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Journal Article

Contributions of the troposphere and stratosphere to CH4 model biases

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

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Citation

Wang, Z., Warneke, T., Deutscher, N., Notholt, J., Karstens, U., Saunois, M., et al. (2016). Contributions of the troposphere and stratosphere to CH4 model biases. Atmospheric Chemistry and Physics Discussions. doi:10.5194/acp-2016-1041.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002C-2C15-9
Abstract
Inverse modeling is a useful tool to retrieve CH4 fluxes; however, evaluation of the applied chemical transport model is an important step before using the inverted emissions. For inversions using column data one concern is how well the model represents stratospheric and tropospheric CH4 respectively when assimilating total column measurements. In this study atmospheric CH4 from three inverse models is compared to FTS (Fourier Transform Spectrometry), satellite and in situ measurements. Using the FTS measurements the model biases are separated into stratospheric and tropospheric contributions. When averaged over all FTS sites the model bias amplitudes (absolute model to FTS differences) are 7.4±5.1 ppb, 6.7±4.8 ppb, and 8.1±5.5 ppb in the troposphere for the models TM3, TM5-4DVAR, LMDz-PYVAR, respectively, and 4.3±9.9 ppb, 4.7±9.9 ppb, and 6.2±11.2 ppb in the stratosphere. The tropospheric model biases show a latitudinal gradient for all models, however there are no clear latitudinal dependencies for stratospheric model biases visible except with the LMDz-PYVAR model. The latitudinal gradient is not present in a comparison with in situ measurements, which is attributed to the different longitudinal coverage of FTS and in situ measurements. Similarly, a latitudinal pattern exists in model biases in vertical CH4 gradients in the troposphere, which indicates vertical transports of tropospheric CH4 is not represented correctly in the models.