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Stomatal closure is a major physiological response to the increasing atmospheric carbon dioxide (CO2), which can lead to surface warming by regulating surface energy fluxes—a phenomenon known as CO2 physiological forcing. The magnitude of land surface warming caused by physiological forcing is substantial and varies across models. Here we assess the continental warming response to CO2 physiological forcing and quantify the resultant climate feedback using carbon–climate simulations from phases 5 and 6 of the Coupled Model Intercomparison Project, with a focus on identifying the cause of inter-model spread. It is demonstrated that the continental (40°–70°N) warming response to the physiological forcing in summer (~0.55 K) is amplified primarily due to cloud feedback (~1.05 K), whereas the other climate feedbacks, ranged from –0.57 K to 0.20 K, show relatively minor contributions. In addition, the strength of cloud feedback varies considerably across models, which plays a primary role in leading large diversity of the continental warming response to the physiological forcing.

South Korea’s heat wave events over 39 years (1980–2018) were defined by spatiotemporal criteria, and their quantitative characteristics were analyzed. The duration and intensity of these events ranked highest in 2016 and 2018. An examination of synoptic conditions of heat wave events in 2016 and 2018 based on a reanalysis dataset revealed a positive anomaly of 500-hPa geopotential height, which could have induced warm conditions over the Korean Peninsula in both years. However, a difference prevailed in that there was a blocking high over the Kamchatka Peninsula and a continental thermal high over northern China in 2016, while the expansion of the western North Pacific subtropical high was mainly associated with 2018 heat wave events. Numerical experiments using the Weather Research and Forecasting (WRF) Model were conducted to 1) evaluate how distinct meteorological characteristics of heat wave events in 2016 and 2018 were reproduced by the model, and 2) investigate how they affect extreme temperature events. Typical synoptic features of the 2016 heat wave events (i.e., Kamchatka blocking and continental thermal high) were not captured well by the WRF Model, while those of 2018 were reasonably reproduced. On the contrary, the heat wave event during late August 2016 related to the Kamchatka blocking high was realistically simulated when the blocking was artificially sustained by applying spectral nudging. In conclusion, the existence of a blocking high over the Kamchatka region (i.e., northern Pacific region) is an important feature to accurately predict long-lasting heat waves in East Asia.