## 1 Introduction
A comparison of modelled gross and net primary productivity [26] of six different models, CASA [43], GLO-PEM [44], TURC [45], MODI7 [46], BEAMS [47] and C-Fix [48], illustrates how the various methodologies used to calculate vegetation productivity can be generalized in the following two equations:  
\[GPP=PAR\times fAPAR\times RUE_{MAX}\times Stress\ factors \tag{1}\]  
\[\mathrm{NPP}=\mathrm{GPP-AR} \tag{2}\]  
where PAR is Photosynthetically Active Radiation (MJ/m\({}^{2}\)), fAPAR is the Fraction of Absorbed PAR (dimensionless), RUE\({}_{MAX}\) is the maximum Radiation Use Efficiency (gC/MJ) (_i.e._, RUE under no stress), which is downregulated by a coefficient that encompasses the effects of all stress factors such as temperature stress or water stress, and AR is Autotrophic Respiration (gC/m\({}^{2}\)/day). In general, variation among the models is caused by the differences in RUE, the incorporation of stress factors, and AR [26]. The initial model conditions, model parameters, model structures and accuracy of input data also play an important role [42; 49]. Uncertainties in global GPP/NPP monitoring also relate to the determination of RUE, AR and the quality of meteorological and the biophysical data [26; 46; 50; 51]. In this study, we analyse the Copernicus Global Land Service-Dry Matter Productivity (CGLS-DMP) product. This model is part of the operational processing chain of SPOT VEGETATION and the following Proba-V at the Vlaamse Instelling Voor Technologisch Onderzoek (VITO). The parametric CGLS-DMP model estimates carbon mass fluxes at local, regional and global scales [48], and has proved usefulness in vegetation productivity studies such as grasslands and forests [52; 53; 54]. For a given location, carbon fluxes are estimated on a decadal basis using SPOT VEGETATION and resulting in a DMP product. Different DMP versions have evolved since the early 1990s [55]. The C-Fix approach (a variant of [PERSON]'s approach) was applied, to monitor the overall carbon balance over Europe in terms of NPP [37]. In the late 1990s, an operational chain was established to retrieve dekadal DMP images over Belgium based on C-Fix using SPOT VEGETATION for crop monitoring. Around 2000, a consortium was established for JRC-MARS. There have been different MARSOP projects in operation (MARSOP1 from 2001-2003, MARSOP2 from 2004-2007, MARSOP3 from 2008-2014, MARSOP4 from 2015-2019). The DMP coverage has been global except for MARSOP1 which was the Mediterranean Basin, part of the Commonwealth of Independent States (CIS--former Soviet Union), Mercosur in South-America, and the Horn of Africa. The procedure for MARSOP1 was the same as C-Fix. The RUE in optimal conditions has been taken as 1.10 kg. C/GJ for NPP and 2.45 kg. DM/GJ for DMP. It is considered constant for all land cover types, while differences exist between biomes, causing the operational DMP product to over/underestimate reality [22; 56]. The RUE value is subsequently reduced by normalised temperature and CO\({}_{2}\) fertilisation dependency factors. With the start of MARSOP2, the temperature errors were corrected using \(T_{12}\) for temperature and CO\({}_{2}\) fertilisation efficiencies, and \(T_{24}\) for autotrophic respiration instead of simply using mean temperature (Equations (3) and (4)). \[T_{12}=0.75+(T_{min}+T_{max}) \tag{3}\]  
\[T_{24}=0.50+(T_{min}+T_{max}) \tag{4}\]  
where \(T_{min}\) is the minimum daily temperature and \(T_{max}\) is the maximum daily temperature. The grid of the meteorological data has been changed from \(1^{\circ}\) to 0.25\({}^{\circ}\) with MARSOP3. For all projects, while calculating CO\({}_{2}\) fertilisation efficiency, the CO\({}_{2}\) value used was fixed at 355.61 ppmv, the global mean level of the year 1994. For MARSOP1 and 2, in order to estimate fAPAR, the linear relationship between NDVI and fAPAR was used. For MARSOP3 and 4, the global fAPAR is computed based on [20]. The DMP has been produced in the CGLS since 2014 using the same meteo data, algorithm and constants as the MARSOP4 DMP [57].