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High resolution modeling of CO2 over Europe: implications for representation errors of satellite retrievals

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons62510

Pillai,  D.
Airborne Trace Gas Measurements and Mesoscale Modelling, Dr. habil. C. Gerbig, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62381

Gerbig,  C.
Airborne Trace Gas Measurements and Mesoscale Modelling, Dr. habil. C. Gerbig, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62478

Marshall,  Julia
Satellite-based Remote Sensing of Greenhouse Gases, Dr. J. Marshall, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62322

Ahmadov,  Ravan
Airborne Trace Gas Measurements and Mesoscale Modelling, Dr. habil. C. Gerbig, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62450

Kretschmer,  R.
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62442

Koch,  T.
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62430

Karstens,  U.
Regional Scale Modelling of Atmospheric Trace Gases, Dr. U. Karstens, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

Externe Ressourcen
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BGC1259.pdf
(Verlagsversion), 3MB

BGC1259D.pdf
(Preprint), 4MB

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Zitation

Pillai, D., Gerbig, C., Marshall, J., Ahmadov, R., Kretschmer, R., Koch, T., et al. (2010). High resolution modeling of CO2 over Europe: implications for representation errors of satellite retrievals. Atmospheric Chemistry and Physics, 10(1), 83-94. doi:10.5194/acp-10-83-2010.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000E-DA6F-9
Zusammenfassung
Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO2 from the high resolution modeling framework WRF-VPRM, which links CO2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10x10 km(2) horizontal resolution. Sub-grid variability of column averaged CO2, i.e. the variability not resolved by global models, reached up to 1.2 ppm with a median value of 0.4 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO2 fluxes as well as resolved mixing ratio of CO2, a linear model can be formulated that could explain about 50% of the spatial patterns in the systematic (bias or correlated error) component of representation error in column and near-surface CO2 during day- and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.