Scientific Online Letters on the Atmosphere (SOLA) is a fully Open Access journal under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License, and aims to make a first decision within one month and a decision upon resubmission within a further month. A rapid review cycle is the first priority of SOLA.
Last year, we published 45 papers. Although the coronavirus disease 2019 (COVID-19) pandemic is still an on-going issue, we are pleased to have a large number of submissions and to publish excellent research outcomes through rapid review cycles. We presented the SOLA Award in 2021 to the paper by Drs. Koichi Shiraishi and Takashi Shibata, entitled “Seasonal variation in high arctic stratospheric aerosols observed by lidar at Ny Ålesund, Svalbard between March 2014 and February 2018” (Shiraishi and Shibata 2021).
From this year, we have started the SOLA's printing style from a double column to a single column format. We hope that a single-column format will be useful to read a paper with various media.
We have been making continuous efforts to organize special editions coordinated jointly with Journal of the Meteorological Society of Japan. We are currently welcoming submissions to the Special Edition on the Frontier of Atmospheric Science with High Performance Computing.
We hope that SOLA is one of your preferred platforms where you can disseminate your research achievements. SOLA welcomes submission from the international community in meteorology, atmospheric sciences, and the related fields.

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The Editorial Committee of Scientific Online Letters on the Atmosphere (SOLA) presents the SOLA Award to one or two outstanding papers published each year. We are pleased to announce that the SOLA Award in 2022 will be given to the paper by Dr. Yasumitsu Maejima et al., entitled “Observing system simulation experiments of a rich phased array weather radar network covering Kyushu for the July 2020 heavy rainfall event” (Maejima et al. 2022), and to the paper by Dr. Tomoe Nasuno et al., entitled “Impacts of midlatitude western North Pacific sea surface temperature anomaly on the subseasonal to seasonal tropical cyclone activity: Case study of the 2018 boreal summer” (Nasuno et al. 2022).

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 This study shows a possible mechanism of abnormal extension of North Pacific subtropical high (NPSH) toward western and eastern Japan observed in late June 2022, when Japan experienced an unprecedented heat wave lasting more than a week. During the period, an upper-tropospheric anticyclonic circulation anomaly amplifies to the east of northern Japan associated with the Silk-Road pattern.

 A diagnosis using quasi-geostrophic potential vorticity (QGPV) inversion shows that the lower-level anticyclonic circulation anomalies induced by the upper-level anticyclone are the primary factor in the generation of lower-level negative QGPV anomalies from mainland Japan to its south associated with the anomalous extension of the NPSH. The induced circulation causes the lower-level negative QGPV anomalies by upgradient horizontal advection of the climatological QGPV, which has a strong gradient from mainland Japan to its south associated with the Baiu frontal zone. The proposed mechanism well explains a peculiar vertical structure of the observed anticyclone near Japan.

 A sensitivity diagnosis considering the sub-seasonal variation of the climatological lower-tropospheric QGPV distribution during summer indicates that the proposed NPSH extension mechanism toward Japan becomes most efficient from late June to early July, when the Baiu frontal zone is most enhanced near Japan.

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The surface temperature was projected to increase from 4 to 5°C in most regions around Japan in winter at the end of the 21st century, according to the Non-Hydrostatic Regional Climate Model (NHRCM) under the Representative Concentration Pathway 8.5 scenario. The melting of sea ice in the Sea of Okhotsk significantly affected the temperature around Hokkaido Prefecture, raising it by more than 8°C in some places. The temperature also rose by more than 8°C in some areas in Honshu where the atmosphere was not susceptible to sea ice. The reduction in snow-covered areas due to global warming raised the temperature further and induced changes in local wind, such as airflows over mountains and wind blowing from the sea. These changes raised the seasonal average temperature and caused the temperature to rise by over 8°C. The dynamical downscaling method played a significant role in projecting such small-scale features in the future climate.

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From the end of 2019 to the beginning of 2020, Australian bushfires caused by high temperatures and drought significantly impacted the local and global atmosphere. This work uses the global atmospheric chemistry transport model and observations to assess the enormous impact of bushfire emissions on PM_2.5 in Australia. During December 2019, the significant increase in biomass-burning emissions led to increases in PM_2.5 observations in megacities such as Canberra, Sydney, Newcastle, Brisbane and Melbourne by 845%, 322%, 171%, 141% and 58%, respectively. Numerical simulations reveal that bushfires increased PM_2.5 in Australia and in the Southern Hemisphere by 49% and 13%, respectively. Although the aerosols produced by bushfires could not cross the equator at ground level and affect the air quality in the Northern Hemisphere, they were transported to South Asian countries such as Malaysia and India, as well as Papua New Guinea and New Zealand. In addition, they were also injected upward into the stratosphere (approximately 15 km height). Aerosols injected into the stratosphere could be transported to Antarctica and South America, thus completing global transport.

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Forecasts of discrete events, such as precipitation, dust storms, and typhoons, can be deterministic, categorical, or probabilistic. Ensemble-based probabilistic predictions generate more consistent forecasts than individual deterministic models. We introduce and evaluate the Ensemble Prediction System of Asian Dust Aerosol Model 3, which generates probability forecasts of Asian dust. Probability forecasts were produced for 300 μgm⁻³ PM₁₀ mass concentrations, according to the air-quality standards of the Ministry of Environment of South Korea and Korea Meteorological Administration. Crisis-level information was produced to categorize the dust risk level for Asia, using a risk matrix. The model's performance was evaluated using a 2 × 2 contingency table, the Brier skill score, and a reliability diagram. For skill score evaluation via the contingency table, the average hit rate and threat score were 0.46 and 0.34 for the best three sites, Jurihe, Erenhot, and Wulatezhongqi. The Brier skill score was positive for approximately 60% of stations, with the highest (0.410) and lowest (−2.038) values in Erenhot and Yanan, respectively. The reliability diagram revealed overestimated Asian dust frequencies for all stations. Although the stations were located within the same regions, their skill scores differed. Regional characteristics of skill scores should be further investigated in the future.

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Due to less tropical cyclone (TC) occurrences, the climatology of the quiescent TC season (i.e., March-April-May, MAM) in the western North Pacific (WNP) is less understood when compared to the more active season (i.e., June-November). Here we show observational evidence of significantly decreasing TC quiescence during MAM that can be attributed to more Central Pacific El Niño events from 2002 to 2022. A Central Pacific El Niño is related to an asymmetric sea surface temperature (SST) pattern where warm (cool) SST anomalies are concentrated in the central (western) Pacific, which consequently contributes to the overall decrease in TC quiescence in MAM. Such anomalous SST pattern prompts the western North Pacific Subtropical High to expand westward, creating a conducive large-scale environment for TC development and allowing TCs to move closer to the landmass, which ultimately leads to an increasing cost of TC-associated damages during the quiescent season. Our study provides new insights into the decreasing TC quiescence and TC climatology in the WNP during MAM, which is ultimately expected to contribute to disaster risk reduction in the region.

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On 18-20 July 2021, Henan Province in China experienced a historically rare extreme precipitation event, termed as the “21.7” event. Its synoptic environment was characterized by a large amount of moisture supply by binary typhoons located over the ocean and a potential vorticity intrusion in the upper level. The present study examines the importance of the latter by conducting WRF model experiments. A qualitatively similar rainfall amount to observation is obtained when the zonal wavenumber 7 and larger is kept above 300 hPa in the initial and lateral boundary conditions. When only the large-scale disturbances with wavenumbers 2-4 are kept, the precipitation is greatly reduced. This result indicates that the upper-level synoptic-scale disturbance, which leads to the development of potential vorticity anomaly and its downward intrusion, has likely played a critical role in the development of this event along with a large amount of moisture transport in the low level.

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This study investigated biases of diffuse radiation in a look-up table approach, which pre-computed the sequential ray tracing to avoid heavy computation in full three-dimensional radiative transfer calculation. We introduced corrections that enhanced directionality of radiative propagation in the solar angle and horizontal direction. By comparing irradiance calculations with and without the corrections for cloudy field in an idealized atmospheric simulation, it was found that the corrections helped mitigate vertically localized false signals by diffuse irradiance. The results suggested that the two types of directionalities are important to accurately represent the three-dimensional transfer of diffuse radiation in an inhomogeneous atmosphere.

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The use of massive sailing ships has been proposed as a means of acquiring renewable energy. It has also been proposed that such ships can be used to reduce the intensity of tropical cyclones (TCs). Here we propose a basis for evaluating the dynamical impacts of numerous sailing ships on the atmosphere. The key parameter is the total sail area per unit horizontal area (referred to as β), which is proportional to the number of ships in the region of interest. From β, the enhancement in the effective surface drag can be evaluated. The maximum potential intensity theory for TCs predicts that, under ideal environmental conditions, the steady-state TC intensity decreases inversely to the drag enhancement if the ship-induced change in the effective enthalpy transfer is much weaker. For example, if β is 0.04%, the potential intensity in terms of squared maximum wind can be decreased by around 10%. The effect of the directional drag from the use of aerodynamic lift in sail operations is also formulated, and its impact on TCs is evaluated by using a slab boundary-layer approximation. Sails' effects on air-sea interaction are briefly discussed, and further studies needed are envisioned.

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This paper shows the CFODD of the regional dependence of cloud growth processes in low-level clouds obtained by the combined use of the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite and the Cloud Profiling Radar (CPR) on the CloudSat satellite. This enabled the evaluation of the cloud growth process based on the cloud optical thickness (τ) and the effective radius of cloud particle (R_e), similar to previous studies that performed statical analysis on low-level clouds over the globe. Our targets were regions in East Asian, Californian, and Peruvian. In all analysis areas, our results showed that the internal structure of clouds changed as R_e increased, indicating cloud growth. In the East Asian region, the maximum τ remained relatively constant even when cloud droplet size grew. In contrast, in the regions of Californian and Peruvian, the maximum τ increased with R_e during the condensation growth process and then decreased as drizzle particles transformed into rain. It was also found that R_e was smaller in the East Asian region unlike in Californian and Peruvian. This indicates that there are more aerosols in the East Asian region, which is consistent with its geographical characteristics.

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Ground-based radar observations of the concentric eyewalls (CEs) of supertyphoon Hinnamnor (2022) showed that CEs evolved as follows: (Stage 0) development of a distinct stationary band complex (SBC) downshear in moderate south-southeastward vertical wind shear (VWS), (Stage 1) maturity of the secondary eyewall (SE), (Stage 2) contraction of the SE, and (Stage 3) decay of the CE structures. From Stage 0 to Stage 1, the SBCs transitioned into an axisymmetric SE, and moats appeared a few hours after SE formation. Outer rainbands formed successively in the down-to-left shear quadrants and developed wide stratiform regions with a vast anvil cloud extending outward as they moved upshear. When the anvil cloud covered the right-shear quadrants, the stratiform regions started contracting. Evolutions of the doppler velocity fields were detected under the anvil and stratiform regions of each rainband. An intense convection developed at the inner edge of the contracting SE as regions with relatively high doppler-velocity merged. When the core region was surrounded by multiple well-developed rainbands, the inner eyewall weakened rapidly. The radar observations revealed the importance of moderate-to-weak VWS and development of a SE as a rainband complex during evolution of CEs.

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Large-scale trends related to the precipitation in central Japan were investigated in the Coupled Model Intercomparison Project 5 dataset. In the Representative Concentration Pathways 4.5 projections, surface temperature over central Japan increases by 1 to 4 K during the 21st century in most models. Focusing on the trend of surface-air temperature and precipitation in central Japan, these models were categorized into two groups: The precipitation significantly increases in 11 models (group A). On the other hand, the trends of precipitation are small in the remaining 20 models (group B). Analyses of high-frequency components based on daily data revealed that the difference in the precipitation prediction is associated with that in the storm activity around Japan. Relatively enhanced meridional surface-air temperature gradient in the subpolar region may contribute to reinforced storm activity. On the other hand, the zonal surface pressure gradient associated with the Siberian high and the Aleutian low is not strengthened in group A. The climatological wintertime monsoon does not appear to contribute to the difference of precipitation trend in central Japan between the two groups. Moreover, the influence of any other planetary-scale variations is not implied.

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An intensive balloon-borne observation was performed at Syowa Station in the Antarctic (69.0°S, 39.6°E) in July 2016 using Cryogenic Frostpoint Hygrometers (CFH) and Electrochemical Concentration Cell (ECC) ozonesondes. High water vapor concentration was observed in the upper troposphere in two out of five observations. Trajectory analysis and atmospheric reanalysis data showed that moist air was transported into the upper troposphere due to the upwelling in front of a trough. While only isentropic transport was dominant in one case, both the isentropic transport and diabatic heating contributed to the upward transport in the other case. In another case where the air parcels came over the Antarctic continent, the water vapor concentration in the upper troposphere was lower than in the other cases. These results suggest that transport of air parcels with different origins by synoptic-scale disturbances controls water vapor concentration in the Antarctic upper troposphere.

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Simulations of future climate indicate that the Mediterranean countries will see increasing temperatures, and decreasing precipitation. In Türkiye, which has a semi-arid and dry sub-humid climate, the coupled effect of warming and drought is expected to lead to a general increase in aridity. We applied indices derived from satellite data to provide continuous monitoring for drought hazards and evaluated recent trends in aridification and drought. Annual averaged temperatures showed a statistically significant rise, although annual rainfall showed no nationwide trend despite strong fluctuations over Türkiye. Significant increasing (decreasing) trends of vegetation (aridification) could be found in the northern, western, and southern regions, despite the rising temperatures and fluctuations in rainfall. One cause of these trends is presumed to be an increase in the nation's proportion of forest, orchard trees, and irrigated farmland. Although decreasing trend of aridification over Türkiye, drought has recurred throughout the 22-year study period in the central and eastern regions. These areas in which the annual averaged satellite-based aridity index exceeds a threshold value correspond closely to regions vulnerable to drought. Satellite-based indices may show particular promise for the major agricultural or pasture areas in central and eastern Türkiye, which are at heightened risk of future drought.

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Dynamical downscaling simulations of MIROC6 (the sixth version of Model for Interdisciplinary Research on Climate) data using the Weather Research and Forecasting (WRF) model were performed to investigate future changes in the Japan Sea polar airmass convergence zones (JPCZs) related to heavy snowfall events in the Sea of Japan–side region of central and northern Japan. WRF dynamical downscaling simulations showed a northward shift of JPCZs and the associated changes in precipitation distribution. Rainfall increased significantly over the central part of the Sea of Japan and in the Tohoku region. On the other hand, snowfall decreased significantly over the entire Sea of Japan. However, there was a significant increase in snowfall in the inland mountainous areas of the Tohoku region. Jet streaks shift northward in the future climate, which was confirmed in the MIROC6 data. Reflecting such future environments, WRF dynamical downscaling simulations showed that a mesoscale cyclonic circulation anomaly passing over Hokkaido from the Sea of Japan, which is not resolved by MIROC6, contributes to the northward shift of JPCZs and the associated changes in rainfall and snowfall.

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In the western North Pacific, as a tropical cyclone (TC) translates northward and approaches the midlatitude jet region, a front is often observed to the northeast of the TC, especially in fall. Theoretically, a front accompanies positive vorticity in the lower troposphere because convergence of cross-frontal circulation generates positive vorticity. Horizontal winds accompanied by positive vorticity along a front can impact the TC track. This study estimates the influence of frontal positive potential vorticity (PV) on the TC track using reanalysis data for a case of TC Chan-hom (2020). Horizontal winds due to frontal PV (FPV) are calculated using PV inversion. The FPV produces west-southwesterlies around the TC center just after the FPV formation. Thereafter, it mainly produces northwesterlies. Steering flow due to the FPV displaces Chan-hom 50 km east-southeastward for 72 h.

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This paper presents experimental observations to improve typhoon prediction accuracy and to understand interactions between atmosphere and ocean directly under typhoons. Two unmanned surface vehicles (Wave Gliders (WGs)) equipped with interchangeable sensors were sailed toward the path of an approaching Category 5 typhoon (Hinnamnor), which began on 29 August 2022 and subsided on 6 September, reaching a minimum pressure of 920 hPa and a maximum wind speed of 55 m/s (105 knots). Sensors on WGs measured atmospheric pressure, wind speed, atmospheric and seawater temperature, wave height, currents, salinity, and chlorophyll-a concentrations in different parts of the typhoon. These observations made it possible to clarify changes in various phenomena as the typhoon approached and to compare differences in storm characteristics measured by the two WGs. Sea surface pressure in the core of a typhoon is useful as an initial predictor of its intensity. Data assimilation into numerical models and other observations are expected to improve prediction accuracy of typhoon phenomena. Furthermore, simultaneous observations of atmosphere and ocean will also be useful for modeling interactions.

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This study investigated the internal precipitation and kinematic structure of the South Pacific convergence zone (SPCZ) observed by the Doppler radar aboard the research vessel Mirai, which passed through the western tropical portion of the SPCZ on 17-21 December 2016. Convective precipitation developed in association with the low-level convergence induced by the monsoon and the upper-level divergence associated with extratropical Rossby wave breaking. Mesoscale convective systems (MCSs) developed from either intersecting (northeast–southwest/northwest–southeast) or zonally oriented convective bands. For the MCS developing from the former mode, the zonal and meridional divergence fields made comparable contributions to convective development. For the MCS developing from the latter mode, the divergence field induced by the meridional wind had the largest contribution to producing convection. The MCS with stronger convective updrafts and higher echo tops and coverage occurred in the region where more intense convergence was observed near the surface. The results of this study highlight the dependence of organizational modes of SPCZ convection on the coupling of the tropical low-level and extratropical upper-level forcings, as well as on the zonal and meridional forcing structures.

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The Noah multi-parameterization (Noah-MP) scheme is one of several land surface schemes implemented in the Weather Research and Forecasting (WRF) model. Our simulations by the WRF model with the Noah-MP scheme show that surface air temperatures in the morning and evening tend to be higher and lower, respectively, than observed, and that the temperatures at an urban station with snow cover increase little from 0°C even in the daytime. The former depends on surface energy balance in the skin layer and the latter results from snow cover assumed to be uniform over a grid cell. These weaknesses are improved by considering the partial transmission of the solar radiation through the skin layer to the soil layer, the heat capacity of the vegetation canopy, and a mixture of soil layers with and without snow cover. The present scheme will contribute to an improvement of the Noah-MP scheme.

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To investigate the effects of global warming on Typhoon Jebi (2018), we performed high-resolution pseudo-global 2-K and 4-K warming simulations with initial time ensembles using a regional atmospheric model. The pseudo-global warming experiments demonstrated the further facilitation of Jebi's development with a higher rise in the temperature. The intensity over the ocean to the south of Japan increased by 8% (20%) in the climate warmed 2-K (4-K) to the current climate. Typhoon Jebi, in the 4-K warming simulations, maintained a robust inner-core characterized by a compact and deep eyewall and well-developed primary and secondary circulations even immediately before landfall, in contrast to the result in the 2-K warming simulations. The sustained robust axisymmetric structure immediately before landfall in the 4-K warming runs was strongly associated with the enhanced ocean warming around Japan, notable moistening of the lower-to-middle troposphere in the vicinity of Typhoon Jebi, and a significant decrease in vertical wind shear under the extremely warmed future climate. The nonlinear responses of Typhoon Jebi to the tropospheric temperature rise are attributable to the drastic changes in the midlatitude's thermodynamic and dynamic environments under climate changes resulting from 2-K to 4-K global warming.

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We investigated the microphysical mechanisms for the enhancement of rainfall in a precipitating system that spawned heavy rainfall over the central part of the Kanto Plain in eastern Japan on 12 July 2022. Optical disdrometer observations confirmed the existence of an equilibrium state in the raindrop size distribution, especially when the precipitation intensity was high (e.g., 20 mm hr⁻¹). As the raindrop size distribution approached equilibrium, raindrop sizes centered around 1.5 mm were observed initially, and then the number concentration of smaller and larger size raindrops increased simultaneously. The raindrop size distribution was closely related to the vertical profile of the parameters of raindrop size distribution that were estimated from polarimetric radar observations. These results suggest that the formation of equilibrium raindrop size distributions is important to produce substantial rainfall in the midlatitude as well as in the tropics.

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Satellite observations are expected to play an important role in studying carbon fluxes. However, it is necessary to properly remove spatiotemporal bias from these observations. In this study, we estimated the spatiotemporal bias in satellite XCO₂ data by making an inversion of in-situ observations. Compared to the GOSAT XCO₂ (NIES Ver. 2.97-8) concentrations derived from this analysis, the global average difference is −1.26 ppm, with a difference of −0.76 ppm over the land and −1.54 ppm over the ocean. We then developed a method to correct the bias between the satellite XCO₂ and the in-situ inversed XCO₂ data. Using this bias correction method, we performed an inverse analysis using in-situ and satellite observations and found that the error relative to the independent observations decreased mainly in the middle and upper troposphere compared to the in-situ inversion. Compared to previous studies, the introduction of satellite observations also suppressed large variations in the regional CO₂ flux, except in regions with few observations. After correction using the proposed method, the estimated CO₂ flux can be used to provide improved estimates of regional CO₂ fluxes; however, the results also show a need for increasing the CO₂ observation sites and improving the analysis system.

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In this study, synthetic inflow turbulence generation methods developed in computational fluid dynamics (CFD) and meteorological fields were applied to thermally driven convective boundary layer (CBL) simulations. Methods developed in the CFD field include the Reynolds stress Cholesky decomposition and digital filter-based method (DF method), and the cell perturbation method (CPM) is a method developed in the meteorological field. Intercomparison results show that both methods can reproduce turbulence in thermally driven CBLs when a proper driver region is ensured. The turbulence reproduced using the DF method in a thermally driven CBL has a shorter driver region than that reproduced using CPM. However, CPM can be applied to a simulation without limiting the inflow boundary, although it requires a longer driver region than the DF method. Therefore, it was confirmed that both methods have unique merits that can be useful for downscaling from meteorological mesoscale models to microscale large-eddy simulation models.

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Column-averaged dry air mole fractions of carbon dioxide and methane (XCO₂ and XCH₄) retrieved from SWIR (Short-Wavelength InfraRed) observations by GOSAT (Greenhouse Gases Observing SATellite) since 2009 and its successor GOSAT-2 since 2019 are available from NIES (National Institute for Environmental Studies) as SWIR L2 (Level 2) products. This paper shows the current status of the data quality of NIES SWIR L2 products and inter-satellite comparison results. Comparisons of XCO₂ and XCH₄ obtained from each satellite with ground-based observations from the TCCON (Total Carbon Column Observing Network) reveal that the averaged single measurement precision are less than 1.9 ppm and 10 ppb, respectively, and the site-to-site biases are less than 0.9 ppm and 5 ppb, respectively. The standard deviations of the inter-satellite differences for XCO₂ and XCH₄ are 2.18 ppm and 12.1 ppb, respectively, on an individual-data basis and 1.77 ppm and 11.7 ppb, respectively, on a monthly-regional-mean basis. While further improvements in the retrieval algorithm and bias-correction method are needed, GOSAT and GOSAT-2 retrievals are generally in good agreement.

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 The particle filter attracts interest from the data assimilation research community since it does not assume a Gaussian prior error distribution. Several local particle filters (LPFs) have been proposed to avoid weight collapse due to assimilation of observations in high dimensional systems. This study focuses on an LPF that uses the ensemble transform matrix as used in the local ensemble transform Kalman filter. Resampling of the transform-matrix-based LPF has been employed using Optimal Transport (OT) that minimizes analysis increments of particles. However, computations of OT increase by order of square, which limits its application for large-ensemble LPF problems.

 This study proposes using the fast Sinkhorn algorithm, an approximated solver of the OT method, for the resampling of LPFs. A series of perfect model experiments with a 40-variable toy model show that the Sinkhorn algorithm produces accurate analyses equivalent to that obtained with the OT method. In addition, the Sinkhorn algorithm accelerates total computational time more than two times compared to the OT-based LPF when the ensemble size is 64 or more. The Sinkhorn-based resampling would be a promising tool for applying the LPFs to account for non-Gaussian prior error distribution with many ensemble members.

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Large ensemble climate projections for Japan's Pacific side depict a greater increase in extreme high temperatures than in mean temperature, driven by changes in near-surface pressure arising from global warming. An exception to this pattern is the Kanto Plain, also on the Pacific side, for which a smaller increase is simulated. We investigated, using the large ensemble projections, the causes on this small increase and examined the variability in future-temperature projections focusing on surface winds at multiple extreme levels. Global warming causes cool air from surrounding areas to suppress the rise in extreme high temperatures over the plain, by contrasting changes in surface wind between inland and coastal areas of the plain: Intensified local advection inland draws cooler air from coastward regions, whereas synoptic-scale shifts in wind patterns channel high-latitude air toward coast areas. Under simulated temperature extremes of ∼10° above the climatological mean, generation of a Foehn-type wind enhances the development of temperature extremes over the Kanto Plain, similar to other Pacific regions of Japan. Although such events are rare, their future thermal condition is anticipated to be more severe.

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This study investigates interactions between the lower stratosphere and troposphere in the idealized Radiative-Convective Equilibrium (RCE) simulation using the Vector Vorticity cloud-resolving Model (VVM). We conducted a long-term RCE simulation with an elongated domain size and high resolution for two years. This allows for a comprehensive analysis of the relationship between domain-averaged zonal wind oscillations and different convective structures. The oscillation is observed to be asymmetric in the first three cycles and symmetric in the last two cycles. The differences in convection structures are found: squall-line-like convection and aggregated convection. The results show that the aggregated convection has more convective core clouds than squall-line-like convection, leading to a faster transition of QBO-like oscillation. In conclusion, this study provides new insight into the impact of different convective structures on QBO-like oscillation.

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To improve remote sensing techniques for global environmental research, aerosol models, indispensable inputs to radiative transfer calculations, should be region specific. Here, we focus on the Japanese region, which is situated downwind of the Asian continent, including China, characterized as one of the most significant sources of aerosols globally. By combining 10-year-long sky-radiometer-retrieved aerosol data from 14 Japanese sites with the k-means++ clustering method, we found that the data were reasonably categorized into four aerosol models: mixed, light-absorbing, oceanic, and oceanic plus urban aerosols. Interestingly, the data were not classified solely as urban aerosols, reflecting that Japan is an island country surrounded by the sea and the air pollution levels were not high. The contribution of the “light-absorbing” category was particularly high at the Fukue site situated in western Japan, as it is close to the Asian continent but isolated from local pollution. Additionally, our results for the Chiba site, which is part of the greater Tokyo megacity located in eastern Japan, indicated that the fraction of the “oceanic” category increased recently, owing to improvements in air quality.

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Improving the accuracy of global precipitation estimates is practically important to predict hydrological disasters such as floods and droughts. Owing to the Global Precipitation Measurement mission and its constellation satellites, surface precipitation can be estimated globally based on microwave radiometers (MWRs). However, MWR-based precipitation is known to be biased, such as overestimation over land. This study aims to improve MWR-based precipitation of Global Satellite Mapping of Precipitation (GSMaP_MWR) through histogram matching against precipitation retrieval based on satellite-borne Ku-band precipitation radar (KuPR) observations. For that purpose, we first developed cumulative distribution functions (CDFs) of hourly precipitation for GSMaP_MWR and the KuPR data for each 0.1° × 0.1° pixel in four seasons independently using data during 2015-2020. The CDF-based histogram matching successfully adjusted seasonal average precipitation of GSMaP_MWR closer to that of the KuPR products globally. Larger corrections were observed over land especially in the summer hemisphere. Validations against radar/raingauge-analyzed precipitation in Japan revealed that the histogram matching successfully improved GSMaP_MWR precipitation in general. The methodology of this study can also be applied to other agency's MWR-based precipitation estimates and their subsequent products such as gauge-adjusted global precipitation.

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This study collected and analyzed data to predict particulate matter (PM) concentrations in Korea at regular intervals. Automated synoptic observation system data, real-time atmospheric observation data from AirKorea, and Geostationary Korea Multipurpose Satellite – 2A data were used. We also used deep learning, which is useful for PM predictions. The deep learning model used a neural network (NN) to predict concentrations of PM with a diameter less than 2.5 μm (PM_2.5) and PM with a diameter less than 10 μm (PM₁₀). To illustrate the results of the NN model, we calculated the Shapley value using eXplanable Artificial Intelligence (XAI) in the SHapley Additive exPlanations (SHAP) library. The difference in the analysis according to the diameter of aerosols was explained. To analyze the contribution of features for each grid, the SHAP values were normalized. The normalized SHAP values were clustered and represented visually. PM_2.5 and PM₁₀ were classified into four clusters. The next day's PM_2.5 and PM₁₀ predictions were both heavily influenced by weather variables in the western region, and air quality data were more influential in the inland region. Unlike PM_2.5, the next day's PM₁₀ prediction in the southern region was affected to a greater degree by the wind.

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An alternative method to estimate the differential reflectivity (ZDR) bias is proposed. The method collects data bins with “weak echo” by the liquid hydrometeor, which theoretically should be spherical (not oblate) to result in a ZDR of ∼ 0 dB, to calculate the averaged ZDR as the bias. The obtained results are comparable to those from traditional “birdbath” scans in hourly data to prove the validity. The present method can be used to better sample the temporal variation, without operating special scans, such as birdbath scans. The supplemental method for the short-pulse region, when it was difficult for the weak-echo method to directly obtain the valid result, is also demonstrated.

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We evaluated the mass concentration levels and long-term trends of black carbon (BC) in the historical and future scenario simulations using 12 climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for East Asia, the region with the largest anthropogenic emissions. By comparing them with surface observations at two regionally representative sites, Fukue and Noto, for the period of 2009-2020, we found that the CMIP6 multi-model mean was approximately two times higher than the observed BC concentrations and did not reproduce the observed decreasing trend before 2014. Sensitivity simulations of emission inventories using a chemical transport model, GEOS-Chem, suggested that the overestimation and increasing trend of Chinese BC emissions in the CMIP6 historical inventory (CEDSv2017-05-18) were responsible for the higher concentrations and opposite trends in the CMIP6 BC simulations. The direct radiative effect of BC for CEDS was estimated to be 72% larger in East Asia than that for the ECLIPSEv6b inventory, which reproduced the observed BC concentrations reasonably well.

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This study proposes a deep learning approach called SolaCam to accurately estimate solar radiation from the images captured by cameras. The proposed SolaCam performs deep learning by utilizing both image features and theoretical maximum solar radiation that vary with time and location. The trained model is capable of accurately estimating solar radiation on the ground surface from sky images captured by smartphones, fixed-point cameras, and other devices. The developed SolaCam can use a remote sensing function, which estimates solar radiation, on inexpensive camera-equipped devices.

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The statistical and dynamical relationships between regional extreme precipitation events (EPEs) during wintertime in five Japanese regions and East-Asian synoptic weather patterns are addressed. Two of the five weather patterns, the southerly flow (SF) and low pressure (LP), are associated with about 50% of EPEs in all the regions. A regional dependency is found, with SF being more likely to cause extreme precipitation in two regions in the south of Japan and LP in the other regions, respectively. The large-scale dynamics leading to EPEs in each region are assessed by a combined Lagrangian and Eulerian analysis. In the two southern regions, EPEs are predominantly associated with direct moisture supply from the subtropical oceans. This is modulated by the large-scale flow pattern of SF. In contrast, EPEs in the northern coastal areas of the Sea of Japan and the Pacific Ocean are influenced by anomalous moisture supply from the cyclone-induced moisture convergence modulated by LP. The eastern coastal region of the Sea of Japan shows a mixture of both these moisture supply mechanisms. The strong link between EPEs and synoptic patterns might help to improve predictions of extreme events, even on the sub-seasonal forecast skill horizon.

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A new particle imaging radiosonde “Rainscope” has been developed, and for the first time, particle fall velocity measurement functionality was added to a balloon-borne device. Rainscope can capture a clear still image of precipitation particles in a cloud when they interrupt an infrared beam, using a CMOS camera equipped with an electronic shutter. It can also record the time when a particle passes the upper and lower built-in infrared sensors, enabling measurement of the velocity of falling precipitation particles. For ground testing in rain and snow, a ground-based Rainscope showed raindrop/snowflake size-fall velocity distributions similar to those obtained in previous studies. In a comparison with a Parsivel2 disdrometer in rain, the Rainscope results were in good agreement with the distributions obtained by an adjacent Parsivel2. In a test flight of Rainscope into a stratiform cloud, raindrops, mostly melted particles, snowflakes in the process of melting, graupel, and snowflakes were observed. It was observed that the fall velocity varied depending on the type of solid precipitation particles.

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The mass concentration of Asian dust in the atmosphere is an essential parameter of the atmospheric environment in East Asia. In April 2016, we conducted simultaneous observations using an optical particle counter (OPC) installed on a tethered balloon and a ceilometer in the Gobi Desert. We estimated the mass-extinction conversion factor MECF (gm⁻²) from the relationship between the dust extinction coefficient and dust mass concentration obtained by simultaneous observations. The MECF at Dalanzadgad in the Gobi Desert is 2.16 gm⁻² at 910 nm and 1.91 gm⁻² at 532 nm. A previous study on Asian dust showed that the values of the MECF were 1.78 gm⁻² in Beijing, 1.40 gm⁻² in Seoul, 1.18 gm⁻² in Tsukuba (Japan), and 1.04 gm⁻² at averaged AD-Net lidar stations in Japan. The MECF values decreased from the Asian dust source to the lee-side areas. This result suggests that the MECF depends on the size distribution of the dust.

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A physical snowpack model was forced by observed meteorological data to map the snow melting distribution over the Jozankei Dam basin, Sapporo, Japan. First, the snowpack model experiment forced by radar precipitation reasonably reproduced the snow environment in the basin, although it underestimated the snow depth in the northern area. Second, the map of the basin showed that the average difference in snowmelt was 22 days between upstream and downstream. On the other hand, the timing when melt forms become dominant in the snow layer was little affected by altitude and precipitation, and the dam inflow attained the peak 35 to 40 days after then.

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This study evaluates the impact of the mid-latitude oceanic front (MOF) on forecasts using the latest Japan Meteorological Agency seasonal prediction system. We focus on subseasonal predictions of the North Atlantic winter circulation by comparing hindcast experiments with different ocean model resolutions from 1991 to 2020. We find that the higher resolution of sea surface temperatures (SSTs) in the higher resolution model reveals SST warming south of the MOF and strengthening of local lower tropospheric circulation consistent with previous studies. Anomaly correlation coefficients of the atmospheric field are improved by about 0.1-0.2 in the lower-to-upper troposphere near the MOF for the higher ocean resolution. The influence of the MOF on ambient atmospheric fields is independent of El Niño Southern Oscillation conditions in both reanalysis and model. The greater accuracy of some predictions during La Niña years is probably due to the smaller errors of our model during La Niña compared with El Niño.

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The relationship between diurnal fluctuations of sea surface temperature (SST) in the Philippine Sea and the boreal summer intraseasonal oscillation (BSISO) and its difference between early and late summer are investigated using four-year (2017-2020) data of a moored buoy deployed at 137°E, 13°N. A strong diurnal cycle of SST is observed frequently during convectively suppressed phases of the BSISO, simultaneous with a weakening of surface winds and enhanced insolation. In addition, abrupt SST warming along with the strong diurnal cycle occurred in the middle of May in 2018 and 2019, in conjunction with the first BSISO of the year. Interestingly, the convectively suppressed phases of second BSISO showed small SST warming albeit the strong diurnal cycle, which can be attributed to a deepening of the warm isothermal layer. In the remaining two years, 2017 and 2020, SST increased gradually with small diurnal SST amplitude, which is presumably attributed to continuous surface winds with moderate strengths mixing the upper ocean. Moreover, the first BSISO was observed in late summer. These results suggest that the abrupt SST warming associated with the strong diurnal cycle is linked to the seasonal onset of the BSISO.

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This study represents a pioneering effort to establish a downscaling framework named “land-surface-physics-based downscaling” (LSP-DS) for agricultural meteorological prediction in the tropical-monsoon region of the Red River Delta, Vietnam. The primary focus of this article is to evaluate the performance of LSP-DS on meteorological variables, specifically temperature and humidity. In details, LSP-DS, which is based on the NCAR's Noah Multi-Parameterizations land surface model, incorporated by recently developed land use/cover data for Vietnam released by JAXA, is forced by ERA5 data for 2013; and the results are compared with ground-based station observations. The results exhibit excellent performance of LSP-DS versus observations with consistently high correlation coefficient between the two, highlighting the high potential of using LSP-DS for real-time operational forecast. The LSP-DS performance varies with different sub land use/cover categories, implying that the proper parameter settings could be key point for improvement. The findings of this research underscore the dual strengths of the LSP-DS approach: its computational efficiency and its remarkable efficacy in predicting spatial heterogeneity of local climates. These attributes render it well-suited for agrometeorological forecasting in a tropical monsoon climate, exemplified by the Red River Delta in Vietnam.

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