The rapid intensification (RI) of tropical cyclones (TCs) associated with global warming is a matter of concern worldwide. This study examines how the RI across the western North Pacific is related to the so-called 'efficiency of intensity' (EINT) environment induced by global warming. The EINT condition has been characterized by a strong anomalous high over an unstable tropical atmosphere, which supports efficient intensification. Here, we show that global warming significantly increases the proportion of RI-experiencing TCs through EINT environment. Global warming explains up to 51.3 % of the variation in the proportion of RI-experiencing TCs with 93.0 % of that related to EINT. Even the influence of El Niño and Southern Oscillation on the proportion of RI events, though small (16.1 %), is mostly through an EINT environment (73.9 %). Despite the increasing proportion of RI events among TCs, the number shows no trend over time as the EINT condition inhibits the number of overall TC occurrences. The findings are confirmed by the observational consensus between U.S. Joint Typhoon Warning Center and Japan Meteorological Agency.

Marine Heatwaves (MHWs) are extreme climatic events that last for days to months and can extend up to thousands of kilometers, causing higher substantial ecological, social, and economic impacts. Climate models is a key tool to study and predict the MHWs. However, it remains a challenge for climate models to simulate MHWs accurately. In this study, we evaluate 29 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and 8 models from CMIP5 to simulate MHWs from the aspects of spatial patterns and temporal variation, and then we estimate future changes to the end of the 21st century under three socioeconomic pathways (SSP1, SSP2, and SSP5). Results show that the CMIP6 ensemble mean is more skillful in capturing the features of MHWs than CMIP5.The bias for MHWs intensity is within ±0.5℃ over most of the ocean, except in the west boundary current region and eastern tropical Pacific where the models are up to 1.5℃ less than observation, while the results from CMIP5 are more than ±1.5℃ in most area. Both CMIP5 and CMIP6 models underestimate the long-duration MHWs in the eastern tropical Pacific, where are nearly 20 days less than the observation. In most areas, CMIP5 overestimate the duration of MHWs (> 25 days), while CMIP6's bias is within 10 days. The future MHWs are projected to increase significantly both in intensity and duration, reach maximum intensities of 4℃. The largest changes are projected to occur in the tropical and North Pacific, and North Atlantic. The socioeconomic pathways affect the increasing trend of MHWs, the most extreme MHWs occur under SSP5, with intensity nearly doubling and near-permanent MHW state occurring since the 2070s. 

As the global sea surface temperature (SST) increases, the frequency and intensity of marine heatwaves (MHWs), persistence of a significant high SST over a certain period, are also increasing. MHWs have been intensified and are projected to increase in the future. MHWs contribute to substantial socio-economic damages by changing the marine ecosystem such as a decrease in catch production and species diversity; and increases in the occurrences of mass mortality of farming fishes and harmful algae blooms. Future changes in global MHWs have generally been projected by global earth system models such as CMIP6 (Coupled Model Project Intercomparison Phase 6) models. In this study, we evaluate marine heatwaves in the historical simulation of 14 CMIP6 models by comparing the CMIP6 simulation with the OISST (Optimum Interpolation Sea Surface Temperature) reanalysis data for 34 years (1982 to 2015). Most of the 14 CMIP6 models show longer duration of MHWs by about 20 days in the Bering Sea compared to OISST. On the other hand, the intensity of MHWs in the North Pacific Ocean was underestimated by about 0.3℃ for 80% of models compared to OISST. The underestimated intensity appears to be associated with a smoothing effect due to the low spatial resolution of the CMIP6 models. We also plan to present future changes in the MHWs projected by the CMIP6 models and their relationship with the biases of the CMIP6 models.

Long-term variability of ocean temperature in the western North Pacific was investigated by using the ScenarioMIP experiments which are integrated under the shared socio-economic pathway (SSP) scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. CMIP6 models including KIOST-ESM are involved in this study. The analysis of KIOST-ESM suggests the evident rising of sea surface temperature (SST) over the 21st century in the SSP2-4.5 and SSP5-8.5, while the warming trend is not significant in SSP1-2.6. The amount of SST change is also dependent on regions. SST difference between 2081-2100 and present (1995-2014) is maximum in the separation points of western boundary currents, the Kuroshio and East Korea warm current. Especially, the maximum SST change between two periods is more than 4°C in the SSP5-8.5 experiment. This is probably due to both the warming effect and northward shift of the western boundary currents. The increase of ocean temperature is maximum at the surface and it decreases with depth. At least in the western North pacific and East/Japan Sea, ocean temperature increases at all depths in 2081-2100 compared to the present (1995-2014). We will also compare the results of the ScenarioMIP experiments from other CMIP6 models to estimate the uncertainty of the long-term variability of the ocean temperature.

Indonesia, a tropical maritime continent between the Pacific Ocean and the Indian Ocean, experiences extreme rainfall more frequent in a changing climate. This is leading to a major disaster such as floods and landslides. These disasters are disrupting economic activity and impacting human daily life, and the future change projection, therefore, is important to reduce the impact of extreme rainfall in Indonesia. In this study, we examine the linking of the annual maximum of daily rainfall series with climate variability phenomena by optimizing statistical extreme value analysis (EVA) using 30 years (1985-2014) recorded daily rainfall series from 10 meteorological stations around Java and Makassar Island. Maximum likelihood estimation was used to find parameters of Generalized Extreme Value Distribution (GEVD). Four non-stationary models corresponded to climate variability imposed to the annual maxima series and the best-fitted model in each station selected based on the smallest corrected Akaike Information Criterion (AICc) and likelihood ratio test. Using the trend-free prewhitening (TFPW) Mann-Kendall test, the daily precipitation annual maxima had increased significantly over the country by 29.5 mm/day over 30 years period. Only Surabaya station shows the increasing trend significantly. Furthermore, based on the best selected non-stationary model, Waingapu and Luwuk covariate significantly with El Nino Southern Oscillation (ENSO), while Perak and Jakarta station covariate insignificantly to Indian Ocean Dipole (IOD). On the contrary, the Madden-Julian Oscillation signal in annual maxima was less prominent in all stations thus not improving the stationary GEV model. A composite analysis reveals that the annual maxima are more robust during La Nina and negative IOD phase compare to El Nino and positive IOD phase. These results imply that the properties of extreme rainfall on sea-air interaction phenomena vary throughout all stations geographically and show phase-locking behavior.

The East sea (Japan Sea) (EJS here after) experienced the surface warming slowdown from 2000 to 2014 (-0.05 ℃ yr^-1 ) but had inversely subsurface (100-300 m) temperature increase (0.03 ℃ yr^-1). To find the causes of two different processes, the trend changes in sea level anomaly, isopycnal depth, and wind pattern were analyzed using monthly mean Ocean Reanalysis System 4 (ORAS4) data from 1980 to 2017. During this period of surface warming slowdown, the strengthened northerly wind enhanced the positive and negative wind stress curl in the western and eastern north EJS, resulting in forming the cyclonic and the anticyclonic ocean circulation accordingly. Consequently, the former and the latter induce oceanic divergence and the convergence at the same time there, respectively. Overall, these two processes cause lower the sea surface temperature, resulting in a surface warming slowdown in the EJS.