## 3 Results
### Water Balance  
Both total and surface soil moisture tended to increase in most places (\(p\)-value < 0.05), but decreases were found in some places, such as the Amazon (Figure 6a-d). More statistically significant changes (dots in the maps of Figure 6) were detected in the total soil moisture (TSM) than in the SSM. We note that SSM data represents 5 cm depth (Figure 6a,b) and the depth known to be detectable by remote-sensing [55]. However, the depth of TSM can be varied among models depending on groundwater existence, vertical resolution, root depth, or the decisions of a model developer (Figure 6c,d). The analyzed results used normalized values or represented the differences between two periods, so the change in water amount can be adequately detected regardless of the depth. Thus, we assumed that the TSM results adequately represented change in TSM. As shown in Figure 6b, the historical simulation of SSM is followed the AER-only simulation. SSM gradually increased since 1870 and decreased from around 1970, opposing PR and net radiation trends. The reduction in net radiation may have caused the SSM increase in the early period, although PR decreased simultaneously. The rebounding of the net radiation might have caused soil moisture loss after 1970 despite growing PR. Moreover, soil moisture reduction after 1970, along with the increased PR and net radiation, suggests that the surface water cycle was accelerating at the surface. Unlike surface moisture, TSM values have constantly increased (Figure 6d). We need to note that TSM has a slower response than the SSM, and while the global-mean soil moisture has slightly changed, TSM  
Figure 5: Results of latent heat (\(\sim\)-evapotranspiration, ET) and sensible heat (SH) flux analyses and their ratio (ET Ratio): (**a**) time series plot of global ET; (**b**) plot of ET in East Asia; (**c**) plot of global SH; (**d**) plot of SH in East Asia; (**e**) plot of global ET Ratio; (**f**) plot of ET ratio in East Asia. The titles above the plots and the legends within the plots are followed by the number of ensemble models in parentheses, and the estimated parameters with hats provide statistical significances (\(p\)-value \(\leq\) 0.05). has undergone statistically significant changes throughout the world, indicating that water balance has certainly been altering (Figure 6c). For instance, the soil moisture has decreased in the Amazon area, which is an important \"breathing\" source of the Earth, and increased in the west of the USA and Europe. The estimated water budget (\(P-(ET+O)\)), which is equivalent to \(I+S\), indicates that the incoming PR exceeds the outgoing water fluxes (Figure 6e,f). Only a few areas have significance, but we can observe that most of the areas have an increasing trend. This can be a reason for the rise soil moisture since the water budget has been increasing over time and is always larger than zero. It may explain the rising soil moisture. In Figure 6f, the values were normalized by their total average in order to detect the slope. This analysis may involve timing-related or over-simplification errors because the land surface process is a complicated system (e.g., snow melting). Moreover, the number of ensemble models was unavoidably small because the analysis used variables' combinations, and we selected models having all sets (AER, GHG, NAT, and Historical). Moreover, analyzing individual sets (e.g., only GHG regardless of \"all sets\") that provide an increased number of ensemble members produces similar results. Figure 6: Results of surface soil moisture (SSM), total soil moisture (TSM), and water budget (\(P-(ET+O)\)) analyses, where O is the surface runoff: (**a**) 50-year mean start-to-end difference in SSM; (**b**) time series plot of global SSM; (**c**) 50-year mean start-to-end difference in TSM; (**d**) time series plot of global TSM; (**e**) 50-year mean start-to-end difference in \(P-(ET+O)\); (**f**) time series plot of global \(P-(ET+O)\). The water budget was normalized by the whole-period average.