Articles | Volume 13, issue 9
Geosci. Model Dev., 13, 4091–4106, 2020
https://doi.org/10.5194/gmd-13-4091-2020

Special issue: CoMet: a mission to improve our understanding and to better...

Geosci. Model Dev., 13, 4091–4106, 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 et al.

Related authors

Estimating CH4, CO2 and CO emissions from coal mining and industrial activities in the Upper Silesian Coal Basin using an aircraft-based mass balance approach
Alina Fiehn, Julian Kostinek, Maximilian Eckl, Theresa Klausner, Michał Gałkowski, Jinxuan Chen, Christoph Gerbig, Thomas Röckmann, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Pawel Jagoda, Norman Wildmann, Christian Mallaun, Rostyslav Bun, Anna-Leah Nickl, Patrick Jöckel, Andreas Fix, and Anke Roiger
Atmos. Chem. Phys., 20, 12675–12695, https://doi.org/10.5194/acp-20-12675-2020,https://doi.org/10.5194/acp-20-12675-2020, 2020
Short summary
Spatiotemporal variability of NO2 and PM2.5 over Eastern China: observational and model analyses with a novel statistical method
Mengyao Liu, Jintai Lin, Yuchen Wang, Yang Sun, Bo Zheng, Jingyuan Shao, Lulu Chen, Yixuan Zheng, Jinxuan Chen, Tzung-May Fu, Yingying Yan, Qiang Zhang, and Zhaohua Wu
Atmos. Chem. Phys., 18, 12933–12952, https://doi.org/10.5194/acp-18-12933-2018,https://doi.org/10.5194/acp-18-12933-2018, 2018
Short summary

Related subject area

Biogeosciences
A model-independent data assimilation (MIDA) module and its applications in ecology
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021,https://doi.org/10.5194/gmd-14-5217-2021, 2021
Short summary
Optical model for the Baltic Sea with an explicit CDOM state variable: a case study with Model ERGOM (version 1.2)
Thomas Neumann, Sampsa Koponen, Jenni Attila, Carsten Brockmann, Kari Kallio, Mikko Kervinen, Constant Mazeran, Dagmar Müller, Petra Philipson, Susanne Thulin, Sakari Väkevä, and Pasi Ylöstalo
Geosci. Model Dev., 14, 5049–5062, https://doi.org/10.5194/gmd-14-5049-2021,https://doi.org/10.5194/gmd-14-5049-2021, 2021
Short summary
WAP-1D-VAR v1.0: development and evaluation of a one-dimensional variational data assimilation model for the marine ecosystem along the West Antarctic Peninsula
Hyewon Heather Kim, Ya-Wei Luo, Hugh W. Ducklow, Oscar M. Schofield, Deborah K. Steinberg, and Scott C. Doney
Geosci. Model Dev., 14, 4939–4975, https://doi.org/10.5194/gmd-14-4939-2021,https://doi.org/10.5194/gmd-14-4939-2021, 2021
Short summary
SCOPE 2.0: a model to simulate vegetated land surface fluxes and satellite signals
Peiqi Yang, Egor Prikaziuk, Wout Verhoef, and Christiaan van der Tol
Geosci. Model Dev., 14, 4697–4712, https://doi.org/10.5194/gmd-14-4697-2021,https://doi.org/10.5194/gmd-14-4697-2021, 2021
Short summary
SolveSAPHE-r2 (v2.0.1): revisiting and extending the Solver Suite for Alkalinity-PH Equations for usage with CO2, HCO3 or CO32− input data
Guy Munhoven
Geosci. Model Dev., 14, 4225–4240, https://doi.org/10.5194/gmd-14-4225-2021,https://doi.org/10.5194/gmd-14-4225-2021, 2021
Short summary

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. 
Download
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.