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CMIP6 simulations showed a weak human contribution to 2022-like Central Andes spring droughts, due to compensating impacts between anthropogenic greenhouse gases and aerosols. The Central Andes is a semiarid mountainous [...]

This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

A recent study published in the Bulletin of the American Meteorological Society examines the impact of global warming on typhoons in the East China Sea. The study focuses on the case of Typhoon Hinnamnor, which struck South Korea in September 2022. The researchers found that the unusually warm surface water in the East China Sea contributed to the intensification of the typhoon. Using observational data and climate model simulations, they determined that human activities have made such warm water conditions at least five times more likely. The study suggests that as global warming continues, typhoons in the region may become stronger, but it does not establish whether they will become more or less frequent. [Extracted from the article]

To assess the anthropogenic influence on the summer 2013 heat wave in Korea, this study employed a fraction of attributable risk (FAR) approach to three Atmospheric General Circulation Models (AGCMs) with a large ensemble simulation, participating in the C20C+ Detection and Attribution Project. Monthly and daily temperatures were compared between two experiments. The real world (ALL) experiments were simulated under the observed variations in sea surface temperature, sea ice, greenhouse gas, and aerosol concentrations, while the counterfactual world (NAT) experiments were performed under adjusted boundary conditions by removing anthropogenic warming and with preindustrial levels of greenhouse gases and aerosols. Results from the three AGCMs consistently show that anthropogenic influences had an important role in the extreme heat event over Korea, increasing the chance of the occurrence of extreme warming in summer mean temperature as observed in 2013 by at least 20 times, which supports results from the Coupled Model Intercomparison Project Phase 5 (CMIP5) coupled GCMs (CGCMs). A comparison of individual CMIP5 CGCMs suggests that inter-model difference in FAR values is highly correlated with the amplitude of surface warming centered over Korea, which is also supported by the three AGCMs. Further analysis of individual forcing experiments suggests that the inter-model difference in the regional surface warming is closely linked to the model's response to the aerosol forcing, with stronger influence than that of greenhouse gas forcing. Anthropogenic influences also result in a 5–6 times greater likelihood of extreme daily heat events as observed in 2013, which supports a robust mean-extreme relation in the attribution of extreme heat waves. Generally good agreement between AGCM and CGCM results increases the robustness of the conclusion of anthropogenic influences on the summer 2013 Korean heat wave.