Namyoung Kang

Climate models are essential for investigating and predicting marine heatwaves (MHWs), but their inherent biases pose challenges for accurately analyzing and projecting MHWs. As global warming intensifies, MHWs are expected to become more extreme, emphasizing the need for precise model evaluations and deeper understanding of the underlying causes of bias to improve MHW simulations. In this study, we evaluated the MHW intensity simulated by 30 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in the North Pacific Ocean by comparing them with the optimum interpolation sea surface temperature (OISST) dataset over a 33 year period (1982–2014). Over 80% of the CMIP6 models showed a dipole-pattern bias in the mean MHW intensity over the Kuroshio Extension, characterized by overestimation to the north and underestimation to the south. Hierarchical clustering based on the spatial pattern of the intensity bias in the Kuroshio Extension identifies four distinct clusters: two showing a dipole-pattern bias with slightly different magnitudes and the other two showing weaker or stronger intensity. The separation latitude based on the maximum surface current revealed that the models with the dipole bias pattern simulated the northward overshooting of the Kuroshio Current. This northward overshooting likely enhanced the transport of warmer sea surface temperatures to higher latitudes, thereby intensifying the MHWs. These findings highlight the critical role of ocean currents in the simulation of MHW in the western boundary current regions, including the Kuroshio region.

The geographical response of western North Pacific subtropical high (SH) to environmental conditions such as the El Niño-Southern Oscillation (ENSO) and global warming has been one of the main concerns with respect to extreme events induced by tropical convections. By considering observed outgoing longwave radiation (OLR) as the strength of subtropical high, this study attempts to further understand the geographical response of SH strength to ENSO and global warming. Here, “SH strength” is defined as the inhibition of regional convections under SH environment. A meridional seesaw pattern among SH strength anomalies is found at 130°–175° E. In addition, the La Niña environment with weaker convections at lower latitudes is characterized by farther westward expansion of SH but with a weaker strength. Conversely, the El Niño environment with stronger convections at lower latitudes leads to shrunken SH but with a greater strength. The influence of the seesaw mechanism appears to be modulated by global warming. The western North Pacific subtropical high strengthens overall under warming in both the La Niña and El Niño environments. This suggests that the weakening effect by drier tropics is largely offset by anomalous highs induced by a warming atmosphere. It is most remarkable that the highest SH strengths appear in a warmer El Niño environment. The finding implies that every new El Niño environment may experience the driest atmosphere ever in the subtropics under global warming. The value of this study lies in the fact that OLR effectively illustrates how the ENSO variation and global warming bring the zonally undulating strength of boreal-summer SH.

A refined geometric variability model is employed to examine the environmental relationship to supertyphoon climatology, which is one of the major concerns about climate change and disasters. It is noted that the recent ten years have led to a remarkable weakening of the environmental explanatory power on supertyphoon climatology compared to the past. Different from simple correlation analysis, this study shows how a deformation of the former climatic connection among variables, in a changing climate, is printed on annual covariance elements. Looking into the annual covariance elements, we find that recent observations showing a group of outlying events with a particular drift are more than unfamiliar compared to the former stable relationship from 1985 through 2012. Greater uncertainty thereby amplifies concerns about the looming climate crisis. The drifting climate connection in recent observations is also clear in the eastern North Pacific and the North Atlantic, which observe a sufficient number of super typhoons for reliable statistical analysis. Global analysis is done by applying twelve-month (Jan. to Dec.) observations. While the last few years may look as if the climate connection came back to the former relationship, the drifting of the climate connection is seen to have a certain trend. Interruptions also indicate that the climate system is suffering from unfamiliar conditions on a global scale. Annual monitoring of the climatic connection may show that the relationship might have returned to its past normal, but it seems that more time is needed to confirm the cessation of the drift.

This study employs a refined geometric variability model to look at the environmental relationship to super typhoon climatology, which is one of the major concerns about climate change and disasters. It is noted that adding only several recent years leads to a remarkable weakening of the environmental explanatory power on super typhoon climatology. Looking into the annual covariance elements, we find that the recent observations showing a group of outlying events with a particular drift are more than unfamiliar compared to the former stable relationship from 1985 through 2012. Greater uncertainty thereby amplifies concerns about the looming climate crisis.

Considering that the subtropical highs and tropical convections are observed as negative and positive vorticities respectively, the large-scale features of the atmospheric environment can be effectively represented using streamfunctions as defined by the Laplacian. By investigating the geographical patterns of streamfunctions from different modes of environmental variability, this study conceptualizes how the subtropical high expands and the region for tropical convections migrates in the western North Pacific. It is confirmed that, owing to the expansion of the subtropical high, the limited ocean area for tropical convections even bounded by the equator becomes narrower in the “La Niña mode” than that in the “El Niño mode”. This study finds that a warmer environment is likely to further expand the subtropical high to the west, and then the westernmost shift in the region for tropical convections appears in the “warmer La Niña mode”. A linear perspective suggests that every warmer La Niña environment could be one that people have scarcely experienced before.

Characteristics of marine heatwaves (MHWs) in the East Asian Marginal Seas (EAMS) were investigated using the daily Optimum Interpolation Sea Surface Temperature for 37 years (1982–2018), focusing on seasonal changes and regional differences. The summer MHWs occur 54% more frequently (2.7 events/decade) in a relatively wide area than in other seasons. The strong (up to 3.7 °C) and long-lasting (up to 38 days/event) winter MHWs are concentrated along the subpolar front (SPF) in the East/Japan Sea (EJS) where the MHWs are 20% longer (2.2 days/event) than in the Yellow and East China Seas (YECS). The summer MHWs are primarily driven by increased shortwave radiation associated with reduced cloud cover and latent cooling from the weakened wind over the western flank of developing subtropical highs. Driving mechanisms of the winter MHWs differ by region. The YECS MHWs occur mainly due to the atmospheric processes associated with weakening continental highs, while the EJS MHWs are largely driven by the northward shift of the SPF. Although large-scale atmospheric processes primarily drive the summer MHWs occurring in a wide area in the EAMS, our findings suggest that ocean processes can be major contributors to intensified MHW generation in limited areas, especially in winter.

Despite the improving techniques for seasonal prediction of tropical storm frequency, attention seems focused on accuracy rather than on forecast interpretation. This study aims to show how seasonal predictions from a hybrid model, i.e. statistical/dynamical model, can be interpreted with probability distributions. The tropical storm frequency in the western North Pacific is modeled with environmental predictors through multiple linear regression. For a demonstration of the probabilistic structure of the prediction result, the forty-two member ensemble predictions from the Glosea5 model for June–July–August in 2020 are used as the dynamical input. Rather than dealing with the expected frequency, this study introduces the predictive probability for a single value of the frequency. From as many probability distributions, a marginal probability distribution is obtained as the final predictive probability distribution. The probability distribution is then compared to the climatological reference by terciles. Additionally, predictive probability distributions made with the individual predictors provide helpful information on how each contributes to the final prediction. This probabilistic interpretation procedure is expected to be effectively used for improving any hybrid approach.