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, everyone in the world suffers from the crisis of the coronavirus disease 2019 (COVID-19). Even under this difficult situation, we have published special editions on “Typhoons in 2018-2019” and “Research on Extreme Weather Events That Occurred around East Asia in 2017-2021” as well as the regular issue in 2021. The COVID-19 pandemic stimulated new directions in meteorology and atmospheric sciences. We presented the SOLA Award in 2020 to the paper by Dr. Fumiaki Fujibe, entitled “Temperature anomaly in the Tokyo metropolitan area during the COVID-19 (coronavirus) self-restraint period” (Fujibe 2020).
We have been making continuous efforts to organize special editions coordinated jointly with Journal of the Meteorological Society of Japan. The special edition on “Research on Extreme Weather Events That Occurred around East Asia in 2017-2021” is welcoming submissions on relevant studies. With these efforts, the impact factor provided by Clarivate Analytics last year was 2.245, which is a rapid growth from the previous year.
We hope that readers would be our next authors. 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) gives The SOLA Award to outstanding paper(s) published each year. We are pleased to announce that The SOLA Award in 2021 will be presented 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).
Stratospheric aerosols play essential roles in radiative and chemical processes in the atmosphere and impact the climate of the Earth. The lidar observations of the temporal and spatial variations of the aerosols will provide essential information to understand the atmospheric processes related to the aerosols. Thus, there have been many studies on lidar observations of aerosols in the low and middle latitude regions. However, the observations in the Arctic are limited. In particular, there are no long-term observations of stratospheric aerosols throughout the year in the high Arctic. This study investigates the seasonal variations of stratospheric aerosols in the high Arctic by using long-term observations for about four years at Ny Ålesund, Svalbard. By carefully removing data affected by polar stratospheric clouds and volcanic eruption, the analysis shows the robust characteristics of the seasonal variations of background aerosols in the stratosphere. It is found that the backscattering ratio takes maximum values at altitudes between 13 and 16 km from December to March and at altitudes between 17 and 20 km from April to November. This observational evidence is highly evaluated in presenting the seasonal variations of stratospheric aerosols in the high Arctic, which will be helpful to understand the dynamical and chemical processes in the stratosphere.
The Editorial Committee of SOLA highly evaluates the significance of this study and therefore presents “The SOLA Award.”

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We examine the relationship between the record-warm winter (DJF) 2019/2020 over East Asia and the extremely weak hemispheric circulation anomaly. During this period, the polar cold-air mass (PCAM) flux over East Asia was the weakest on record since the DJF 1958/1959 due to the weak Siberian High. The zonal averaged surface temperature over the Northern Hemisphere mid-latitudes in DJF 2019/2020 was the highest since DJF 1958/1959 and was linked to the weakest PCAM flux at the mid-latitudes. The zonal mean field during this period was characterized by weak stationary waves, weak wave activity as diagnosed by Eliassen-Palm flux, and, to balance with this, record-weak extratropical direct meridional circulation (EDC). The weak EDC corresponded to weaker-than-normal meridional heat exchange and was consistent with warm anomalies in the Northern Hemisphere mid-latitudes, since the lower branch of EDC corresponds to zonally averaged cold air outflow. In addition, the statistical relationship also indicates the EDC intensity is negatively correlated with the surface temperature anomaly over East Asia.

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The horizontal movement vectors of the maximum rainfall area associated with local heavy rainfall around Tokyo in the afternoon of high-temperature summer days were analyzed using a numerical algorithm in order to investigate their relationship to the wind vectors in the free atmosphere. First, the movement vectors were objectively identified every 10 minutes from radar echo intensity data, and their time average from the onset to the termination of a heavy rainfall event was calculated. The results show that the maximum areas of localized heavy rainfall around Tokyo most frequently move to the east-southeast and southeast. Moreover, the direction of movement is shifted to the right relative to the mean direction of the free atmospheric winds in most cases. It is also implied that water vapor supply from the south in the boundary layer plays a role in the rightward movement.

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We propose a new application method in which radar/raingauge-analyzed precipitation amounts (RAP) produced by the Japan Meteorological Agency are spatially converted into 5km-resolution data, in addition to a three-hourly accumulation procedure, in order to statistically analyze localized heavy rainfall areas (HRAs) for a long period. A long-term trend and homogeneity in the appearance frequency of RAP with 5km-resolution converted by several methods, including the conventional method, are statistically evaluated in comparison with rain-gauge observations. The results indicate that the following application method is the most suitable to represent long-term variations in the appearance frequency of HRAs; (1) the converted value of RAP from 1 km to 5 km resolution is set to the 90th percentile value in 30 segments with 1km-resolution included in a grid with 5km-resolution, and (2) this spatial conversion is conducted after accumulating original RAP with 1km-resolution for three hours. Statistical analyses were performed for the appearance frequency of HRAs extracted from 5km-resolution RAP that were produced by the new application method, which indicates that the number of HRAs of the linear-stationary type could be increased without compromising the characteristics of HRAs extracted by the conventional method.

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Seasonal predictability of summertime Asian jet deceleration near Japan is examined using monthly mean data of hindcasts based on an operational seasonal prediction system of the Japan Meteorological Agency. Interannual variabilities of the Asian jet deceleration averaged during July–August are generally well predicted with moderate to high forecast skill starting from initial months from January to June. The seasonal predictability of the Asian jet deceleration in specific years is, by contrast, limited with large forecast errors. An inter-member regression analysis for the forecast errors of the Asian jet deceleration using ensembles shows that the forecast errors of the Asian jet are associated with those of the Asian jet deceleration near Japan. Furthermore, the forecast errors of El Niño Southern Oscillation (ENSO)-related excessive upper-tropospheric divergence near Southeast Asia can account for the errors of the northward shifted Asian jet. The above-mentioned results indicate that more accurate seasonal prediction of ENSO can further improve the seasonal prediction skill of the Asian jet deceleration and summer climate near Japan.

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This study investigates a potential impact of a rich phased array weather radar (PAWR) network covering Kyushu, Japan on numerical weather prediction (NWP) of the historic heavy rainfall event which caused a catastrophic disaster in southern Kumamoto on 4 July 2020. Perfect-model, identical-twin observing system simulation experiments (OSSEs) with 17 PAWRs are performed by the local ensemble transform Kalman filter (LETKF) with a regional NWP model known as the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM) at 1-km resolution. The nature run is generated by running the SCALE-RM initialized by the Japan Meteorological Agency (JMA) mesoscale model (MSM) analysis at 1800 JST 3 July 2020, showing sustained heavy rainfalls in southern Kumamoto on 4 July. Every 30-second synthetic reflectivity and radial winds are generated from the nature run at every model grid point below 20-km elevation within 60-km ranges from the 17 PAWRs. Two different control runs are generated, both failing to predict the heavy rainfalls in southern Kumamoto. In both cases, assimilating the PAWR data improves the heavy rainfall prediction mainly up to 1-hour lead time. The improvement decays gradually and is lost in about 3-hour lead time likely because the large-scale Baiu front dominates.

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A regional hybrid gain data assimilation (HGDA) system is newly developed using Weather Research and Forecasting model (WRF). The WRF-HGDA augments an ensemble-based Kalman filter (WRF-LETKF) with information from the variational analysis system (WRF-3DVAR) by combining their gain matrices. The performance of WRF-HGDA is evaluated by assimilating the GNSS radio occultation (RO) observations from the FORMOSAT-3/COSMIC (FS3/C) and the FORMOSAT-7/COSMIC2 (FS7/C2) under an Observing System Simulation Experiment (OSSE) framework. The results demonstrate that the variational correction improves the WRF-LETKF, with the equal-weighted WRF-HGDA outperforming its component DA systems in the moisture and wind fields when only conventional observations are assimilated. Assimilating additional RO data from FS7/C2 further improves the WRF-LETKF and WRF-HGDA systems. Although the variational correction for the mid-level temperature causes degradation in the WRF-HGDA analysis, this can be alleviated by adjusting the combination weight to include more flow-dependent information in WRF-HGDA at these levels. Further tuning of the static background error covariance used in WRF-3DVAR also brings some improvement in the WRF-HGDA wind analysis. Our results imply that a well-tuned variational system is critical for the accuracy of the regional HGDA analysis.

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Determining the thresholds for risk assessment is critical for the successful implementation of thermal health warning systems. A risk assessment methodology with multiple thresholds must be developed to provide detailed warning information to the public and decision makers. This study developed a new methodology to identify multiple thresholds for different risk levels for heat or cold wave events by considering simultaneously impact on public health. A new objective function was designed to optimize segmented Poisson regression, which relates public health to temperature indicators. Thresholds were identified based on the values of the objective functions for all threshold candidates. A case study in identifying thresholds for cold and heat wave events in Seoul, South Korea, from 2014 to 2018, was conducted to evaluate the appropriateness of the proposed methodology. Daily minimum or maximum air temperature, mortality, and morbidity data were used for threshold identification and evaluation. The proposed methodology can successfully identify multiple thresholds to simultaneously represent different risk levels. These thresholds show comparable performance to those using the relative frequency approach.

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This study examined the influence of stratospheric variability on the polar winter tropospheric climate. The winter-mean tropospheric condition can be well represented by a winter-mean stratospheric index (the Polar-night Jet Oscillation (PJO) index) defined from profiles of monthly polar temperature anomalies. In winters with a positive (negative) index, the winter-mean surface pressure anomaly tends to acquire a positive (negative) pattern resembling the Arctic Oscillation (AO). This tropospheric condition tends to become a persistent polarity of the AO index throughout the winter. This tendency is also found when the PJO index for each month is used. Although the PJO index in January shows the best results, those in early winter can be used as predictors for the entire winter troposphere. Use of the PJO index for the stratospheric effect on winter troposphere is compared with that associated with the occurrence of the major stratospheric sudden warmings. The origin of the decadal variability of the index is also discussed.

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For over 20 years, precipitation measurement has continued with spaceborne radars including the Precipitation Radar (PR) operating at 13.8 GHz on the Tropical Rainfall Measuring Mission and the Ku-band Precipitation Radar (KuPR) operating at 13.6 GHz on the Global Precipitation Measurement mission core satellite. PR and KuPR have essentially the same hardware designs and the same algorithm to make standard products (PRV8 and KuPRV06, respectively). The surface precipitation rate estimates (R) and related variables are statistically compared between PR and KuPR for a common observation area (within 35°N and 35°S) and period (April to September 2014). Due to the difference in sensitivity, the total precipitation amount recorded by KuPR is larger than recorded by PR by approximately 1.3%. For heavy precipitation, PR shows a smaller measured radar reflectivity factor (Z_m) and a larger R than KuPR. Z_m is affected by the attenuation and it is smaller for PR than KuPR, as the frequency is slightly higher. The attenuation corrected radar reflectivity factor is almost the same for PR and KuPR. However, the adjustment factor is larger for PR, which results in a larger R. Direct comparison between PR and KuPR during matchup cases demonstrates similar results.

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Future changes in extreme precipitation over the western North Pacific and East Asia (WNP-EA) are investigated using a 20 km mesh atmospheric general circulation model (AGCM). Time-slice simulations are performed under low- and high-emission scenarios using different spatial patterns of changes in sea surface temperature. In the WNP-EA region, future changes in the climatological mean of the annual maximum 1 day precipitation total (Rx1d) are characterized by a large meridional variation, where the higher the latitude, the greater the rate of increase in Rx1d, although this pattern is not so clear under the low emission scenario. This feature probably results from a combination of two factors: a greater warming in high latitudes and a decrease in tropical cyclone (TC) frequency in the subtropics. The future changes in Rx1d climatology for the 20 km AGCM show a marked difference in comparison with those of the lower-resolution AGCM and conventional climate models. Part of this discrepancy may come from differences in model resolution through representation of TCs, suggesting that coarse-resolution models may have some systematic bias in future projections of extreme precipitation in the WNP-EA region.

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Previous studies suggested that increases in ocean heat content result in strengthening of tropical cyclone (TC) and causing the associated disasters. In the western North Pacific (WNP), acceleration of increasing rates of tropical cyclone heat potential (TCHP: ocean heat content above 26°C from the surface) in the TC rapidly intensifying (RI: a 24-h intensity change of ≥ 30 kt) zone may have contributed to increases in TC intensity. However, there is no research on the relation of the acceleration of increasing rates to the variations in TCHP in a climatological view, differently from the relation to decadal variations such as Pacific Decadal Oscillation (PDO). This study focused on the relation of the variations in TCHP anomalies (TCHPA) to RITCs over the past six decades.

Although the annual mean TCHPA in the global ocean was not accelerated, the TCHPA accelerated recently in the late 1990s over the RI zone particularly in fall (October-December) in the WNP. The acceleration of the increase in TCHPA was possibly explained by the intensification of trade wind-driven ocean general circulation and the combination of the linear trend of TCHPA with PDO phase change.

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We introduce a new procedure to evaluate the snowdrift distribution over complex topography and improve the accuracy of snow avalanche warning systems. We select the Niseko region, Japan, as the target area, and first obtain the wind distribution map at a 50-m grid spacing for 16 wind directions. We then employ these maps to calculate the amount of snow erosion and deposition. We present a case study to demonstrate that the model output agrees fairly well with measurements of local wind speed and observed snowdrift distribution. While improvements can be made to improve the accuracy of the model results, including more comprehensive calculation procedures and quantitative comparisons of snowdrift formation and evolution, it appears that the presented snowdrift analysis is an effective tool that can be incorporated into a snow avalanche warning system that employs a simple snow-cover model.

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The energy dispersion process of westward propagating Rossby waves in tropical easterlies are investigated in the linear nondivergent barotropic atmosphere. The variations in wave energy and amplitude along energy dispersion paths are calculated by solving the wave action conservation equation. The results suggest that a westward marching ray can form a cycle-like path near the turning latitude that is located in easterlies. Waves with shorter periods propagate between two turning latitudes, which are located in either the easterlies or westerlies and have the largest meridional propagation range. Waves with longer periods propagate between a turning latitude in westerlies and a critical latitude in easterlies. Both wave energy and amplitude can simultaneously increase to their maximum values at the turning latitudes that are located in easterlies. This implies that waves may develop significantly. Wave energy and amplitude do not always have an in-phase variation when the ray moves toward the turning latitude that is located in westerlies. The oscillating ranges of wave energy and amplitude are also limited. In this case, waves may not develop significantly.

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As a complement work to the authors' previous studies, we examined the pre-typhoon rainfalls (PRE) ahead of typhoon T0918 (Melor) in October 2009. The influence of moistening in the upper atmosphere induced by the northward ageostrophic winds on PRE precipitation was examined by a sensitivity experiment using a cloud resolving model with a horizontal resolution of 2 km.

The cloud resolving simulation showed a large impact of the water vapor in the upper atmosphere on the precipitation over western Japan. In the sensitivity experiment where the moisture in the middle and upper layers was reduced over the area off the south coast of western Japan, the water vapor reduction area was advected northward, and the snow in the middle and upper layers and the cloud ice in the upper layer decreased, reducing the rain below the melting level. The intrusion of drying air into the upper atmosphere reduced the thickness of the moist absolutely unstable layer (MAUL), and the maximum intensity of convective updrafts decreased by about 10% in the test experiment. In this case, the increase of rain in PRE was primarily caused by the deep northward water vapor transport which yielded a large amount of condensation in the middle and upper layers, and change of moist instability in the upper atmosphere subsidiarily enhanced the convective updrafts.

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In this study, we explored the impacts of midlatitude western North Pacific (WNP) sea surface temperature (SST) on tropical cyclone (TC) activity at intraseasonal to seasonal time scales during the 2018 boreal summer. During this period, a positive SST anomaly occurred in the midlatitude WNP and subtropical central Pacific; TC activity was abnormally high under the influence of the strong Asian summer monsoon. We performed sensitivity experiments using a global cloud system-resolving model for global SST (control, CTL) and SST that were regionally restored according to midlatitude WNP climatology (MWNPCLM). TC track density in the eastern WNP was higher in CTL than in MWNPCLM, in association with large-scale atmospheric responses; enhanced monsoon westerlies in the subtropical WNP, moist rising (dry subsiding) tendencies, and reduced (enhanced) vertical wind shear in the eastern (western) WNP. Enhanced TC activity in the eastern WNP was more distinct for intense TCs and during the active phase of intraseasonal oscillation (ISO). These results suggest that the impacts of midlatitude SST anomalies can reach lower latitudes to affect TC activity via large-scale atmospheric responses and ISO, which are usually overwhelmed by the impacts of SST anomalies in the tropics and subtropics.

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The technique for composing a small subset of global climate models is critical to provide climate scenarios for impact and adaptation studies of regional climate changes. A recent study developed a novel statistical method for selecting a mini-ensemble of five climate models from the Coupled Model Intercomparison Project Phase 6 for widely capturing different future projections of Japanese climate across eight atmospheric variables at the surface. However, it remains unclear which mini-ensemble model contributes to efficiently covering the full projection ranges. Here, we rank each mini-ensemble projection around Japan among a full ensemble, showing that the selected five models capture the full ranges without systematic biases, except for relative humidity. Furthermore, we find that the widespread global warming level contributes to covering well the projection uncertainties in the daily-mean, maximum and minimum air temperatures and downward longwave radiation but not in precipitation, solar radiation, relative humidity, or wind speed. As the last four variables are sensitive to various factors, such as large-scale circulation and aerosol-forcing changes, rather than global-mean temperature changes, the model selection method featured here is preferable for capturing the wide future projection ranges in Japan.

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The number concentrations of microbial (counted as viable) particles and size-separated particles were measured continuously in Imizu City, Toyama, in the coastal region of the Sea of Japan, in 2015 using a commercial real time viable particle counter. From February to June, large increases in the number concentrations of coarse particles with rapid increases of viable particles were observed during Asian dust events. In mid-July, a phenomenon was observed in which the number concentrations of viable particles decreased, although coarse particles significantly increased. From the results of the backward trajectory analysis, the phenomenon was considered to be due to the transport of volcanic ash from Nishinoshima. The monthly average number concentrations of the viable particles were highest in September, whereas the average concentrations of coarse particles were at a maximum in April.

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 A rapid rise of the lightning activity center in the upper part of a cloud is called a lightning bubble (LB). It remains unclear how LBs occur in thunderstorm clouds. Recently, high-spatiotemporal resolution data obtained by a phased array weather radar enabled observation of temporal changes in the three-dimensional structure of precipitation cores in a precipitation cell. To understand the mechanism by which LBs occur, we examined the relationship between the time-evolution of precipitation cores and the flash initiation points.

 After a precipitation core developed in an isolated thundercloud, the top height of the core reached its highest altitude and then started to descend. Meanwhile, the echo tops above the core continued to rise, which is termed an upward reflectivity pulse (URP). Over an hour, nine URPs were successively observed in the thundercloud. The average tracking period of the URPs was 3.9 minutes. Flash initiation points appeared near the highest points of the URPs and continued to rise with time. These observational results suggest that URPs cause LBs by enhancing the electric field, via the separation of graupel and ice crystals near the highest points of ascending URPs.

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Large-amplitude meteotsunamis were observed in many areas in Japan, following the arrival of barometric Lamb waves emitted by an underwater volcanic eruption of Hunga Tonga-Hunga Ha‘apai in January 2022. We modeled the power spectra of the tidal level data obtained from 12 tide stations of the Geospatial Information Authority of Japan, based on a method of transfer function which converts the barometric pressure pulse spectra into the meteotsunami spectra. The obtained transfer functions are similar at 12 stations. The pressure pulse spectra are obtained from the ensemble average of ∼1500 Soratena weather sensors of Weathernews Inc. distributed over Japan. The observed meteotsunami spectra can be characterized by the enhanced seiche eigenmodes at each station excited by the mesoscale pressure pulse within the amplitude error of 50%, which contributes for accumulating the necessary knowledge to understand the potential dangers in various different areas over Japan.

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Climate changes around Japan associated with upper troposphere and stratosphere responses of global warming during December-January-February were investigated using the storyline approach and the Coupled Model Intercomparison Project 5 dataset. Climate change was calculated by subtracting the 1959-1990 mean in historical simulations from the 2068-2099 mean in the Representative Concentration Pathways 8.5. Four storylines in plausible future climates were discussed by considering two remote indices representing tropical amplification (tropical upper tropospheric temperature changes) and stratospheric vortex strength. Stratosphere-troposphere connections in terms of zonal wind responses are most pronounced in the storyline of high tropical amplification with strong stratospheric vortex in which the subtropical jet shifts substantially northward. The multimodel mean displays more (less) precipitation in the northern (southern) parts of Japan, while the storyline of high (low) tropical amplification with strong (weak) stratospheric vortex shows increasing (decreasing) precipitation in most parts of Japan. Projected precipitation changes around Japan depend heavily on the storyline adopted and the degree of global warming in these two storylines. Alternatively, precipitation changes depend mostly on the overall strength of global warming with minor influences from storylines in the case of low (high) tropical amplification with strong (weak) stratospheric vortex.

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 On 15 January 2022, the volcano Hunga Tonga about 8000-km away from Japan explosively erupted. Following the eruption, tsunami-like sea-level fluctuations were observed in Japan, much earlier than expected based on the oceanic long-wave propagation from Tonga. By contrast, atmospheric pressure disturbance presumably due to the eruption was also observed about 30 minutes before the sea-level change. Therefore, the observed sea-level fluctuations can be considered as meteotsunamis forced by the pressure perturbation rather than tectonically forced by the eruption, but the mechanism is not yet fully understood.

 This study attempts to understand the nature of this meteotsunami by using a simple one-dimensional shallow-water model. The results show that the time and amplitude of the observed sea-level changes are consistent with the simulated sea-level changes forced by the atmospheric forcing. A set of experiments with different bathymetry profiles also reveals the importance of amplification due to near-Proudman resonance over deep basins and the shoaling effect over the continental slope, while extremely deep and narrow topography such as trenches is of second-order importance.

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The numbers of heavy air pollution events per year in Beijing have decreased significantly since 2017. To find out the reasons and how meteorology and emissions control have played a role in this change, we used the WRF-SMOKE-CMAQ modeling system to reconstruct the characteristics of the fine particulate matter (PM_2.5) concentrations from 2013 to 2019. The model system performed well, and the correlation coefficients (R) between the simulated and observed daily PM_2.5 concentrations were all above 0.64. The model results also show that the meteorology contributed approximately ±5 g/m³ to the annual average PM_2.5 concentrations. More interestingly, the coincidence degrees of the simulated PM_2.5 concentrations to the heavy pollution (daily PM_2.5 concentration > 150 g/m³) dates decreased significantly after 2016. Meteorology plays an important role in reducing the number of heavy pollution days. According to the model results under the same emission scenarios, the average numbers of heavy pollution days from 2017 to 2019 decreased by 33% compared to the period from 2013 to 2016, while the numbers of good days changed by less than 1%. These results also indicate that meteorology made a significant contribution to decreasing the number of heavily polluted days after 2016.

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We conducted numerical simulations on a case of local “Karakkaze” wind on 23 March 2009. On this day, an aircraft crashed on landing at Narita Airport in the eastern Kanto Plain in Japan in the early morning when surface winds were significantly strengthened. Numerical simulations were used to elucidate the characteristics and mechanism of the strong wind over the Kanto Plain. This strong wind was identified as the Karakkaze wind, which occurs in the lee of the convex mountain range northwest of the Kanto Plain. The vertical shear associated with the Karakkaze wind could cause strong turbulence near the surface. The results of a sensitivity experiment suggest that the presence of the mountain convexity is essential for the development of the Karakkaze wind. Backward trajectory analyses reveal the area where the Karakkaze wind originated upstream of the mountain range. The horizontal wind speed in this area is even weaker than in the northern area. However, unlike in the northern area, the air with large momentum descends from altitudes much higher than the height of the dividing streamline owing to the mountain convexity, thereby driving strong surface winds in the leeward area.

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We investigated the sub-seasonal predictability of heavy snowfall events in Iwamizawa, Hokkaido, using the Japan Meteorological Agency's 1-month ensemble predictions. First, the self-organizing map (SOM) technique was applied to the Japanese 55-year Reanalysis sea-level pressure anomalies to identify weather patterns resulting in heavy snowfall. It revealed that heavy snowfall developed in SOM nodes (weather patterns) with low-pressure centers to the east/northeast of Hokkaido and Siberian high to the west, resulting in westerly to northwesterly monsoon winds traversing the Sea of Japan towards western Hokkaido. Next, ensemble forecasts were projected onto the SOM map to determine the predictability of weather patterns up to a month in advance. For winter 2019, there was relatively low probability of projecting a high number of ensembles in SOM nodes to those observed in the reanalysis. In contrast, much higher probability was seen in 2020 to ∼10 forecast days. When considering multiple SOM nodes that contribute to heavy snowfall in the forecast, both winters saw more ensemble members predicting heavy snowfall to ∼10 forecast days. We also saw a higher probability of heavy snowfall beyond 10-days in 2020. These results highlight the potential benefit of incorporating multiple weather patterns to forecast heavy snowfall.

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This study investigates the diurnal variation of surface wind divergence in the seas of the Maritime Continent by using satellite scatterometer observations and atmospheric reanalysis data. This is the first study to demonstrate the distribution and seasonal variation of the diurnally varying surface winds in the Maritime Continent in terms of wind divergence. Wind divergence develops from the coasts of the islands toward the center of the seas and dominates during the afternoon and evening hours. Wind convergence dominates over the seas during the nighttime and morning hours. The offshore extensions of the wind divergence and convergence from the coast differ regionally and thus show the asymmetric patterns with respect to the center of the seas. In particular, strong wind divergence develops from the southern coasts of the Java Sea and the Arafura Sea to extend northward beyond the center of the seas. The diurnal amplitudes of wind divergence vary seasonally and reach a peak in September in most of the seas. The switching times between wind divergence and convergence are almost fixed throughout the year regardless of the monsoon reversal.

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This study examines the pattern transition of dust events identified based on dust RGB images from the Himawari-8 satellite, along with associated key circulations and dynamic features, during spring 2016-2020. The dust RGB images are ordered onto a 4 × 3 topological map according to the spatial similarity of the dust distribution using self-organizing maps. In this topological map, the dust distribution exhibits mainly an eastward displacement or amplification from the Taklimakan Desert to the Gobi Desert. The key circulation triggering the transition of dust pattern is the large-scale tilted ridge from Xinjiang to Siberia. Such a northeast–southwest-oriented ridge conveys cold air into Tibet and causes the near-surface Siberian high extending southward from the Sayan mountains to central China. Consequently, dust intrudes from the Gobi Desert into northern China. In contrast, a zonal “+ − +” wave train in the upper troposphere confines the near-surface high over western Siberia and induces the near-surface cyclogenesis over Mongolia and northern China. As a result, the dust is mainly concentrated over the Taklimakan Desert, with weak influence over Mongolia and northern China.

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The procedures for identifying and classifying heavy rainfall areas of linear-stationary type (LS-HRAs) from the distributions of radar/raingauge-analyzed precipitation amounts (RAP) were improved to extract “senjo-kousuitai” with elongated and stagnant characteristics that causes localized heavy rainfall in Japan. The improved procedures were verified based on subjective judgments (‘certain’, ‘doubtful’, and ‘suspect’) whether LS-HRAs possess the characteristics of typical senjo-kousuitai. Criteria for excluding LS-HRAs judged to be ‘suspect’, mainly associated with tropical cyclones (TCs) and non-stationary mesoscale convective systems, were introduced to optimally extract senjo-kousuitai events. The criteria were determined by the distance between LS-HRAs and TC centers (DLT), the maximum total RAP of LS-HRA (total RAP), and the properties of each RAP distribution at every hour during the LS-HRA extraction period, e.g., DLT ≤ 500 km and total RAP < 200 mm. By applying these criteria, 372 senjo-kousuitai events were extracted from 452 LS-HRAs during the warm seasons (April–November) in 2009-2020, although approximately 35% of the LS-HRAs judged to be ‘suspect’ were not excluded. The criteria associated with TCs excluded them more effectively than the other factors. The improved procedures for extracting senjo-kousuitai events are expected to be used effectively for their statistical analyses.

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This study performed 4-day numerical integration in 1-hour intervals using the Weather Research and Forecasting (WRF) model for four major cases of heavy snowfall that occurred from 2020 to 2021. The model-predicted snow depth data were compared with the ground-observed snow depth and the satellite-observed snow cover data and then were statistically verified. The scalar verification results for ground data from the four cases showed a root–mean–square error of 2.55-16.67 cm and a correlation coefficient of 0.48-0.80, whereas the verification results with satellite data showed the correlation coefficients of 0.38-0.60. For categorical verification, using a threshold value of a snow depth exceeding 5 cm, the proportion correct was 90% or higher for ground observations of each case. In addition, in the satellite categorical verification, when the threshold value of the Snow Cover Fraction (SCF) exceeds 0.5, the proportion correct was 50% or more. These results are meaningful because the model snow depth verification methods were devised strategically for the first time using both the snow depth data of the mesoscale ground observation networks and ultra-high-resolution Sentinel-2 satellite data currently available in Korea. The findings of this study will contribute to the development of a high-resolution numerical prediction model and its verification methodology for snowfalls in the Korean Peninsula, eventually leading to increased prediction accuracy and reduced snow damage.

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This study investigated a recent tendency of interannual precipitation variations during the Baiu season (June–July) in southern Kyushu, Japan. Long-term satellite precipitation observations revealed a significant amplification of the interannual variability of Baiu precipitation after the beginning of this century and the appearance of a quasi-quadrennial variation (QQV). Composite analyses with respect to the unstable regime of Baiu activity when the QQV prevailed suggested a possible link between the Indo-western Pacific Ocean Capacitor (IPOC) mode and the QQV. Regression analyses with an IPOC index showed the dominance of an anomalous anticyclone in the lower troposphere centered over the South China Sea and the Philippine Sea and enhanced poleward moisture transport along its western periphery. The interdecadal shift in remote IPOC influence seen around the year 2000 featured the westward (northward) extension of the low-level anomalous anticyclone toward the Bay of Bengal (southern Japan); consequently, the significant moisture flux convergence area covered southern Kyushu during the unstable Baiu regime, consistent with the QQV appearance during the same period. It is also inferred that the IPOC mode modulation may come from the increased impact of central Pacific El Niño/Southern Oscillation on the IPOC in recent decades.

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Extreme rainfall (ER) in Indonesia frequently leads to floods and landslides, disrupting economic activity and impacting human lives. Here, we investigate ER variability in association with climate teleconnection patterns (CTP) including the El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Madden-Julian Oscillation (MJO), using extreme value analysis based on daily rainfall data from 32 stations for 30 years (1985-2014). By fitting a generalized extreme value distribution, a significant association between the annual maximum rainfall (AMR) and CTP was found in 12 of 32 stations. The sensitivity test of location parameter showed that the AMR-CTP interconnection was spatially inhomogeneous. The positive (negative) significant association of ENSO and IOD to AMR was noticeable in south-western (eastern) Indonesia. Additionally, MJO positive (negative) association was detected at 4 (3) stations mostly located in Sumatra (Java) Island. Furthermore, the return level analysis shows that the 20-year ER intensity waiting time will be shorter and longer when CTP indexes strengthen and weaken, suggesting a potential increase and decrease in the likelihood of future ER occurrences, respectively. These results are relevant for understanding the relationship between ER and CTP that should be considered in the adaptation and mitigation plans to minimize the ER impacts.

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Despite the importance of seasonal snow in Japan, quantitative information on seasonal snow mass in the whole area is lacking. To understand the current mass balance of seasonal snow cover, we develop a method to quantify the mass balance of seasonal snow all over Japan using the Japan Meteorological Agency's operational regional atmospheric model, Local Forecast Model (LFM), as well as the snow physics model, Snow Metamorphism and Albedo Process (SMAP). Our model simulations using the LFM-SMAP model chain show that the seasonal snow water equivalent (SWE) evolution is mostly controlled by snowfall and runoff. It is estimated that the seasonal peak area-integrated SWE in Japan reaches 42.2 Gt on average during the 2017-2022 winters, and 60.1 Gt (+43% with respect to the average) and 22.0 Gt (−48%) during relatively heavy (2017-2018) and relatively light (2019-2020) snow years, respectively. The ratios between seasonal peak area-integrated SWE and winter-accumulated (November to February) snowfall amounts for the heavy, average, and light snow years are 83%, 74%, and 59%, respectively.

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Anomalous coldness was observed over midlatitude Eurasia in December 2020 and over subpolar Eurasia in January 2021. The former was accompanied by the Warm Arctic and Cold Eurasia (WACE) pattern, while the latter by the negative phase of the Arctic Oscillation (AO). A set of large ensemble experiments with an atmospheric general circulation model suggests a contribution of reduced Arctic Sea ice to the midlatitude cooling and WACE pattern in December 2020. The tropical and extratropical sea surface temperature (SST) anomalies, however, contribute to warming over midlatitude Eurasia. In January 2021, neither the sea ice nor SST anomalies can explain the subpolar Eurasian cooling and the negative AO in our experiments.

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In this study, we investigated the remote effect of warm sea surface temperatures (SSTs) in the Kuroshio region of the East China Sea (ECS) on heavy rainfall that occurred in southern Kyushu, Japan, on 3 July 2020 using the Weather Research and Forecasting model. To examine the effect, a simulation with realistic SSTs and two simulations with reduced SSTs in the ECS Kuroshio region were performed. Backward- and forward-trajectory analyses showed that low-level parcels in the simulation with warmer SSTs in the ECS Kuroshio region possessed larger amounts of water vapor than those in the reduced-SST experiments. The difference in the water-vapor amounts of low-level parcels between the simulations with warmer and colder SSTs remained until the parcels started to ascend in the heavy rainfall area. In addition, there were many more parcels with extremely large amounts of water vapor in the simulation with warmer SSTs. Such an increase in low-level water-vapor amounts under warmer SST conditions in the ECS Kuroshio region led not only to enhancement of the precipitation source but also to atmospheric destabilization, resulting in the production of a large amount of precipitation.

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This study investigated the spatial and temporal modulation of aerosol species by monsoon intraseasonal oscillation (MISO) using the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations from 2003 to 2019. The climatological spatial distribution of aerosol species showed long-range transport of sea-salt and dust to Indian landmass from the Arabian Sea and desert regions of the Arabian Peninsula, respectively. While organic matter, black carbon, and sulfate originated mainly in India. In the eight MISO phases, southwesterly/westerly strengthening/weakening was responsible for aerosol species transport and spatial distribution. During MISO break to active transition phases 2-5, strong southwest monsoon winds transported sea-salt aerosols from the Arabian Sea to the Indian region. In the active-to-break transition phases 5-7, dust transport strengthened from the Arabian Peninsula. The dust aerosols over the Indian subcontinent peaked in phases 6 and 7. In phases 2-5 (6-8, 1), direction of strong winds along the Indo-Gangetic Plain influenced increased levels of organic matter, sulfate, and black carbon aerosols in the western/northwestern (eastern/northeastern) regions of India. These dynamic spatial changes in aerosols caused by MISO over the Indian region influence the shortwave and longwave radiation balances that can influence monsoon circulation.

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Ensemble future climate projections were performed using the Meteorological Research Institute Earth System Model version 2.0 (MRI-ESM2.0) for sand and dust storms (SDS), which have a significant social and climatic impact on East Asia. A replication experiment using MRI-ESM2.0 reproduced the decreasing trend of SDS emissions in the Gobi Desert in the early 21st century. Prediction experiments using MRI-ESM2.0 in Coupled Model Intercomparison Project phase 6 future scenarios indicated no considerable differences in the total amount of SDS emissions in the Gobi Desert for 2015-2100; however, SDS emissions increased with warmer scenarios in spring and autumn. In particular, March in the highest warming scenario (SSP5-8.5) exhibited an annual increase rate of 3.0% in SDS emissions for the years 2015-2100. Friction velocity was highly correlated with SDS emissions, with a correlation of ∼0.6 for all climate scenarios throughout the year. In spring and autumn, snow cover exhibited a low negative correlation with SDS emissions, while ground temperature exhibited a positive correlation. The increase in SDS emissions and subsequent dust transport by midlatitude westerlies in spring and autumn during accelerated warming scenarios could be attributed to the changes in friction velocity and erodibility due to the decrease in snow accumulation.

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In Mongolia, combined with the dry and windy climate during spring and autumn, the exposed sediment of mine tailings pond becomes an additional source of anthropogenic windblown dust and poses potential threats to the surrounding environment and human health. In this study, we reported on our first attempt to derive the spatiotemporal distribution of dust originating from the tailings pond of the Erdenet mine using a combination of ground-based in-situ measurements and Himawari-8 geostationary satellite remote sensing. Temporal evolution of the dust plume visualized by the RGB imagery corresponded well with the in-situ particle concentration measured on the ground. Under relatively cloud-free conditions, the dust RGB imagery from Himawari-8 clearly showed the spatial extent of the white dust plume originating from the tailings pond, in the range of 2,040-2,748 km². Therefore, the dust RGB imagery by Himawari-8 is demonstrated to be sensitive enough to resolve the highly localized anthropogenic dust, even from a point source as small as the tailings pond, and is effective in studying susceptible areas subject to associated heavy metal deposition and contamination.

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We developed a method for estimating the height and growth rate of volcanic eruption columns, at high-temporal resolution, by processing vertical cross-sectional images of areas around the crater obtained with a marine radar tilted on its side. We applied our method to 127 eruptions occurring at Sakurajima (Kagoshima, Japan) from June to December 2019 and successfully estimated the time-series height of the eruption column and its growth rate every 2.5 seconds. In 48 cases, we obtained the maximum height of the eruption column and confirmed that these results were consistent with those estimated using meteorological radar. Although the maximum height estimated with our method tended to be lower than that observed by monitoring cameras, results could be obtained even when observations were difficult due to cloud effects, etc.

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Analysis of the El Niño-Southern Oscillation (ENSO) phenomena has conventionally been performed using deviations from the mean. However, the question remains as to whether the mean is appropriate as the reference state, since it is sensitive to the existence of a few extreme events. In this study, the validity of the mean and mode as a reference is compared using an idealized simulation model. We show that the mode is not affected by the asymmetry of El Niño and La Niña and is more stable as a reference than the mean. Then, this result is also demonstrated using observed data. Observations also show that the relationship between the ENSO amplitude and the zonal shifts of the ENSO anomalies is more emphasized if the mode is employed. For the variables in the ocean interior, differences between the mode-based and mean-based methods appear throughout all seasons.

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We examined forty-five typhoons associated with insurance losses in Japan to explicitly describe typhoon-related variables that explain insurance-loss variations. Multiple regression analysis revealed that the combination of maximum wind speed and translation speed explained more of the variation in insurance-loss size than what the regression model with maximum wind speed alone did. Using maximum wind speed and gale-area radius as explanatory variables also slightly improved the explained variance, but it was less stable than the multiple regression model combining maximum wind speed and translation speed. The translation speed suggested an inland expansion of the strong-wind area associated with wind-speed asymmetry, while considering the exposure led to similar conclusions. Our regression model can be applied to estimate changes in the damage and uncertainty by adjusting the typhoon characteristics under multiple climate-change scenarios.

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A set of hydrological experiments for a flooding event on 11 September 2014 at Motsukisamu River in Sapporo were performed. Dynamical downscaling to 5-km resolution of a large-ensemble global simulation allowed us to estimate that a 99%-tile hourly precipitation in Sapporo would increase by 70% in a future climate, when the global-mean temperature increases by 4 K compared with the present climate. After developing a three-tank model of which parameters were optimized on the basis of the in-situ observation at the Motsukisamu River during the event period, the model was forced by hypothetical hyetographs of the event that would occur under the future climate. The results of this experiment suggested that the peak flow rate would increase by 75%. However, it was also revealed that an upstream aqueduct tunnel, just completed in autumn 2021, would effectively reduce the peak flow rate and mitigate the flooding risk even in extreme precipitation under the future climate.

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The ENSO phenomenon is investigated by building a fractional derivative recharge-discharge model in which the integer derivative is replaced with the left-sided Caputo type fractional derivative. The results suggest that when the highest order fractional derivative is larger than 1 but smaller than or equal to 2, the model exhibits a variation between exponential decay and pure harmonic oscillation. The system will strengthen to an El Niño/La Niña event and then weaken to the neutral state which does not require a zero value. Therefore, there is only a life cycle of an El Niño/La Niña event, rather than the life cycle of a complete ENSO event in the pure harmonic oscillation. When the highest order fractional derivative is larger than 2, the model exhibits an exponential-like amplified oscillation. The system benefits to exhibit the life cycle of strong ENSO events. The fractional derivative recharge-discharge model, in general, extends the integer model and can be applied in studying the complexity in ENSO phenomenon.

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