# Predicted Future Changes in the Mean Seasonal Carbon Cycle Due to Climate Change
## 6 Conclusions
also acknowledge funding from the MIUR Project (PRIN 2020)--Research Projects of National Relevance funded by the Italian Ministry of University and Research entitled: \"Multi-scale observations to predict Forest response to pollution and climate change\" (MULTIFOR, project number: 2020E52 THS). **Data Availability Statement:** The 3D-CMCC-FEM model code is publicly available and can be found on the GitHub platform at: [[https://github.com/Forest-Modelling-Lab/3D-CMCC-FEM](https://github.com/Forest-Modelling-Lab/3D-CMCC-FEM)]([https://github.com/Forest-Modelling-Lab/3D-CMCC-FEM](https://github.com/Forest-Modelling-Lab/3D-CMCC-FEM)) (accessed on 24 June 2024). The 3D-CMCC-FEM output data used in this work can be downloaded at: [[https://zenodo.org/records/11124413](https://zenodo.org/records/11124413)]([https://zenodo.org/records/11124413](https://zenodo.org/records/11124413)) (accessed on 7 May 2024). Correspondence and requests for additional materials should be addressed to the corresponding author. **Acknowledgments:** We are thankful to [PERSON]. [PERSON] for supporting data preparation and analysis. We also thank the ISMIP project and the COST Action FP1304 PROFOUND (Towards Robust Projections of European Forests under Climate Change), supported by COST (European Cooperation in Science and Technology) for providing us the climate historical and future scenarios and site data used in this work. This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEurope-IP, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, TCOS-Siberia, and USCCC. The ERA-Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata Project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the respective climate modeling groups for producing and making available their model output. The U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison at Lawrence Livermore National Laboratory provides coordinating support for CMIP and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. **Conflicts of Interest:** The authors declare no conflicts of interest. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **IT-Col** & **FR-LBr** & **FI-Hyy** & **CZ-Bk1** & **DK-Sor** \\ \hline \multicolumn{5}{c}{Daily GPP} \\ \hline \(r\) & 0.99 & 0.95 & 0.93 & 0.95 & 0.99 \\ RMB & 0.15 & 0.55 & 0.01 & \(-\)0.14 & 0.00 \\ NRMSE & 0.34 & 0.42 & 0.39 & 1.21 & 0.19 \\ ME & 0.91 & 0.28 & 0.86 & 0.85 & 0.97 \\ MAE & 0.91 & 1.51 & 0.91 & 0.97 & 0.75 \\ \hline \multicolumn{5}{c}{Monthly GPP} \\ \hline \(r\) & 0.99 & 0.96 & 0.93 & 0.99 & 1.00 \\ RMB & 0.15 & 0.52 & 0.01 & \(-\)0.06 & 0.00 \\ NRMSE & 0.31 & 0.40 & 0.38 & 0.15 & 0.16 \\ ME & 0.92 & 0.34 & 0.86 & 0.97 & 0.97 \\ MAE & 20.68 & 41.69 & 26.05 & 14.25 & 20.26 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of the statistics between simulated and measured R\({}_{\text{eco}}\) from the Fluxnet2015 Dataset ([PERSON] et al., 2020 [56]), calculated on the 5 cases studies selected (i.e., Collelongo—IT-Col, Le Bray—FR-LBr, Hyyitala—FI-Hyy, Bilý Kriz—CZ-Bk1, and Soro—DK-Sor). The table shows the daily and monthly values for Person’s Coefficient (r—dimensionless), Relative Mean Bias (RMB—dimensionless), Normalized Root Mean Square Error (MAE, gC m\({}^{-2}\) time\({}^{-1}\)).