## 4 Summary and Conclusions
Some regions, such as South Asia, were less affected than East Asia and the global mean; MLRM found a small number of statistically significant parameters among forcings in South Asia. Although other causes (e.g., land use) are possible, the regionally variable AER emissions might mainly explain the spatial gap in the model results of net radiation and PR. Variables that include sub-variables or are intertwined with other variables tend to involve multiple forcings. For instance, AER can be regarded as a dominant forcing to net radiation because aerosols can block incoming solar radiation. However, in the present study, net radiation was significantly affected not only by AER but also by GHG. In the time-series plots, both ET and SH apparently followed the variations in net radiation. Meanwhile, the ET ratio was mainly influenced by GHG. As ET and SH are correlated due to a summation relationship and SH is strongly related to AER, we note that ET can be affected by GHG. Hence, the dual forcing effect (AER and GHG) on net radiation might be attributable to two-variable combinations (ET + SH). This study also showed that GHG accelerates energy exchange, water cycle, and photosynthesis. The GHG-only simulations showed an increase in precipitation and evapotranspiration. GHG also enhances the PR intensity, causing a high runoff rate. TSM and water balance analyses showed that the available water of the land has increased. However, SSM showed a decreasing trend in the recent past. Here, higher PR than ET and runoff should increase SSM, but the fast water cycle induced by high PR intensity (same amount of PR at low frequency) and the raised ET rate appears to prevent an increase in SSM. GHG changes can also shift surface conditions. The ET ratio, which can be related to the Bowen ratio, strongly followed the GHG trend. The increase in these variables impliesthat the surface is becoming a wet climate globally (based on the Bowen ratio classification). The WUE, which defines the GPP to ET ratio, dramatically increased and strongly followed the GHG-only simulation, indicating that plant productivity has increased by elevated CO\({}_{2}\). The models we used for this study can have errors. However, this analysis comes from the advanced models which have long been verified and possess rationality with respect to simplification. In conclusion, DAMIP analysis identified a role for GHG and AER on the land surface and behaves similarly to PR and TAS. Their contributions to each variable within the water and energy balance equations were explored in an MLRM. This method helped to identify the role of natural forcing, which has been usually ignored in previous studies. The study revealed that greenhouse gas tends to accelerate land surface processes, possibly causing extreme processes such as runoff. However, some variables were positively affected by GHG; for instance, GPP and its efficiency both increased. Planning scenarios normally focus on the climatologic consequences of GHG. However, we need to be concerned about balances between GHG and other fluxes (aerosol and natural variations) regarding land surface processes. This study was limited to past simulations, but a DAMIP analysis about the future, when GHG and AER are expected decrease, may be needed. Moreover, the MLRM analysis was limited to the global scale and a few regions. Mapping MLRM parameters and analyzing future scenarios are interesting topics to be addressed in our future research. [PERSON] wrote the manuscript and contributed to the graphics. [PERSON], [PERSON]-S.K., [PERSON]-H.L., [PERSON]-H.B., and [PERSON]-H.K. contributed to the discussion and revision of the manuscript. All authors have read and agreed to the published version of the manuscript. This research was funded by the Korea Meteorological Administration Research and Development Program Development and Assessment of Climate Change Scenario under Grant (KMA2018-00321). Not applicable. The data presented in this study are available upon request from the corresponding author.