Abrupt enhancement of convective activity over the subtropical western North Pacific around 20°N, 150°E is known as the convection jump (CJ) caused by the ocean–atmosphere coupling, which is one of the important factors inducing the end of the Baiu season in Japan. Using atmospheric reanalysis and observation data for 1974–2021, this diagnosis is made for the influences of Rossby wave propagation and breaking, high-potential vorticity (PV) intrusion, and cutoff lows over the western North Pacific on CJ occurrence.

Preceding CJ occurrence, southeastward Rossby-wave propagation is discernible along the upstream of the mid-Pacific trough in the upper troposphere, and its energy accumulates over the northeast of the CJ region. The subsequent wave breaking near the exit region of the Asian jet induces the southwestward intrusion of high-PV airmass toward the northeast of the CJ region, which is concurrent with the enhancement of convective activity. The high-PV intrusion may also be interpreted as westward-moving, upper-level cutoff lows migrating from the mid-Pacific trough. The diagnosis of Q-vector indicates that variations in the extratropical upper-tropospheric circulation induce dynamical ascent, contributing to the onset and maintenance of convective activity over the CJ region. Moreover, the PV budget analysis suggests that the persistent positive advection of PV at the edge of the high-PV intrusion nearly counterbalances the intense low-PV generation by diabatic heating associated with the CJ. These results indicate that the CJ is influenced by extratropical upper-tropospheric variations as well as the coupled atmosphere–ocean system in the subtropical western North Pacific.

A high-resolution sea surface temperature (SST) analysis called COBE-SST3 covers daily to centennial SST variations. The SSTs were constructed by performing analyses for low-frequency components, interannual variations, and daily changes with statistical methods using in-situ and satellite observations. The biases for each observation type were objectively estimated, and the result was a reconfirmation that the types are not properly categorized in the international database. By introducing a correction to the global mean nighttime marine air temperature observations which is used for the bias detection, moderate changes in global mean SSTs around World War II were obtained in COBE-SST3. SST and land surface air temperature (LSAT) fields were simultaneously analyzed on a monthly time scale for consistency between SST and LSAT. The LSAT observations acted as low-quality SST observations, and could produce SST variations to an eye-opening degree. This is the same as in the SST observations. The simultaneous analysis suggested that SST and LSAT observations were complementary and of satisfactory quality. Two types of daily SST analyses on a 0.25° grid were produced: one is a blend of multiple satellite and in-situ observations, and the other is a reconstruction with in-situ observations only. The two analyses were highly correlated with a counterpart provided by the National Oceanic and Atmospheric Administration of the USA. Uncertainties in low-frequency components, interannual variations, daily changes were separately estimated. These were used to construct daily perturbed SSTs, which are random, normally distributed, and spatiotemporally continuous.

Heavy wet snow accretion occurred along the coast of the Okhotsk Sea, collapsing a transmission tower near Monbetsu City and causing a power outage in the area, on December 22–23, 2022. This study investigated the meteorological conditions that caused heavy wet snow accretion in this area, with a particular focus on three factors responsible for wet snow accretion: strong winds, snowfall, and temperatures slightly above 0 °C. An analysis of the station observations from the Japan Meteorological Agency shows that this case occurred on the most favorable day for the wet snow accretion in Hokkaido since 1976. A duration of favorable temperatures for wet snow accretion for this case was longer than historical events by 30 %. A numerical simulation using the Weather Research and Forecasting model, with a horizontal resolution of 1.667 km, demonstrated that the formation of torrential wet snowfall and strong winds were associated with multiple extratropical cyclones. On the evening of December 22, a cyclone moving northward off the eastern coast of Japan, together with another stagnant cyclone located over the northern Japan Sea, formed a large cyclonic circulation. The cold conveyor belt, a cold airstream located poleward of the warm front, associated with the northward-moving cyclone, caused strong easterly winds along the coast of the Okhotsk Sea and carried a large amount of moisture there, reinforcing snowfall from stratiform clouds through depositional growth. A backward trajectory analysis showed that temperatures slightly above 0 °C were maintained through the balance between heating from the sea surface and cooling caused by snow melting. The norward-moving cyclone tracks resembled other historical events at Monbetsu, but the precipitation amounts were the largest in this event. These findings suggest that a combination of synoptic-scale circulations and cloud microphysics plays an essential role in the occurrence of heavy wet snow accretion.

Quantifying emissions from megacities is important for reduction of greenhouse gases. We used atmospheric carbon dioxide (CO₂) concentration data obtained at an altitude of around 250 m above the ground on TOKYO SKYTREE (TST; a 634-m-high freestanding broadcasting tower; 35.71°N, 139.81°E), which is located north of central Tokyo, Japan. To use the TST observations for estimating net CO₂ fluxes from Tokyo, a global, high-resolution simulation of atmospheric CO₂ transport with CO₂ flux data from a global inverse analysis was performed. In the simulation, atmospheric CO₂ variations were well reproduced at remote sites around Japan. The application of tagged tracers in the simulation revealed that variations of CO₂ concentrations at TST were largely driven by fluxes in the southwest region of Tokyo, including the western Tokyo Bay area where huge power plants are located. Then, we performed a regression analysis of modeled and observed Tokyo-originated CO₂ concentrations, both of which were derived from the simulated background concentrations, while changing the minimum wind speed used in the analysis. The removal of low wind speeds altered the slope of the regression line, and excluding wind speeds below 7 m s⁻¹ resulted in a stabilized slope of 0.93 ± 0.08. This stabilized regression indicated that the annual net CO₂ emission from Tokyo is 79.5 ± 6.6 Tg-C yr⁻¹. Our findings demonstrate that analysis using a global high-resolution model with tagged tracers has the potential to monitor emissions changes in a megacity.