## 5 Conclusions  
In the present study, we used simultaneous assimilation of ESA-CCI soil moisture and atmospheric CO\({}_{2}\) in situ observations to constrain the global terrestrial carbon cycle during 1980-2015 within a Carbon Cycle Data Assimilation System (CCDAS). We demonstrated the importance of soil moisture in the TBMs for terrestrial carbon and water cycles modeling with a CCDAS. The conclusions are as follows:  
1. The combination of soil moisture and atmospheric CO\({}_{2}\) concentrations in CCDAS results in a much better simulation of the terrestrial biosphere model in simulating coupled water-carbon processes in ecosystems. For NEP and GPP, the RMSE between the optimized model and Jena CarboScope as well as FLUXCOM is reduced by 6.88% and 14.93% compared to the prior experiment, and by 4.44% and 15.90% compared to only assimilating CO\({}_{2}\). The reason why adding soil moisture observations can better represent the carbon and water cycle is that the soil moisture constrains the model's phenology and photosynthesis through affecting the water uptake and surface energy balance-related parameters (\(V_{cmax}\) T\(\Phi\), Cw0, sdepth, Sb, emis0, and Offset) and additionally controls (through these parameters) plant-available soil moisture. 2. The assimilation of soil moisture has shown the ability of improving the model's representation of inter-annual variability of terrestrial carbon-water cycles and the atmospheric CO\({}_{2}\) growth rate, resulting in high correlations with ENSO indices (soil moisture: \(>\)0.70, NEP: \(<\)\(-\)0.60, GPP: \(<\)\(-\)0.20, and CGR: \(>\)0.40). Soil moisture is the main factor controlling GPP at the time of ENSO events. For continents mainly distributed north of \(30^{\circ}\)N (North America, Europe, and Asia), the ENSO results in lower GPP but higher soil moisture, while for continents mainly south of \(30^{\circ}\) (South America, Africa, and Oceania), ENSO results in the same trend of GPP and soil moisture. We also found that the ENSO shows lagged effects on GPP and varies continently. North America, Asia, and Europe (mainly distributed in the Northern Hemisphere) show a >3-month time lag compared to South America, Africa, and Oceania (mainly distributed in the Southern Hemisphere), which show just a <3-month time lag. * We show that the optimized GPP is capable of reasonably depicting the response of GPP to sub-annual drought (\(\leq\)9 months) by contrasting the continentally aggregated GPP with the comprehensive drought index SPEI. For the GPP optimized by CCDAS with both soil moisture and CO\({}_{2}\) concentration, GPP responded to 68% of droughts detected globally with less than 9 months' duration, while for TRENDY GPP, GIMMS NDVI, and LT_SIF, these percentages are 20%, 34%, and 23%, respectively. Based on this 9-month time scale, we analyzed the regional-scale GPP response to drought and showed that for regions at high latitude in the Northern Hemisphere, where temperature is the primary control of drought, an increase in GPP occurs with the occurrence of drought events. Similarly, for the Amazon rainforest region, where radiation is the main controlling factor, GPP is slightly enhanced when drought occurs. This indicates that using satellite-based soil moisture observations with a data assimilation approach can effectively constrain the water-carbon processes of the model and the simulation results based on this constraint can effectively reveal the response of GPP to sub-annual (\(\leq\)9 months) drought at the regional scale. We noticed that, because a 9-month time scale SPEI was used, the lagged effect of drought could not be shown in most cases. Moreover, the focus was on the relationship between GPP and drought over the previous 36 years at a continental scale; only a coarse spatial resolution (8\({}^{\circ}\)\(\times\) 10\({}^{\circ}\)) could be used due to the constraints of spatial resolution and assimilation duration.