In early summer 2020, the Meiyu-Baiu rainfall was markedly enhanced, triggering devastating floods in Japan and central China. We examined the underlying processes using a climate model and analysis. The enhanced Meiyu-Baiu rainfall was reasonably predicted by the climate model initialized at the end of April. The sensitivity experiment indicated that Indian Ocean (IO) warming enhanced the Meiyu-Baiu rainfall. Moreover, we found that the warm IO condition can be traced back to the super Indian Ocean Dipole (IOD) in 2019. The IO warmth was influenced by successive processes: record strong downwelling Rossby waves excited by the IOD and tripole sea surface temperature anomalies in the tropical IO-western Pacific, their arrival to the southwestern IO in spring, and associated modulation of monsoon flow. The results suggest that the seasonal predictability of the Meiyu-Baiu rainfall in 2020 originated from the super IOD. Plain Language Summary In early summer 2020, Japan and central China suffered from serious floods due to torrential rainfall associated with the intensified Meiyu-Baiu front, which extends from central China to southern Japan. The results of climate model simulations indicated that a warm condition of the Indian Ocean (IO) was an underlying condition for the enhanced rainfall. We found that the warm IO condition can be traced back to the strong Indian Ocean Dipole (IOD) episode in 2019, which featured a pair of colder-than-normal and warmer-than-normal ocean temperatures west of the Sumatra coast and in the western IO, respectively. This IOD contributed to the IO warming in the following seasons through oceanic dynamics and monsoon modulation.

Ocean heat content (HC) is one of the key indicators of climate variability and also provides ocean memory critical for seasonal and decadal predictions. The availability of multiple operational ocean analyses (ORAs) now routinely produced around the world is an opportunity for estimation of uncertainties in HC analysis and development of ensemble-based operational HC climate indices. In this context, the spread across the ORAs is used to quantify uncertainties in HC analysis and the ensemble mean of ORAs to identify, and to monitor, climate signals. Toward this goal, this study analyzed 10 ORAs, two objective analyses based on in situ data only, and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability, and long-term trend of HC in the upper 300 m (HC300) from 1980 to 2009 are compared. The spread across HC300 analyses generally decreased with time and reached a minimum in the early 2000s when the Argo data became available. There was a good correspondence between the increase of data counts and reduction of the spread. The agreement of HC300 anomalies among different ORAs, measured by the signal-to-noise ratio (S/N), is generally high in the tropical Pacific, tropical Indian Ocean, North Pacific, and North Atlantic but low in the tropical Atlantic and extratropical southern oceans where observations are very sparse. A set of climate indices was derived as HC300 anomalies averaged over the areas where the covariability between SST and HC300 represents the major climate modes such as ENSO, Indian Ocean dipole, Atlantic Niño, Pacific decadal oscillation, and Atlantic multidecadal oscillation.

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[1] We examined decadal variability of the Subtropical Front (STF) of the western North Pacific by using a North Pacific ocean general circulation model (OGCM), comparing the results of three simulations with different horizontal resolutions. In the long-term mean fields, the eddy-resolving model (10 km) was able to simulate the distributions of the STF and the associated Subtropical Countercurrent (STCC) between 20°N and 30°N better than either the non-eddy-resolving model (100 km) or the eddy-permitting model (20 km) because it simulated the Kuroshio recirculation gyre more realistically. The simulated STF intensity exhibited significant decadal-scale variations: it was stronger in the late 1970s and weaker in the early 1990s. During these two periods, the simulated mode waters showed corresponding differences in their potential vorticity minima density and paths. We also investigated the relationship between the decadal-scale STF variability and atmospheric forcing. The results suggest that the decadal-scale STF variability can be largely explained by changes in the mode waters formed in the western North Pacific and advected to north of the STF by the subtropical gyre in response to a change in surface westerly winds that occurred in the mid-1970s.

Memantine was effective for reducing fragmented sleep and improving BPSD, and was well tolerated.

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