• \
    Start Submission Become a Reviewer

    Reading: Quantifying the benefit of A-SCOPE data for reducing uncertainties in terrestrial carbon flu...

    Download

     A- A+
    Alt. Display

    Original Research Papers

    Quantifying the benefit of A-SCOPE data for reducing uncertainties in terrestrial carbon fluxes in CCDAS

    Authors:

    T. Kaminski ,

    FastOpt, Schanzenstr. 36, 20357 Hamburg, DE
    X close

    M. Scholze,

    QUEST – Department of Earth Sciences, University of Bristol, Wills Memorial Building, Bristol BS8 1RJ, GB
    X close

    S. Houweling

    Netherlands Institute for Space Research (SRON), Sorbonnelaan 2, 3584, CA Utrecht, NL
    X close

    Abstract

    ESA’s Earth Explorer candidate mission A-SCOPE aims at observing CO2 from space with an active LIDAR instrument. This study employs quantitative network design techniques to investigate the benefit of A-SCOPE observations in a Carbon Cycle Data Assimilation System. The system links the observations to the terrestrial vegetation model BETHY via the fine resolution version of the atmospheric transport model TM3. In the modelling process chain the observations are used to reduce uncertainties in the values of BETHY’s process parameters, and then the uncertainty in the process parameters is mapped forward to uncertainties in both in long-term net carbon flux and net primary productivity over three regions. A-SCOPE yields considerably better reductions in posterior uncertainties than the ground-based GLOBALVIEW station network. This is true for assimilating monthly mean values and instantaneous values, and it is true for two potential vertical weighting functions. The strength of the constraint through A-SCOPE observations is high over the range of observational uncertainties.

    How to Cite: Kaminski, T., Scholze, M. and Houweling, S., 2010. Quantifying the benefit of A-SCOPE data for reducing uncertainties in terrestrial carbon fluxes in CCDAS. Tellus B: Chemical and Physical Meteorology, 62(5), pp.784–796. DOI: http://doi.org/10.1111/j.1600-0889.2010.00483.x
      Published on 01 Jan 2010
    Peer Reviewed
     CC BY 4.0
     Accepted on 10 Jun 2010            Submitted on 21 Jan 2010

    References

    1. Baker , D. F. , Bosch , H. , Doney , S. C. and Schimel , D. S . 2008 . Carbon source/sink information provided by column CO2 measurements from the Orbiting Carbon Observatory. Atmos. Chem. Phys. Discuss . 8 ( 6 ), 20051-20 112.  

    2. Breon , F. M. , Houweling , S. , Aben , I. , Ehret , G. , Chevallier , F. and co-authors . 2009 . Observation Techniques and mission concepts for the Analysis of the Global Carbon Cycle, ESA contract 20839/07/NL/HE, Technical report, European Space Agency, Noordwijk, The Nether-lands.  

    3. Cadule , P. , Friedlingstein , P. , Bopp , L. , Sitch , S. , Jones , C. D. and co-authors . 2010 . Benchmarlcing coupled climate-carbon models against long-term atmospheric CO2 measurements. Glob. Biogeochem. Cycle 24 , GB2016 , doi: https://doi.org/10.1029/2009GB003556 .  

    4. Chevallier , F. , Breon , F.-M. and Rayner , P. J . 2007 . Contribution of the Orbiting Carbon Observatory to the estimation of CO2 sources and sinks: theoretical study in a variational data assimilation framework. J. Geophys. Res . 112 , doi: https://doi.org/10.1029/2006JD007375 .  

    5. Chevallier , F. , Maksyutov , S. , Bousquet , P. , Breon , F.-M. , Saito , R. and co-authors . 2009 . On the accuracy of the CO2 surface fluxes to be estimated from the GOSAT observations. Geophys. Res. Lett . 36 , doi: https://doi.org/10.1029/2009GL040108 .  

    6. Cramer , W. , Bondeau , A. , Woodward , F. , Prentice , I. , Betts , R. and co-authors . 2001 . Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models. Global Change Biol . 7 ( 4 ), 357 - 373 .  

    7. Cramer , W. , Kicklighter , D. W. , Bondeau , A. , Moore , B. I. , Churkina , G. and co-authors . 1999 . Comparing global models of terrestrial net primary productivity (NPP): overview and key results. Glob. Change Biol . 5 , 1 - 15 .  

    8. Ehret , G. , Kiemle , C. , Wirth , M. , Amediek , A. , Fix , A. and co-authors . 2008 . Space-borne remote sensing of CO2, CH4, and N20 by inte-grated path differential absorption lidar: a sensitivity analysis. AppL Phys. B 90 , 593 - 608 . doi: https://doi.org/10.1007/s00340-007-2892-3 .  

    9. Enting , I. G . 2002 . Inverse Problems in Atmospheric Constituent Trans-port . Cambridge University Press, Cambridge , UK .  

    10. ESA 2008 . A-SCOPE - Advanced Space Carbon And Climate Obser-vation of Planet Earth, Technical Report SP-1313/1, European Space Agency, Noordwijk, The Netherlands.  

    11. Feng , L. , Palmer , P. I. , Bosch , H. and Dance , S. 2009. Estimating surface co2 fluxes from space-borne co2 dry air mole fraction observations using an ensemble kalman filter . Atmosp. Chem. Phys . 9 ( 8 ), 2619 - 2633 .  

    12. Friedlingstein , P. , Cox , R , Betts , R. , Bopp , L. , von Bloh , W. and co-authors . 2006 . Climate-carbon cycle feedback analysis: results from the C4MIP model intercomparison. J. Climate 19 , 3337 - 3353 .  

    13. Giering , R. and Kaminski , T . 1998 . Recipes for adjoint code construc-tion . ACM Trans. Math. Software 24 ( 4 ), 437 – 474 .  

    14. GLOBALVIEW-CO2 2004 . Cooperative Atmospheric Data Integra-tion Project -Carbon Dioxide, CD-ROM, NOAA CMDL, Boul-der, Colorado. [Also available on Internet via anonymous FTP to ftp.cmdl.noaa.gov, Path: ccg/co2/GLOBALVIEW].  

    15. Heimann , M. and Kaminski , T . 1999 . Inverse modeling approaches to infer surface trace gas fluxes from observed atmospheric mixing ratios. In: Approaches to Scaling of Trace Gas Fluxes in Ecosystems (ed. A. E Bouwman ), Elsevier , Amsterdam , Chapter 14 , 275 – 295 .  

    16. Heimann , M. and Körner , S . 2003 . The global atmospheric tracer model TM3, Technical Report 5, Max-Planck-Institut fiir Biogeochemie, Jena, Germany.  

    17. Houweling , S. , Breon , E-M. , Aben , I. , Rödenbeck , C. , Gloor , M. and co-authors . 2004 . Inverse modeling of CO2 sources and sinks using satellite data: a synthetic inter-comparison of measurement techniques and their performance as a function of space and time. Atmos. Chem. Phys . 4 , 523 - 538 .  

    18. Kalnay , E. , Kanamitsu , M. , Kistler , R. , Collins , W. , Deaven , D. and co-authors . 1996 . The NCEP/NCAR 40-Year Reanalysis Project. Bull. Am. MeteoroL Soc . 77(3 ), 437 - 471 .  

    19. Kaminski , T. , Giering , R. , Scholze , M. , Rayner , P. and Knorr , W . 2003 . An example of an automatic differentiation-based modelling system. In: Computational Science -ICCSA 2003, International Conference Montreal, Canada, May 2003, Proceedings, Part II (eds V. Kumar , L. Gavrilova , C. J. K. Tan and P. L'Ecuyer ), Vol. 2668 of Lecture Notes in Computer Science, Springer, Berlin, 95 - 104 .  

    20. Kaminski , T. and Heimann , M . 2001 . Inverse modeling of atmospheric carbon dioxide fluxes . Science 294 ( 5541 ), 259 .  

    21. Kaminski , T. , Knorr , W. , Rayner , P. and Heimann , M . 2002 . As-similating atmospheric data into a terrestrial biosphere model: a case study of the seasonal cycle. Glob. Biogeochem. Cycl . 16(4) , doi: https://doi.org/10.1029/2001GB001463 .  

    22. Kaminski , T. and Rayner , P. J . 2008 . Assimilation and network design. In: Observing the Continental Scale Greenhouse Gas Balance of Eu-rope (eds H. Dolman , A. Freibauer and R. Valentini ), Ecological Stud-ies, Springer-Verlag, New York, Chapter 3, 33 - 52 . doi: https://doi.org/10.1007/978-0-387-76570-9_3 .  

    23. Keeling , C. and Whorf , T . 2002 . Atmospheric CO2 records from sites in the SIO air sampling network. Trends: A Compendium of Data on Global Change , Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, TN, 723 - 741 .  

    24. Kicklighter , D. W. , Bondeau , A. , Schloss , A. L. , Kaduk , J. , McGuire , A. D. and the participants of the Potsdam NPP Model Intercomparison 1999. Comparing global models of terrestrial net primary productiv-ity (NPP): global pattern and differentiation by major biomes. Glob. Change Biol . 5 , 16 - 24 .  

    25. Knorr , W . 1997 . Satellitengestiitzte Fernerkundung und Modellierung des Globalen CO2 -Austauschs der Landvegetation: Eine Syn-these, PhD thesis, Max-Planck-Institut fiir Meteorologie, Hamburg, Germany.  

    26. Knorr , W . 2000 . Annual and interannual CO2 exchanges of the terrestrial biosphere: process based simulations and uncertainties . Glob. EcoL Biogeogr 9 , 225 – 252 .  

    27. Knorr , W. and Heimann , M . 2001 . Uncertainties in global terrestrial biosphere modeling: 1. A comprehensive sensitivity analysis with a new photosynthesis and energy balance scheme . Glob. Biogeochem. CycL 15 ( 1 ), 207 – 225 .  

    28. Michalak , A. , Miller , C. , Browell , E. , Moore , B. , Abshire , J. and co-authors . 2008 . ASCENDS—active Sensing of CO2 Emissions over Nights, Days, and Seasons Mission, Technical report, University of Michigan in Ann Arbor, Michigan.  

    29. Miller , C. E. , Crisp , D. , DeCola , P. L. , Olsen , S. C. , Randerson , J. T. and co-authors . 2007 . Precision requirements for space-based XCO2 data. J. Geophys. Res . 112 , doi: https://doi.org/10.1029/2006JDO07659 .  

    30. Pak , B. C. and Prather , M. J . 2001 . CO2 source inversions using satel-lite observations of the upper troposphere . Geophys. Res. Lett . 28 , 4571 – 4574 .  

    31. Patra , P. K. , Sasano , S. M. Y. , Nakajima , H. and Inoue , G . 2003 . An evaluation of CO2 observations with SOFIS sensor for surface source inversion. J. Geophys. Res . 108 , doi: https://doi.org/10.1029/2003JDO03661.  

    32. Randerson , J. , Hoffman, E , Thornton , P. , Mahowald , N. , Lindsay , K. and co-authors . 2009 . Systematic assessment of terrestrial biogeo-chemistry in coupled climate—carbon models. Glob. Change Biol . 15 , 2462 - 2484 .  

    33. Rayner , P J. , Enting , I. G. and Trudinger , C. M. 1996. Optimizing the CO2 observing network for constraining sources and sinks. Tellus 48B , 433 - 444 .  

    34. Rayner , P J. , Law , R. M. , O'Brien , D. M. , Butler , T. M. and Dilley , A. C. 2002. Global observations of the carbon budget: 3. Initial as-sessment of the impact of satellite orbit, scan geometry and cloud on measuring CO2 from space. J. Geophys. Res . 107(D21) , 4557. doi: https://doi.org/10.1029/2001JD000618 .  

    35. Rayner , P. J. and O'Brien , D. M. 2001. The utility of remotely sensed CO2 concentration data in surface source inversions. Geophys. Res. Lett . 28 , 175 - 178 .  

    36. Rayner , P. , Scholze , M. , Knorr , W. , Kaminski , T. , Giering , R. and co-authors . 2005 . Two decades of terrestrial Carbon fluxes from a Car-bon Cycle Data Assimilation System (CCDAS). Global Biogeochem. CycL 19 , doi: https://doi.org/10.1029/2004GB002254 .  

    37. Scholze , M . 2003 . Model studies on the response of the terrestrial carbon cycle on climate change and variability, PhD thesis, Max-Planck-Institut fiir Meteorologie, Hamburg, Germany.  

    38. Scholze , M. , Kaminski , T. , Rayner , R , Knorr , W. and Giering R . 2007 . Propagating uncertainty through prognostic CCDAS simulations. J. Geophys. Res . 112 , doi: https://doi.org/10.1029//2007JDO08642 .  

    39. Tarantola , A . 1987 . Inverse Problem Theory—Methods for Data Fitting and Model Parameter Estimation . Elsevier Sci ., New York .  

    Jump to Discussions Related content
    comments powered by Disqus