, USA, 2002. [ http | .pdf ]

The manual of the MITgcm contains a chapter on Automatic Differentiation of the model. The ECCO consortium applied TAMC first and has now switched to TAF.

H. M. Bücker and R. Beucker. Using automatic differentiation for the solution of the minimum p-norm estimation problem in magnetoencephalography. Preprint RWTH-CS-SC-02-11, RWTH, Institute for Scientific Computing, Aachen, Germany, 2002.

The study uses TAF generated derivatives of a function arising in tomography of the human brain. The adjoint code takes about 3 times as long as the function code.

P. Heimbach, C. Hill, and R. Giering. Automatic Generation of Efficient Adjoint Code for the Parallel MIT General Circulation Model. In RIST/NCAR International Workshop on Next Generation Climate Models for Advanced High Performance Computing Facilities. National Center for Atmospheric Research (NCAR), Boulder, March 12th to 14th, 2002. [ http | .pdf ]

P. Rayner, W. Knorr, M. Scholze, R. Giering, T. Kaminski, M. Heimann, and C. Le Quere. Inferring terrestrial biosphere carbon fluxes from combined inversions of atmospheric transport and process-based terrestrial ecosystem models. In Proceedings of 6th Carbon dioxide conference at Sendai, pages 1015-1017, 2001. [ .pdf ]

This is the first document featuring the implementation of a carbon cycle data assimilation and prediction scheme, which is based on the terrestrial biosphere model BETHY

C. H. Bischof, H. M. Bücker, B. Lang, and A. Rasch. Recent Progress in Automatic Differentiation: Advanced Tools and Large-Scale Applications. Preprint RWTH-CS-SC-01-18, RWTH, Institute for Scientific Computing, Aachen, Germany, 2001. [ .html ]

Among other things, the paper compares the performance of two sets of derivative code for a test problem. One of these sets is generated by ADIFOR 3 and the other by TAF. The TAF generated adjoint code is by a factor of 5 faster than that generated by the ADIFOR 3.

CCDAS Team. CCDAS project - overview strategy. Informal Presentation, 2001. [ .pdf ]

A schematic overview of the strategy in the Carbon Cycle Data Assimilation Project.

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