The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ^∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ^∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ^∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ^∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

The East Sea Intermediate Water (ESIW) is the subsurface salinity minimum layer in the depth range 200–400 m in the East/Japan Sea. The origin, variability, and pathways of the ESIW were investigated using a 4‐year‐long (2015–2018) high‐resolution (1/24°) ocean reanalysis and Lagrangian particle modeling. A backward particle tracking analysis revealed that the ESIW was formed south of Vladivostok and shows strong interannual variability. In 2018, owing to strong northwesterly winds, heat loss to the air intensified, and freshwater transport from the northern East/Japan Sea was simultaneously decreased by about 18% compared with the previous year. Furthermore, there was increased formation of water masses heavier than that of the typical ESIW, and the volume of the ESIW was reduced. A forward particle tracking analysis showed that the contribution of the particles originated from the northern end of the East/Japan Sea was about two times greater than those from the southern end. The major portion of the ESIW's freshwater came from the northern East/Japan Sea, where sea ice melted and the Amur River discharged. The remaining portion was from the Changjiang River, which came through the Korea Strait. The ESIW reached the Ulleung Basin over the course of a year mainly through the deep channel, the Ulleung Trough, located to the north of the basin. The diapycnal diffusivity of 1.0 × 10⁻⁴ m² s⁻¹ could erode away the low salinity core in about 27 years.

The impacts of observation data sets on the high-resolution (1/24°) Northwest Pacific prediction system were investigated with the model sensitivity tests. We compared the model experiments assimilating the different combinations of the observation data sets, such as the sea surface height derived from satellite altimetry, sea surface temperature, and in-situ profiles, based on the Ensemble Optimal Interpolation. Pseudo-profiles constructed by the method of Cooper and Haines (1996, CH96) were assimilated into the model to assimilate sea surface height data. CH96 applied a conservation principle to derive pseudo-profiles by rearranging preexisting profiles. The comparison of the model experiments suggests that each observation data set enhances the model performance. Especially, the assimilation of the sea surface height reduces the model error by more than 9.81% and 6.44%, respectively, in terms of the root-mean-square error of the ocean temperature and salinity in the subsurface layer. It is interesting that the assimilation of the in-situ temperature profiles in the Korean marginal seas contributes to improving the reproducibility of the subsurface temperature and salinity in the East/Japan Sea (EJS) as well as Kuroshio-Kuroshio Extension (K-KE) regions. The improvement in the K-KE region seems to be related to the reproducibility of the Kuroshio axis. As the water mass in the EJS flows into the Pacific Ocean through the Tsugaru Strait, it affects the front of the Sanriku confluence, and it seems to eventually control the Oyashio Current and Kuroshio axis. In conclusion, this study evaluated the contribution of each observation component to ocean analysis in the KOOS-OPEM and confirmed the role of the existing observation networks. This study also suggests that greater attention should be paid to the role of regional ocean observation networks to improve the forecast skill of the ocean prediction system not only in the region but also in the open ocean, such as the Pacific Ocean.

The Northwest Pacific (NWP) has a complex ocean circulation system and is among the regions most affected by climate change. To facilitate rapid responses to marine incidents and effectively address climate variability impacts, the Korea Institute of Ocean Science and Technology (KIOST) developed the Korea Operational Oceanographic System–Ocean Predictability Experiment for Marine Environment (KOOS-OPEM), a high-resolution regional ocean prediction system based on Modular Ocean Model version 5 (MOM5). In this study, the base model of KOOS-OPEM was upgraded to MOM6 to enhance its regional ocean modeling capabilities. A key advancement of MOM6 is its flexible vertical coordinate system enabled by a Lagrangian remapping system. Taking advantage of this feature, we evaluated the impact of vertical coordinate choices on model performance by comparing the HYBRID (z^∗-isopycnal) and ZSTAR (z^∗) configurations. Model outputs from the 2003–2012 period were assessed against multiple observational datasets and reanalysis products to determine their ability to reproduce key oceanographic features. The results indicated that HYBRID better preserved stratification and reduced spurious diapycnal mixing, significantly improving the representation of North Pacific Intermediate Water (NPIW). In contrast, ZSTAR exhibited excessive diapycnal mixing, resulting in a thicker isopycnal layer associated with NPIW and a salinity bias of approximately 0.2 psu. An idealized age tracer experiment further confirmed that ZSTAR facilitates excessive downward diffusion of younger surface waters, eroding the minimum salinity layer of the NPIW. In tidal simulations, HYBRID outperformed ZSTAR in reproducing M2 tidal amplitudes in the Yellow Sea, where stratification plays a key role. Conversely, ZSTAR underestimated these amplitudes due to its limitations in representing stratification. Despite its advantages, HYBRID underperformed in high-latitude regions, exhibiting larger temperature and salinity biases between 100 and 600 m depth, with temperature biases reaching approximately −1 °C. This discrepancy arose because HYBRID maintained fewer active layers in weakly stratified regions, reducing vertical resolution and leading to errors in water mass representation. To mitigate these issues and improve HYBRID's performance in high-latitude regions, adjustments to target density profiles are necessary. In addition, both configurations showed limitations in simulating winter SST, largely due to insufficient vertical resolution in the surface mixed layer. To address these issues, adopting a finer surface layer resolution (e.g., 1 m instead of 2 m) will further enhance the model's representation of mixed-layer processes.

The formation mechanism as well as its temporal change of the North Pacific subtropical mode water (NPSTMW) is investigated using a 50‐year (1960–2009) ocean general circulation model hindcast. The volume budget analysis suggests that the formation of the NPSTMW is mainly controlled by the air‐sea interaction and ocean dynamics, but there is a regime shift of the relative importance between the two around late‐1980s. While the local air‐sea interaction process is a main driver of the NPSTMW formation prior to late‐1980s, ocean dynamics including the vertical entrainment become dominant since then. The NPSTMW formation is affected by the North Pacific Oscillation simultaneously in the early period, but with a few years lag in the later period. The interdecadal change of the driving mechanism of the interannual variability of the NPSTMW is probably due to the stronger (weaker) influence of local atmospheric forcing in the western North Pacific and unfavorable (favorable) wind stress curl condition for the remote oceanic forcing from the central North Pacific during the former (later) period. This regime shift may be related to the change of centers of the actions of the wind stress curl since the late‐1980s.