Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4091-2020
https://doi.org/10.5194/gmd-13-4091-2020
Model evaluation paper
 | 
07 Sep 2020
Model evaluation paper |  | 07 Sep 2020

Short-term forecasting of regional biospheric CO2 fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)

Jinxuan Chen, Christoph Gerbig, Julia Marshall, and Kai Uwe Totsche

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Cited articles

Agustí-Panareda, A., Massart, S., Chevallier, F., Balsamo, G., Boussetta, S., Dutra, E., and Beljaars, A.: A biogenic CO2 flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO2 analyses and forecasts, Atmos. Chem. Phys., 16, 10399–10418, https://doi.org/10.5194/acp-16-10399-2016, 2016. 
Ahmadov, R., Gerbig, C., Kretschmer, R., Koerner, S., Neininger, B., Dolman, A., and Sarrat, C.: Mesoscale covariance of transport and CO2 fluxes: Evidence from observations and simulations using the WRF-VPRM coupled atmosphere-biosphere model, J. Geophys. Res.-Atmos., 112, D22107, https://doi.org/10.1029/2007JD008552, 2007. 
Amediek, A., Ehret, G., Fix, A., Wirth, M., Budenbender, C., Quatrevalet, M., Kiemle, C., and Gerbig, C.: CHARM-F-a new airborne integrated-path differential-absorption lidar for carbon dioxide and methane observations: measurement performance and quantification of strong point source emissions, Appl. Opt., 56, 5182–5197, 10.1364/Ao.56.005182, 2017. 
Anthoni, P., Knohl, A., Rebmann, C., Freibauer, A., Mund, M., Ziegler, W., Kolle, O., and Schulze, E. D.: Forest and agricultural land-use-dependent CO2 exchange in Thuringia, Germany, Glob. Change Biol., 10, 2005–2019, 2004. 
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Short summary
One of the essential challenge for atmospheric CO2 forecasting is predicting CO2 flux variation on synoptic timescale. For CAMS CO2 forecast, a process-based vegetation model is used. In this research we evaluate another type of model (i.e., the light-use-efficiency model VPRM), which is a data-driven approach and thus ideal for realistic estimation, on its ability of flux prediction. Errors from different sources are assessed, and overall the model is capable of CO2 flux prediction.