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Volume 8, issue 10 | Copyright
Geosci. Model Dev., 8, 3285-3310, 2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 20 Oct 2015

Development and technical paper | 20 Oct 2015

CH4 parameter estimation in CLM4.5bgc using surrogate global optimization

J. Müller et al.
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Adhya, T., Bharati, K., Mohanty, S., Ramakrishnan, B., Rao, V., Sethunathan, N., and Wassmann, R.: Methane emission from rice fields at Cuttack, India, Nutr. Cycl. Agroecosys., 58, 95–105, 2000.
Aleman, D., Romeijn, H., and Dempsey, J.: A response surface approach to beam orientation optimization in intensity modulated radiation therapy treatment planning, INFORMS J. Comput., 21, 62–76, 2009.
Arah, J. and Stephen, K.: A model of the processes leading to methane emission from peatland, Atmos. Environ., 32, 3257–3264, 1998.
Aselmann, I. and Crutzen, P.: Global distribution of natural fresh-water wetlands and rice paddies, their net primary productivity, seasonality and possible methane emsissions, J. Atmos. Chem., 8, 307–358, 1989.
Baird, A., Beckwith, C., Waldron, S., and Waddington, J.: Ebullition of methane-containing gas bubbles from near surface Sphagnum peat, Geophys. Res. Lett., 31, L21505,, 2004.
Publications Copernicus
Short summary
We tune the CH4-related parameters of the Community Land Model (CLM) using surrogate global optimization in order to reduce the discrepancies between the CLM predictions and observed CH4 emissions. This is the first application of a surrogate optimization method to calibrate a global climate model. We found that the observation data drives the model to predict more CH4 emissions in the northern latitudes and less in the tropics.
We tune the CH4-related parameters of the Community Land Model (CLM) using surrogate global...