This study investigates the dependency of the charge structure in a summer convective cloud on the horizontal resolution of a bulk lightning model coupled with a meteorological model. For simulations involving a bulk lightning model with fine grid resolution, a multigrid solver is applied to the model, and the simulation results show that the charge separation numerically converges when the resolution reaches 200 m. The reason for this convergence is that with finer resolution, the strong vertical updraft actively transports liquid water and water vapor to higher altitudes, generating an environment conducive to riming, with sufficient supercooled water, transported by vertical updraft and produced from water vapor by condensation, present at altitudes of 9-11 km. Consequently, with higher resolution, the graupel mixing ratio increases at these altitudes, and this graupel formation leads to increased charge separation, which results in a higher lightning frequency. These results suggest that simulations with a resolution of 200 m or finer are necessary to simulate the lightning frequency accurately in numerical models coupled with a bulk lightning model.

Extreme and intense atmospheric phenomena occur in complex urban areas, but stationary ground-based meteorological observations cannot capture the detailed meteorological conditions across urban blocks. Vehicle-based mobile observation provides a method to collect high spatiotemporal data in cities. We developed a small IoT observation system to mount vehicles easily and measure air temperature, humidity, pressure, wind speed and direction, together with local time and location. To evaluate this system, we conducted a case study of mobile observation in Tokyo almost daily for one and a half months. Mobile observation data had occasional missing and erroneous, so data extraction and processing were applied based on weather conditions and vehicle's speed. Using the quality-controlled data, we confirmed that given the mobile observation was within 2 km of the fixed-point observation, air temperature and humidity from mobile observation was highly correlated with reliable fixed-point observation (RMSD < 1°C and < 0.34 g/kg). Thus, the mobile observation system potentially provides those datasets comparable to conventional ground meteorological datasets. The spatial distributions of air temperature and humidity exhibited distinctive changes between urban blocks, influenced by land use and urban characteristics. This system enables long-term, extensive vehicle-based observations and aids in detecting extreme atmospheric phenomena in urban areas.

 Tropical cyclones (TCs) contribute to hydroclimates. The relationship between TC-related rainfall and TC activity was investigated using a high-resolution global atmospheric model. To separate the influences of the interannual variability of sea surface temperature (SST), a 64-member ensemble simulation was conducted for 11 TC seasons. TC direct rainfall (TCDR) and indirect rainfall (TCIR), within and away from the 500-kilometer distance from the TC center, were separately examined.

 The results show that TCDR was strongly correlated with TC activity, while TCIR was moderately correlated with TC activity. When TCs were more active, TCDR increased by more than twice in the southwestern region of Japan, and TCIR increased by up to 20% in the western part of Japan and the Pacific coastline of eastern Japan.

 A simple regression analysis showed that the relationship between seasonal TC activity and TC-related rainfall was independent of the interannual variability of the SST for TCDR but dependent on TCIR in the analysis area. The independent relationship between TC activity and TCDR likely becomes a useful metric for intermodel comparison and evaluation of the impact of global warming.

Atmospheric hydrogen peroxide (H₂O₂) was intensively measured in the Tokyo metropolitan area (Kazo City, Saitama Prefecture and Shinjuku-ku, Tokyo), Japan in the summer of 2022 and 2023. In particular, the temperatures in the summer of 2023 were very high. H₂O₂ and ozone (O₃) concentrations were generally higher in Kazo City than in Shinjuku-ku, and the concentrations were particularly higher during the period of typical summer atmospheric pressure pattern when Photochemical Oxidant Warning was issued in Saitama Prefecture. Sufficiently high concentrations of H₂O₂ exceeding 3-4 ppb (30-minute values) were occasionally measured, which have hardly been seen in Toyama Prefecture, where the air environment is relatively clean in Japan. The oxidation capacity of SO₂ seems to be high in summer in the Tokyo metropolitan area. In Kazo City, H₂O₂ was highly positively correlated with O₃. When the atmospheric pressure pattern was typical for summer, both O₃ and H₂O₂ reached their maximums at around 15 JST in Kazo City; however, in Shinjuku-ku, the peak time of O₃ was in the early afternoon (around 13 JST), while the highest concentration of H₂O₂ was seen at around 15 JST when NO_X became significantly low.

Substantial progress has been made in understanding the role of snow cover (SC) within the climate system. Previous studies have focused predominantly on average SC conditions across specific months or seasons. However, the atmospheric impacts of occasional SC, which last only a few days, have been largely overlooked. Here, we demonstrate that the sudden appearance of occasional SC in East Asia, despite its short duration, induces an immediate local cooling effect on the atmosphere, extending from the near surface to the lower troposphere. This cooling effect is driven by diabatic heating caused by the snow albedo effect. Numerical experiments indicate that 24% of the maximum intensity of extreme temperature drops associated with SC events is driven by SC amplification. Furthermore, in the absence of this feedback, the extremity of these temperature drops can be mitigated. This study underscores the critical role of occasional SC in shaping cold extremes and aims to highlight the need for greater attention to occasional SC phenomena in atmospheric research.

In July 2023, persistent rainfall associated with the Baiu front caused record-breaking rainfall and flooding on the Sea of Japan side of the Tohoku region, where heavy Baiu rainfall is usually less common. Using a risk-based event attribution approach with a 100-member climate simulation at 5-km grid spacing, our analysis revealed that anthropogenic global warming substantially increased the likelihood of such an extreme rainfall event under the July 2023 conditions. At the Akita weather station, the probability of a 72-h rainfall event similar to that observed in 2023 increased from approximately 0.4% in a non-warming climate to 7.2% in the historical climate. This indicates that anthropogenic warming increased the probability of a 2023-like extreme rainfall event by approximately 18 times. As observed, the ensemble experiment showed that westward extension of the western Pacific subtropical high facilitated moisture inflow toward the Sea of Japan side of the Tohoku region, and that this extension was forced primarily by the global sea surface temperature pattern. Under this synoptic condition, increase in lower-atmosphere equivalent potential temperature driven by global warming enhanced the latent instability, contributing to the persistent heavy rainfall similar to that observed during the 2023 event.

Numerical simulations were conducted to examine the influence of unusually high sea surface temperatures (SSTs) in the southern part of the Sea of Japan (SOJ) on heavy rainfall that occurred in Noto, Japan, on 21 September 2024. During this period, SSTs in the southern SOJ were significantly higher as compared to climatological normals. In a simulation in which local SSTs west of the Noto Peninsula were substituted with the climatological normals from 1991 to 2020, the maximum and area-averaged values of the 48-hour accumulated precipitation were reduced by approximately 28% and 14%, respectively, as compared with the control simulation. Backward trajectory analyses showed that boundary-layer air parcels entering the heavy rainfall region were enriched with substantial water vapor from the warm sea west of the Noto Peninsula. In addition, these parcels reached the heavy rainfall region without losing heat to the warm sea. These features indicate that the sensible and latent heat fluxes from the warm sea not only increase the water vapor content but also enhance low-level convective instability, leading to a significant increase in precipitation.

This study proposes introducing convex optimization to find initial perturbations of atmospheric states to realize specified changes in subsequent weather. In the proposed method, we formulate and solve an inverse problem to find effective perturbations to atmospheric variables so that controlled variables satisfy specified changes at a specified time. The proposed method first constructs a sensitivity matrix of controlled variables, such as accumulated precipitation, to the initial atmospheric variables, such as temperature and humidity, through sensitivity analysis using a numerical weather prediction (NWP) model. Then a convex optimization problem is formulated to achieve various control specifications involving not only quadratic functions but also absolute values and maximum values of the controlled variables and initial atmospheric variables in the cost function and constraints. The proposed method was validated through a benchmark warm bubble experiment using the NWP model. The experiments showed that the identified perturbations successfully realized specified spatial distributions of accumulated precipitation.