Articles | Volume 16, issue 1
https://doi.org/10.5194/gmd-16-47-2023
https://doi.org/10.5194/gmd-16-47-2023
Model description paper
 | 
03 Jan 2023
Model description paper |  | 03 Jan 2023

ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application

Peter J. M. Bosman and Maarten C. Krol

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This preprint is open for discussion and under review for Biogeosciences (BG).
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Cited articles

Barbaro, E., Vilà-Guerau de Arellano, J., Ouwersloot, H. G., Schröter, J. S., Donovan, D. P., and Krol, M. C.: Aerosols in the convective boundary layer: Shortwave radiation effects on the coupled land-atmosphere system, J. Geophys. Res.-Atmos., 119, 5845–5863, https://doi.org/10.1002/2013JD021237, 2014. a
Bastrikov, V., MacBean, N., Bacour, C., Santaren, D., Kuppel, S., and Peylin, P.: Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2), Geosci. Model Dev., 11, 4739–4754, https://doi.org/10.5194/gmd-11-4739-2018, 2018. a, b, c
Bergamaschi, P., Frankenberg, C., Meirink, J. F., Krol, M., Villani, M. G., Houweling, S., Dentener, F., Dlugokencky, E. J., Miller, J. B., Gatti, L. V., Engel, A., and Levin, I.: Inverse modeling of global and regional CH4 emissions using SCIAMACHY satellite retrievals, J. Geophys. Res.-Atmos., 114, 1–28, https://doi.org/10.1029/2009JD012287, 2009. a
Bosman, P. and Krol, M.: PBosmanatm/ICLASS: ICLASS v1.1, Zenodo [code and data set], https://doi.org/10.5281/zenodo.7239147, 2022. a
Bosveld, F., Van Meijgaard, E., Moors, E., and Werner, C.: Interpretation of flux observations along the Cabauw 200 m meteorological tower, in: 16th Symposium on Boundary Layers and Turbulence 6.18, 1–4, Portland, USA, https://ams.confex.com/ams/BLTAIRSE/webprogram/Paper78632.html (last access: 9 December 2022), 2004. a
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We describe an inverse modelling framework constructed around a simple model for the atmospheric boundary layer. This framework can be fed with various observation types to study the boundary layer and land–atmosphere exchange. With this framework, it is possible to estimate model parameters and the associated uncertainties. Some of these parameters are difficult to obtain directly by observations. An example application for a grassland in the Netherlands is included.
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