Misclassification of convective precipitation pixels as stratiform precipitation over the Tibetan Plateau (TP) in summer by the precipitation type classification algorithm (CSF algorithm) of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) has been reported in several studies. To investigate the cause of this misclassification, we validated the CSF algorithm using Doppler radar observations of mesoscale wind divergence. The case studies revealed that the algorithm performs well for typical isolated deep convection, whereas embedded convection within stratiform precipitation was misclassified; the divergence profile clearly indicated convective characteristics, although the CSF algorithm classified it as stratiform. This provides the first evidence of misclassification of precipitation type over the TP in summer based on mesoscale wind divergence. We found that the misclassification is primarily caused by the thresholds of the Peakedness function in the H-method, and that reclassification aimed at enhancing the detection of embedded convection and weak convective precipitation led to a more reasonable convective precipitation fraction.

Understanding the characteristics of atmospheric gravity waves driving stratospheric circulation, which directly influence tropospheric weather, is of considerable importance. However, in-situ observation datasets in the middle and upper stratosphere remain limited. To investigate gravity wave activity in this part of the atmosphere, we conducted high-altitude radiosonde observations using large rubber balloons over Okinawa, Japan, in July 2024, obtaining wind velocity and temperature data. During the observation, a distinctive fluctuation was observed on July 25 as Typhoon Gaemi passed southwest of Okinawa. In this study, we investigate the characteristics of the observed fluctuation using hodograph and ray tracing analyses. The results suggest that the fluctuation was a gravity wave with a large vertical wavelength ~ 11 km, originating near the center of Typhoon Gaemi and propagating upward and east-northeast direction. Furthermore, the typhoon-induced gravity waves were modulated by the easterly mean wind field, suggesting that their vertical propagation characteristics differed between the eastern and western sectors of the typhoon.

Abstract Zonal asymmetry in the amplitude of the Quasi-Biennial Oscillation (QBO) is investigated using JRA-55 reanalysis data and in-situ IGRA radiosonde observations. In addition to the previously reported asymmetry near 10 hPa, significant longitudinal variation with the largest amplitudes over the western and central Pacific is found around 70 hPa. Unlike the dominant wavenumber-1 pattern near 10 hPa, the structure at 70 hPa exhibits more localized variations. Longitudinal differences in the QBO zonal wind at 70 hPa reach up to 30%, indicating that the descent of the QBO into the lower stratosphere and upper troposphere exhibits pronounced longitudinal variation. The asymmetry results were confirmed in five additional reanalysis datasets. Similar zonal variation of QBO amplitudes is also identified in radiosonde observations and in both CMIP6 and QBOi models that explicitly simulate the QBO. These results demonstrate that the longitudinal structure of the 70-hPa QBO amplitude is a robust feature across observations, reanalyses, and climate models.

Abstract Precipitation patterns in the northwestern Himalayas have shifted markedly over the past four decades. Using MERRA-2/GEOS reanalysis data (1983–2022) coupled with non-parametric trend analysis, Sen’s slope estimates, and Intensity–Duration–Frequency (IDF) modeling, we document a significant increase in annual and monsoonal rainfall across southern and mid-altitude belts, alongside persistently low but increasingly variable precipitation in high-altitude cold deserts such as Ladakh. The Seasonality Index (0.46–1.26) indicates growing temporal clustering of rainfall, heightening flood and drought exposure. IDF-curves reveal the most severe short-duration extremes in orographically enhanced monsoon catchments, highlighting heightened flash-flood risk, while arid zones face sporadic but impactful extremes. Although reanalysis products can underestimate localized extremes in steep terrain, especially cloudburst-like events, the four-decade consistency of MERRA-2 provides robust regional-scale diagnostics of changing rainfall variability. These findings support region-specific adaptation strategies, including resilient infrastructure design and early-warning systems, for these ecologically sensitive mountain landscapes.

Super-resolution (SR) in deep learning is a technique to generate high-resolution (HR) outputs from low-resolution (LR) inputs. Recently, combining SR with data assimilation (DA) has been proposed, leading to the development of super-resolution data assimilation (SRDA). The SRDA method simultaneously performs SR and DA by inputting LR simulation results and observations into a neural network. This study develops a four-dimensional SRDA (4D-SRDA) model to predict temporal evolutions of three-dimensional quasi-geostrophic flows in a baroclinic jet system. To evaluate the performance of 4D-SRDA, we compare it with a Local Ensemble Transform Kalman Filter (LETKF), which uses an HR model. 4D-SRDA successfully reproduces both small- and large-scale structures of potential vorticity, visually similar to those produced by the LETKF. We compare grid-wise and pattern-similarity errors to quantify the accuracy of the analysis and forecast states. Despite using an LR fluid model, 4D-SRDA achieves accuracy comparable to that of the LETKF. Comparing the computational time required for prediction reveals that 4D-SRDA is substantially more efficient than the LETKF. These results suggest that 4D-SRDA is a promising approach for predicting HR atmospheric flows.

Tropical cyclones (TCs) often cause torrential rainfall and cause severe disasters. To assess the possible worst heavy rainfall events in mid-latitude regions under warming climates, the top 10 heavy rainfall events over Hokkaido, Japan, were selected from around 100 TC cases in large-ensemble climate change simulations of both historical and 4-K warming climates. The results of dynamical downscaling experiments using a 2-km-mesh regional model show a 42% increase in mean accumulated rainfall over Hokkaido during the warming-climate events, compared to that during the historical-climate events. Increases in rainfall preceding TC passage were particularly high. Two types of the worst heavy rainfall events are proposed: top 10 events with high amounts of rainfall preceding the TC passage (Preced10) and those with high amounts of rainfall occurring during the storm passage (TY10). Under a warming climate, Preced10 caused significantly higher amounts of rainfall than TY10. Moreover, Preced10 brought rainfall throughout Hokkaido, whereas rainfall during TY10 was concentrated on the eastern side of Hokkaido. A combination of higher amounts of water vapor, higher temperatures, and slower TC movement under a warming climate produced the worst unprecedented heavy rain events due to long-term rainfall preceding TC passage.

Typhoons AMPIL and SHANSHAN (2024) slowed down as they approached and moved parallel to the Kuroshio Current. Both typhoons reached peak intensity at relatively high latitudes while they were moving northward. Various atmospheric and oceanic datasets were used to investigate atmospheric and oceanic thermodynamic similarities and differences between AMPIL and SHANSHAN. In addition, numerical simulations and sensitivity experiments for high sea surface temperature (SST) in the Kuroshio Current region were performed with a nonhydrostatic atmosphere model and an atmosphere-wave-ocean coupled model to understand related intensification mechanism. The 26°C isotherm was relatively deep and the upper-ocean heat content was relatively high where AMPIL and SHANSHAN intensified. Despite the different atmospheric environments, such as the vertical wind shear and the relative humidity at the 600-hPa altitude, AMPIL and SHANSHAN were able to develop and maintain the maximum intensity at relatively high latitudes during when the TCs moved slowly near the Kuroshio Current region. The results of the sensitivity experiments suggest that high SSTs in the Kuroshio Current region possibly contribute to the development and maintenance of the maximum intensity of AMPIL and SHANSHAN through high latent heat fluxes outside the radius of maximum wind speed and the inner-core axisymmetrization.

This study investigates the statistical characteristics of Baiu frontal depressions (BFDs), which occasionally accompany heavy rainfall in Japan. Using a high resolution (5 km) regional reanalysis dataset in June and July from 1991 to 2020, we objectively detected about 7000 BFDs (more than 1,000 distinct events) by combining methods to identify isolated depressions and the Baiu front. Our analysis shows that BFDs occur widely around Japan, particularly in western areas, and BFDs with smaller radii are more prone to intense precipitation. Although smaller BFDs are more common in the western areas, both small and large BFDs also occur in the eastern areas. Composite analyses indicate that small BFDs exhibit heavy rainfall near their centers and have an upright or slightly eastward tilted vertical structure, suggesting the essential role of diabatic heating. In contrast, BFDs with larger radii exhibit maximum precipitation east of their centers and have a westward tilted structure, suggesting a greater contribution from baroclinic processes.

This study investigates the influence of aerosol optical depth (AOD) on warm cloud microphysics in three distinct regions: East Asia (EA), the Equatorial Atlantic Ocean (EqAO), and Peru (PR), using Cloud Frequency by Optical Depth Diagram (CFODD) analysis. Satellite data from Aqua/MODIS and CloudSat/CPR during the period 2006-2014 were utilized to compare cloud properties under low and high AOD conditions. In EA, high AOD levels are associated with enhanced radar reflectivity at smaller cloud droplet radius (CDR), particularly within the 12-15 μm range. This indicates an increased droplet numbers and greater reflectivity variability within the same CDR interval. The observed enhancement in radar reflectivity at the cloud base under high AOD suggests an intensified collision-coalescence processes, consistent with the Anti-Twomey effect. A similar, though weaker, pattern is observed over the EqAO, indicating a reduced aerosol impact. In contrast, the PR region, exhibits minimal AOD variability, leading to limited aerosol effect and relatively stable cloud structures. These regional differences highlight the importance of considering both Twomey and Anti-Twomey effects to improve the representation of aerosol–cloud interactions (ACI) representation in climate models.