Scientists occasionally predict projected changes in extreme climate using multi-model ensemble methods that combine predictions from individual simulation models. To predict future changes in precipitation extremes in the Korean peninsula, we examined the observed data and 21 models of the Coupled Model Inter-Comparison Project Phase 6 (CMIP6) over East Asia. We applied generalized extreme value distribution (GEVD) to a series of annual maximum daily precipitation (AMP1) data. Multivariate bias-corrected simulation data under three shared socioeconomic pathway (SSP) scenarios—namely, SSP2-4.5, SSP3-7.0, and SSP5-8.5—were used. We employed a model weighting method that accounts for both performance and independence (PI-weighting). In calculating the PI-weights, two shape parameters should be determined, but usually, a perfect model test method requires a considerable amount of computing time. To address this problem, we suggest simple ways for selecting two shape parameters based on the chi-square statistic and entropy. Variance decomposition was applied to quantify the uncertainty of projecting the future AMP1. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1973–2010), were estimated for three overlapping periods in the future, namely, period 1 (2021–2050), period 2 (2046–2075), and period 3 (2071–2100). From these analyses, we estimated that the relative increases in the observations for the spatial median 20-year return level will be approximately 18.4% in the SSP2-4.5, 25.9% in the SSP3-7.0, and 41.7% in the SSP5-8.5 scenarios, respectively, by the end of the 21st century. We predict that severe rainfall will be more prominent in the southern and central parts of the Korean peninsula.

We investigated the effect of artificial marine cloud brightening on extreme temperatures over East Asia. We used simulation data from five global climate models which have conducted the GeoMIP G4cdnc experiment. G4cdnc was designed to simulate an increase in the cloud droplet number concentration of the global marine lower clouds by 50% under the greenhouse gas forcing of the RCP4.5 scenario. G4cdnc decreased the net radiative forcing in the top of the atmosphere more over the ocean, alleviating the rise in mean temperature under RCP4.5 forcing. For extreme temperatures, G4cdnc reduced both the monthly minimum of daily minimum temperature (TNn) and monthly maximum of daily maximum temperature (TXx). The response of TNn was higher than that of TXx, especially in the winter, over the Sea of Okhotsk and the interior of the continent. This spatial heterogeneity and seasonality of the response were associated with sea ice–albedo and snow–albedo feedbacks. We also calculated the efficacy of warming mitigation as a measure of the relative effect of geoengineering. The efficacy for TXx was higher than that for TNn, opposite to the absolute effect. After the termination of geoengineering, both TNn and TXx tended to rapidly revert to their trend under the RCP4.5 forcing.

Potential intensity (PI) is a metric for climate model evaluation of TC-related thermodynamic conditions. However, PI is utilized usually for assessing basin-wide TC-related thermodynamic conditions, and not for evaluating TC passage to a certain region. Here we evaluate model-simulated PI over the passage of TCs affecting South Korea (KOR PI) as well as the PI over the entire western North Pacific basin (WNP PI) using 25 CMIP5 and 27 CMIP6 models. In terms of pattern correlations and bias-removed root mean square errors, CMIP6 model performances for KOR PI are found to be noticeably improved over CMIP5 models in contrast to negligible improvement for WNP PI, although it is not in terms of normalized standard deviations. This implies that thermodynamic condition on the route of TCs affecting South Korea is likely better captured by CMIP6 models than CMIP5 models.

The goal of the present study is to elucidate and assess the observed closure and annual variations of the water cycles for the Asian continent and its constituent climatic regions. For this purpose, heavy reliance is placed on simulation as well as observational data. The difference between moisture convergence (MC) and runoff (R) is used as an inverse measure of the closure. Areal averages of MC − R are compared between different areas to decide on its scale dependency and also between different climatic regions categorized by Köppen's climate classification to investigate their annual variations. Atmospheric Model Intercomparison Project (AMIP) II standard output data were used for simulation. The normal annual means of hydrological variables averaged over the Asian continent are similar between the AMIP II ensemble (MOD) data and the observational (OBS) counterparts, even though MOD and OBS do not exactly agree in terms of their respective regions of distinctive features. In the Asian continent, both OBS MC − R and MOD MC − R are small but in the case of OBS the smallness was due to cancellation of two large and opposite MC − Rs for the dry and mesothermal climatic regions. An appraisal of the closure for each climatic regions has been attempted through comparison between MOD MC − R and OBS MC − R. Nevertheless the relatively poor closures in these two climatic regions surely pose a problem for the simulation community. The mean annual variations of MOD MC and MOD R, averaged for the Asian continent and its climatic regions, respectively, were analyzed for their uncertainty using the Taylor diagram. MOD R in the dry regions and MOD MC in the microthermal and polar regions are unreliable.

In recent decades, extremely cold winters have occurred repeatedly throughout the Northern Hemisphere, including the Korean Peninsula (hereafter, Korea). Typically, cold winter temperatures in Korea can be linked to the strengthening of the Siberian High (SH). Although previous studies have investigated the typical relationship between the SH and winter temperatures in Korea, this study uniquely focused on a change in the relationship, which reflects the influence of the Arctic Oscillation (AO) and El Niño–Southern Oscillation (ENSO). A significant change in the 15-year moving correlation between the SH and the surface air temperature average in Korea (K-tas) was observed in January. The correlation changed from −0.80 during 1971–1990 to −0.16 during 1991–2010. The mean sea-level pressure pattern regressed with the temperature, and a singular value decomposition analysis that incorporated the temperature and pressure supports that the negative high correlation during 1971–1990 was largely affected by AO. This connection with AO is substantiated by empirical orthogonal function (EOF) analysis with an upper-level geopotential height at 300 hPa. In the second mode of the EOF, the temperature and pressure patterns were primarily affected by ENSO during 1991–2010. Consequently, the interdecadal change in correlation between K-tas and the SH in January can be attributed to the dominant effect of AO from 1971–1990 and of ENSO from 1991–2010. Our results suggest that the relative importance of these factors in terms of the January climate in Korea has changed on a multidecadal scale.