Scientific Online Letters on the Atmosphere (SOLA) has been a fully Open Access journal under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License (http://creativecommons.org/ license/by/4.0) since 2018, and has been added in the DOAJ (Directory of Open Access Journals) list. Last year, SOLA has updated the Guide for Authors and renewed its own web site (https://www.metsoc.jp/sola/).
In response to the extreme weather events in the summers of 2017 and 2018, SOLA welcomed submissions of paper on the related topics and has published the special edition “Extreme Rainfall Events in 2017 and 2018” as Volume 15A. The published papers cover the large-scale atmospheric and oceanic features of extreme weather in the summer of 2018 (Shimpo et al. 2019; Sekizawa et al. 2019; Takemura et al. 2019; Takaya 2019), the mesoscale environmental properties of the extreme rainfall in July 2018 (Takemi and Unuma 2019), the predictability of extreme weather in the summer of 2018 (Kotsuki et al. 2019; Matsunobu and Matsueda 2019; Kobayashi and Ishikawa 2019), the relationship between a typhoon and the rainfall in July 2018 (Moteki 2019; Enomoto 2019), the use of a gridded precipitation product in investigating extreme rainfalls (Yatagai et al. 2019), and the impacts of global warming on the extreme hot summer in 2018 (Imada et al. 2019).
We are growing. 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. I am pleased to announce that The SOLA Award in 2019 is going to be presented to the paper by Dr. Yukiko Imada et al., entitled with “The July 2018 high temperature event in Japan could not have happened without human-induced global warming”.
Attribution of individual extreme weather and climate events on human-induced climate change, called event attribution (EA), is often obscured by strong atmospheric fluctuations. By exploiting the large ensembles of d4PDF global and regional atmospheric model simulations, this study performs EA of the extreme heat event in Japan in July 2018. The authors first show, based on a comparison of two global ensembles, that the event would have had virtually no chance to occur without human-induced global warming. Second, with the regional ensemble dataset, they propose a new method to estimate changes in the occurrence of extreme heat events in Japan in accordance with global warming. These analyses answer public concerns on how global warming affected the devastating heat event and how it will under future greenhouse gas warming. The authors further proceed to examine atmospheric circulation features that induced the heat wave. With the model simulations and a reanalysis dataset, they conclude that the enhancement of the lower-tropospheric subtropical anticyclone in the North Pacific and the anomalous eastward expansion of the upper-level Tibetan high are part of naturally-driven teleconnection patterns and human influence on the circulation anomalies is undetectable.
The Editorial Committee of SOLA highly evaluates this process-based EA as well as the social impacts of the paper.

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Japan Meteorological Agency (JMA) best track data indicate that the number of rapid intensification (RI) tropical cyclone events in the western North Pacific increased from 1987 to 2018. To clarify whether this increase is due to climatological changes or qualitative changes in the data, the long-term trend of RI events in JMA operational Dvorak data, which have been used as the first guess for best track analysis, was investigated. Because the JMA Dvorak analysis procedure has remained almost unchanged since 1987, the temporal homogeneity of the Dvorak data is expected to be much better than that of the best track data. The results showed no discernable trend in Dvorak-based RI events over the 32 years. Although the frequency distribution of 24-h intensity changes changed slightly in the Dvorak analysis, that of the best track data changed significantly; as a result, the frequency of best track-based RI events increased after 2006. JMA started using microwave satellite imagery for best track analysis in 2006. This change likely affected the temporal homogeneity of the best track data. These results suggest that the increase in best track-based RI events was due mainly to qualitative changes related to advances in observational techniques.

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The observation operator for the Phased Array Weather Radar in the SCALE-LETKF data assimilation system is revisited, and the impact of its improvement on the analyses and forecasts is examined. The observation operator provides a functional relationship between equivalent radar reflectivity factor (Z_e) and hydrometeor mass density (W) of each precipitation particle category. The W–Z_e relationship is obtained by a radar simulator. This study performs a radiation code calculation with the parameters regarding particle size distribution of graupel consistent with the cloud microphysics scheme in the SCALE model. The newly obtained observation operator provides much stronger sensitivity of graupel mixing ratio to observed Z_e compared to the operator originally used in the model. To examine the impact on the SCALE-LETKF analyses and forecasts, an experiment on a 13 July 2013 heavy rain case is performed with the new observation operator and is compared with the previous study. The forecast initiated by the analysis using the new operator shows much more realistic evolution of Z_e in the middle troposphere, where a large amount of graupel is located. The overestimation of forecast Z_e is significantly alleviated by the new observational operator. The 30-minute forecast of surface precipitation rate is also improved.

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The 2015/16 El Niño is compared with the two previous strongest events, the 1982/83 and 1997/98 El Niño. The 2015/16 winter features a basin warming in the Indian Ocean, a negative sea surface temperature (SST) anomaly shifted to the north in the western Pacific Ocean in addition to a positive SST anomaly shifted to the west in the eastern Pacific Ocean. These SST distributions lead to suppressed convection in the Maritime Continent, and to a weakened Hadley circulation in the western Pacific Ocean. The eastern Asian monsoon in the 2015/16 winter was also weakened due to the dominance of the western Pacific (WP) pattern. On the other hand, the third and fourth centers of action of Pacific/North American (PNA) pattern in the 2015/16 case are obscure. This may be due to weak divergence in the eastern Pacific Ocean.

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Heavy precipitation frequently occurs over Kyushu, southwestern Japan, during the Baiu season, and abundant moisture transport is a key driving factor. To statistically understand the intensification of moisture transport to Kyushu during the Baiu season, synoptic-scale atmospheric conditions are examined using a composite analysis of reanalysis data. A heavy precipitation day is defined as a day with area-averaged daily precipitation over Kyushu that is larger than 1.0 mm and ranked in top 10% during May 31 to July 19 from 1981 to 2015. During such heavy precipitation days, the precipitation observed over Kyushu exceeds 100 mm day⁻¹. For several days before the occurrence of heavy precipitation over Kyushu, a plateau-scale disturbance develops over the Tibetan Plateau associated with daytime surface heating, and is characterized by cloud convection formation and eastward extension. During the eastward extension, latent heating from the cloud and upper-level high potential vorticity maintains the disturbance. The disturbance reaches northwest Kyushu on the heavy precipitation day, and a pair of positive and negative anomalies of relative vorticity over northwestern and southeastern Kyushu intensify the anomalous moisture transport.

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This study investigated future changes in extreme precipitation associated with tropical cyclones (TCs) around Japan using large ensemble regional climate simulations for historical and +4 K climates. Under the warmer climate, extreme TC precipitation, defined as the 90th percentile value of the maximum daily precipitation derived from each TC (TCP90), is projected to increase throughout Japan from Kyushu to Kanto. We attributed most of the increase in TCP90 to increased atmospheric moisture due to global warming. Furthermore, it was found that TCP90 is projected to increase for all TC intensity categories. However, the projected increase in intense TCs affects TCP90 in only a limited area. Stronger TCs enhance TCP90 over east- and north-facing slopes of mountainous terrain, while TCP90 in most other areas is insensitive to TC intensity. These results suggest that even relatively weak TCs could have potential to produce extreme precipitation that might cause natural disasters.

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This study investigated the environmental factors responsible for the development of heavy rainfall in eastern Japan during the passage of Typhoon Hagibis (2019) by using mesoscale gridded analysis data as well as observed data. Environmental indices for diagnosing stability and moisture conditions were examined. It was found that the whole troposphere is almost saturated and the column total water vapor content is extremely large. In the lower troposphere we identified layers of moist absolutely unstable states with the thickness deeper than 2 km. Such deep moist absolutely unstable layers as well as abundant moisture content and almost saturated troposphere set a high potential for convective development. Under these favorable environmental conditions, the fact that the heights of the absolutely unstable layers' bottom are comparable to the mountain elevations is considered to be favorable for topographic lifting of unstable, moist air, which will trigger and activate strong convection and hence heavy rainfall. In spite of a moderate amount of convective available potential energy and a nearly moist-adiabatic lapse rate, moist absolute instability, abundant moisture, and high humidity jointly play a key role to increase the potential for generating the present heavy rainfalls.

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This study aims to investigate the tradeoff between the computational time and forecast accuracy with different data assimilation (DA) windows of four-dimensional local ensemble transform Kalman filter (4D-LETKF) for a single-case severe rainfall event. We perform a series of Observing System Simulation Experiments (OSSEs) with 1-, 3-, 5- and 15-minute DA window in a severe rainstorm event in Kobe, Japan, on July 28, 2008, following the prior OSSEs by Maejima et al. (2019). Running 1-minute DA cycles showed the best forecast accuracy but with the highest computational cost. The computational cost could be reduced by taking a long DA window, but the forecast became less accurate even though the same number of observations were used. A significant gap was found between the 3-minute window and 5-minute window. With the 1- and 3-minute windows, the forecasts captured the intense rainfall, while with the 5-minute window or longer, the rainfall intensity was drastically underestimated. This single-case study suggests that 3-minute or shorter DA window be a promising method for a severe rainfall forecast, although more case studies are necessary to draw general conclusion.

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We conducted observation system simulation experiments (OSSE) to investigate the effects of water vapor vertical profiles observed by Raman lidar (RL) on forecasts of heavy precipitation in Hiroshima, Japan, on August 19, 2014 using a local ensemble transform Kalman filter. We employed a simulation result similar to reality as nature-run (NR) and performed two OSSEs. In the first experiment (DaQv), conventional observation data and vertical profiles of water vapor mixing ratio in air (q_v) estimated from NR were assimilated. In the second experiment (CNTL), only conventional observation data were assimilated. In DaQv, we assumed that the RL was in the low-level inflow that supplied water vapor to the heavy precipitation in Hiroshima. Assimilating q_v for several hours increased q_v around the RL observation station, especially at low level. The regions modified by the assimilation of q_v moved to Hiroshima by low-level inflow, resulting in 9-hour precipitation being approximately 28% greater than that of CNTL, and was thus closer to that of the NR. The OSSEs suggest that water vapor RL observations on the windward side of the heavy precipitation are a useful approach for improving precipitation forecasts.

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We have developed a new method of diagnosing the characteristics of ice particles using a bulk microphysics model. Our model tracked the mass compositions of different classes of ice particles, using their microphysical process of origin, such as water vapor deposition and riming. The mass composition from depositional growth was further divided into six components by the temperature and humidity ranges corresponding to the typical growth habits of ice crystals. In test simulations, the new framework successfully revealed the influences of riming and depositional growths of ice particles within clouds and on surface snowfall. The new approach enables weather prediction models to provide much more information on the characteristics of ice particles regarding crystal habits and the extent of riming.

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To understand the impacts of global warming on tropical cyclones (TCs) in midlatitude regions, dynamical downscaling experiments were performed using a 4-km-mesh regional model with a one-dimensional slab ocean model. Around 100 downscaling experiments for midlatitude TCs that traveled over the sea east of Japan were forced by large-ensemble climate change simulations of both current and warming climates. Mean central pressure and radius of maximum wind speed of simulated current-climate TCs increased as the TCs moved northward into a baroclinic environment with decreasing sea surface temperature (SST). In the warming-climate simulations, the mean central pressure of TCs in the analysis regions decreased from 958 hPa to 948 hPa: 12% of the warming-climate TCs were of an unusual central pressure lower than 925 hPa. In the warming climate, atmospheric conditions were strongly stabilized, however, the warming-climate TCs could develope, because the storms developed taller and stronger eyewall updrafts owing to higher SSTs and larger amounts of near-surface water vapor. When mean SST and near-surface water vapor were significantly higher and baroclinicity was significantly smaller, unusual intense TCs with extreme wind speeds and large amounts of precipitation around a small eye, could develop in midlatitude regions, retaining the axisymetric TC structures.

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Using long-term high-resolution operational radiosonde observation data from nine stations in the subtropics and mid-latitudes of Japan, this study performed statistical analysis of the dynamical characteristics of gravity waves (GWs). Wave generation by shear instability in summer was a particular focus because orographic GWs cannot propagate deep into the middle atmosphere through their critical layer in the lower stratosphere. The kinetic energy of summer stratospheric GWs is markedly large south of 37°N. Hodograph analysis revealed that GWs propagating eastward relative to the ground are dominant in summer. The percentage of GWs propagating energy upward (downward) is large above (below) the height at which the mean occurrence frequency of shear instability is high. The time series of the kinetic energy of stratospheric GWs exhibited statistically significant positive correlation with the occurrence frequency of shear instability slightly below the tropopause. These findings strongly suggest the possibility of excitation of summer stratospheric GWs by shear instability above the jet. The shear instability condition is satisfied more frequently in the region 30°N-35°N. This is probably related to two characteristics of the background fields slightly below the tropopause: larger vertical shear of zonal winds at higher latitudes and lower static stability at lower latitudes.

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In relation to projections of tropical cyclone (TC) frequency in a future warmer climate, there is a debate on whether the global frequency of TC seeds (weak pre-storm vortices) will increase or not. We examined changes in the frequency of TC seeds by occurrence frequency analysis (OFA) of vortex intensity (vorticity or maximum wind speed). We directly counted the number of vortices with various intensities in high resolution global atmospheric model simulations for present and future climates. By using the OFA we showed a clear reduction of the occurrence frequency of TC seeds and relatively weak (category 2 or weaker) TCs in a future warmer climate, with an increase in the frequency of the most intense (category 5) TCs. The results suggest that the OFA is a useful method to estimate the future changes in TC frequency distribution ranging from TC seeds to the most intense TCs.

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The ensemble average projections of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) ensemble show future increases in shortwave radiation at the surface (SW) in Japan. We reveal that the Arctic Oscillation-like atmospheric circulation trends cause cloud cover decreases around Japan, leading to increases in the SW.

In many cases, impact assessment studies use the outputs of only a few models due to limited research resources. We find that the four climate models used in the Japanese multisector impact assessment project, S-8, do not sufficiently capture the uncertainty ranges of the CMIP5 ensemble regarding the SW projections. Therefore, the impact assessments using the SW of these four models can be biased. We develop a novel method to select a better subset of models that are more widely distributed and are not biased, unlike the S-8 models.

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Bias corrected climate scenarios over Japan were developed using two distinct methods, namely, the cumulative distribution function-based downscaling method (CDFDM) and Gaussian-type Scaling approach (GSA). We compared spatial distribution, monthly variation, and future trends. The seasonal distribution of bias-corrected data using CDFDM closely followed the original general circulation model (GCM) outputs. GSA overestimated the amount of precipitation by 12-18% in every season because of an unsuitable assumption on the probability distribution. We also examined the contributions of each source of the uncertainty in daily temperature and precipitation indices. For daily temperature indices, GCM selection was the main source of uncertainty in the near future (2026-2050), while different Representative Concentration Pathways (RCPs) resulted in large variability at the end of the 21st century (2076-2100). We found large uncertainty using the bias-correction (BC) methods for daily precipitation indices even in the near future. Our results indicated that BC methods are an important source of uncertainty in climate risk assessments, especially for sectors where precipitation plays a dominant role. An appropriate choice of BC, or use of different BC methods, is encouraged for local mitigation and adaptation planning in addition to the use of different GCMs and RCPs.

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The severe air pollution events continue to occur every year during late October and early November in Delhi, forcing air/land traffic disruptions and anxiety in the daily life of the citizens. We analyze the behaviors of the air pollution events in October and November 2019 that arose from the crop-residue burning as seen using remote sensing techniques. Transport pathways and the mean transit time from the fire hotspots are evaluated using the FLEXPART (FLEXible PARTicle dispersion model). Our results suggest that the polluted regions in Delhi are partly influenced by the crop-residue burning. The uncertainty of our evaluation can be attributable to insufficient information on emission sources because the biomass burning emission based on daily-basis fire radiative power (FRP) of Moderate-Resolution Imaging Spectroradiometry (MODIS) is significantly degraded by the existence of hazy clouds. In future, it is desirable to establish a dense measurement network between Punjab and Delhi for the early detection of the source signals of aerosol emissions and their transport in this region. The FLEXPART model simulation shows the transport of emission signals from Punjab to Delhi, which further expands toward the Bengal region within a span of two days.

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The meridional propagation of Rossby waves links different latitudes. Traditional wave propagation theory is mostly discussed in the non-divergent atmosphere. This work emphasizes the influence of the divergent effect on wave propagation by analyzing wave solutions to the linearized shallow-water quasi-geostrophic potential vorticity equation on the zonal mean flow. Changes in the basic-state quantities and wave solutions generated from consideration of the divergent effect are highlighted. Compared with the non-divergent situation, more waves are allowed to exist and propagate to much higher latitudes in the divergent case. The turning latitudes are generally moved northward when the divergent effect is included. This main conclusion is robust in the idealized super-rotational flow and 300 hPa climatological flows in winter and summer. The divergent effect also tends to slow the speed of wave propagation and favor waves reaching remoter longitudes. These finding implicates Rossby wave propagation with divergent effect may contribute more to the long-distance teleconnection than that in non-divergent case.

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This study investigates the forecast sensitivity of an afternoon thunderstorm in northern Taiwan to the upstream condition associated with the prevailing warm and moist southwesterly winds on 16 June 2008. This event was initiated near noon and lasted for several hours with a maximum hourly precipitation rate of 69 mm hr⁻¹ at 14 LST.

Experiments are conducted to assimilate radial velocity only or both radial velocity and reflectivity data from radars at southwestern and southern Taiwan with the WRF-Local Ensemble Transform Kalman Filter Radar assimilation system. Results show that these experiments can predict the rainfall occurrence in northern Taiwan, but the location and rainfall amount is very sensitive to upstream environmental conditions. Assimilating the unfiltered topography-associated reflectivity noise upstream generates unrealistic light rain and cooling, which leads to a great reduction of rainfall in the target area. The precipitation prediction suggests that a careful topography-based quality control performed on the radar data can be essential to restore the necessary environmental conditions for forecasting the afternoon thunderstorm event.

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This study reveals the best combination of meteorological variables for the prediction of the number of emergency transport due to heat stroke over 64 years old in Tokyo metropolis based on a generalized linear model using 2008-2016 data. Temperature, relative humidity, wind speed, and solar radiation were used as candidates of the explanatory variables. The variable selection with Akaike's information criterion (AIC) showed that all the four meteorological elements were selected for the prediction model. Additional analysis showed that the combination of daily mean temperature, maximum relative humidity, maximum wind speed, and total solar radiation as explanatory variables gives the best prediction, with approximately 19% less error than the conventional single-variable model which only uses the daily mean temperature. Finally, we quantitatively estimated the relative contribution of each variable to the prediction of the daily number of heat stroke patients using standardized partial regression coefficients. The result reveals that temperature is the largest contributor. Solar radiation is second, with approximately 20% of the temperature effect. Relative humidity and wind speed make relatively small contributions, each contributing approximately 10% and 9% of the temperature, respectively. This result provides helpful information to propose more sophisticated thermal indices to predict heat stroke risk.

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This study examined the diurnal cycles of brightness temperature (TB) and upper-level horizontal winds associated with tropical cyclones (TCs) over the western North Pacific basin, making use of data retrieved from geostationary-satellite (Himawari-8) observations that exhibited unprecedented temporal and spatial resolutions. The results of a spectral analysis revealed that diurnal cycles prevail in TB variations over the outer regions of TCs (300-500 km from the storm center). The dominance of the diurnal cycle was also found in variations in the radial wind (Vr) in intensive TCs, although there was no dominant cycle in tangential wind variation. In addition, coherence spectra demonstrated that the diurnal cycles of TB and Vr are significantly coupled in intensive TCs. The migration speed of TB and Vr anomalies exceeded the time-mean Vr, and it was speculated that diurnal cycle signals propagate (i.e., are not advected) toward the outer regions of TCs.

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Two products from the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) algorithms, a flag of intense solid precipitation above the −10°C height (“flagHeavyIcePrecip”) and a classification of precipitation type (“typePrecip”) were validated by ground-based hydrometeor measurements and X-band multi-parameter (X-MP) radar observations of snow clouds on 4 February 2018. Contoured frequency by altitude diagrams of the X-MP radar reflectivity exhibited a significant difference between footprints flagged and unflagged by the “flagHeavyIcePrecip” algorithm, which indicated that the algorithm is reasonable. The hydrometeor classification (HC) by the X-MP radar, which was confirmed by microphysical evidence from ground-based hydrometeor measurements, suggested the existence of graupel in the footprints with “flagHeavyIcePrecip”. In addition, according to the information of the GPM DPR, the “flagHeavyIcePrecip” footprints were characterized by not only graupel but also large snowflakes. According to the information of X-MP radar HC, the “typePrecip” algorithm by the detection of “flagHeavyIcePrecip” was effective in classifying precipitation types of snow clouds, whereas it seems that there is room for improvement in the “typePrecip” algorithms based on the extended-DPR_m-method and H-method.

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The similarity of the turbulence intensity profile with the inner-layer (i.e. from the ground to the top of the logarithmic layer) and the outer-layer (i.e. from the top of the inner layer to top of the boundary layer) scalings were examined for an urban boundary layer using numerical simulations. The simulations consider a developing neutral boundary layer over realistic building geometry with and without a slightly upsloping terrain. The computational domain covers an 19.2 km by 4.8 km and extends up to a height of 1 km, and is resolved by 2-m grids. Several turbulence intensity profiles are defined locally in the computational domain. The inner- and outer-layer scalings work well reducing the scatter of the turbulence intensity within the inner- and outer-layers, respectively, regardless of the surface geometry. Although the main scatters among the scaled profiles are attributed to the mismatch of the parts of the layer (i.e. inner or outer) and the scaling parameters, their behaviours can also be explained by introducing a non-dimensional parameter which consists of the ratio of the inner- and outer-layer parameters for length (the boundary-layer height over the roughness length), or velocity (the external free stream velocity over the friction velocity).

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Heavy precipitation in Japan is caused by various phenomena, such as tropical cyclones and the Baiu front, and shows regional-scale variation. Here we investigate extremely heavy precipitation events exceeding the 100-year return period in the Kanto area and future projections of such events using large ensemble climate simulations for periods of several thousand years. To understand these extreme events, associated sea level pressure anomalies over Japan and the surrounding region are classified into four clusters. These cluster means are characterized by (1) a strong anomalous cyclone, (2) a weak anomalous cyclone, (3) an anomalous cyclone accompanied by an anomalous anticyclone to the north, and (4) an anomalous anticyclone to the north. The cluster with a strong anomalous cyclone is accompanied by widely distributed heavy precipitation, and its area-averaged precipitation is predicted to be more enhanced under global warming than that of other clusters, partly because of an increase in the strength of strong tropical cyclones approaching Kanto. The cluster dominated by an anomalous anticyclone is characterized by localized heavy precipitation in the plains area. The relative frequency of this cluster will increase, whereas that of other clusters will decrease under global warming.

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The Non-Hydrostatic Regional Climate Model (NHRCM) was used in simulating the present and future rainfall climate over Malaysia under the RCP8.5 scenario in this study. Simulation and projection from 1979 to 2002 for present day and 2070 to 2100 for the end of century were conducted over the Malaysia. The 20 km resolution MRI-AGCM3.2 model simulation from Meteorological Research Institute (MRI) was used as boundary conditions. The objective of this study was to estimate the extreme rainfall projections in Malaysia at 5 km of resolution during the November to February period, representing the northeast monsoon season. Overall, the model was capable to simulate the historical rainfall climatology and distribution, but model tended to underestimate high rainfall frequency and mean rainfall intensity in Malaysia. However, compared with simulations at 25 km, added values have been shown at 5 km resolution. Based on the NHRCM05 simulations, a number of hotspots have been identified with significant projected increases up to 80% for the extreme rainfall indices (R20mm, RX1day, R95pTOT and R99pTOT), 30% increases in mean rainfall intensity (SDII) and 20% for consecutive dry days indices (CDD).

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In this study, based on the daily maximum wind speed and maximum instantaneous wind speed data recorded at 61 observation points operated by the Korea Meteorological Administration from 1993 to 2018, the self-organizing map clustering method was used to classify regions with similar characteristics of strong wind and gust wind occurrence and intensity. Characteristics of these regions were analyzed by averaging 30 variables related to wind for each cluster. As a result, 13 homogeneous regions of strong wind and gust wind in Korea were identified, which were clearly divided into regions of high and low strong wind frequency of occurrences. In most regions, the average daily maximum wind speed and maximum instantaneous wind speed were high in spring and winter. However, the average daily maximum wind speed and maximum instantaneous wind speed exceeding the criteria of strong wind (14 m s⁻¹) and gust wind (20 m s⁻¹) in this study were high in summer and autumn. Among the four clusters with high occurrence of strong wind and gust wind, one was classified as a specific region with high occurrence in summer and autumn. This results are likely to be beneficial to support regional customized special weather reports and disaster prevention.

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One way of the tropical cyclone (TC) initialization is assimilating the official advisory sea-level pressure observation to specify the initial structures of a TC with the aid of a background error covariance (BEC). In the hybrid four dimensional ensemble-variational data assimilation system, a static BEC explains the geostrophic and cyclostrophic wind-mass balance, and an ensemble BEC expresses the flow-dependent feature. Assimilation of the minimum sea-level pressure using a larger localization length-scale with limited ensemble members yields the closest to the observations at the initial state, but an imbalance in the broad analysis increment distorts geopotential and wind fields. Moreover, the reduced central pressure of TC is rapidly returned to an intensity that a model resolution can represent during the prediction. We introduce the application of final-scale localization (FSL) at the last outer loop with the shortest one to improve the TC initialization. With the aid of FSL, we may conduct the shorter localization length-scale, especially adopted for the TC initialization. As preliminary results, both analysis and prediction become more stable and the large-scale environments are preserved better than in the control experiment.

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This study investigated the remote impact of an increase in latent heat flux (LHF) over the Kuroshio on tropical cyclone (TC) development, using a cloud-resolving model. A control run and a sensitivity experiment with Kuroshio's LHF artificially enhanced were performed for Typhoon Chaba in 2010. The TC development simulated in the sensitivity experiment was suppressed as compared with the control run. The sensitivity experiment demonstrated that eyewall convection and the associated TC secondary circulation were suppressed by a decrease in equivalent potential temperature (θ_e) around the eyewall through the lower θ_e penetration into the inner core region in the boundary layer. The dynamic features of the TC were also altered by the attenuated TC secondary circulation through the inhibition of the inward advection of the absolute angular momentum. The super-gradient tangential velocities in the inner core were smaller than those in the control run. Such thermodynamic and dynamic changes were remotely induced by the decrease in moisture import from the Kuroshio. Since the increased LHF facilitated the development of a surface low over the Kuroshio, the intensified low further accumulated the Kuroshio's vapor and suppressed low-level northeasterlies toward the TC, resulting in interrupting the moisture import into the TC.

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Although wetlands are the largest natural source of atmospheric methane, the amount and variability of methane emissions from wetlands still have large uncertainty. We investigated the local growth rate of the column-averaged methane dry air mole fraction (XCH₄) in Siberia where wetlands are widely abundant using 11-year (2009-2019) Greenhouse gases Observing SATellite (GOSAT) data. While the mean growth rate during the summer from the GOSAT observations is 7.2 ppb yr⁻¹ globally, that in West Siberia is 8.4 ppb yr⁻¹. In particular, the growth rates in West Siberia after 2013 is much larger in July and August than in the other months. Moreover, the growth of XCH₄ in West Siberia appears to larger than in the other boreal areas. These results imply that methane emissions from wetlands in West Siberia increased during the summer in recent several years.

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To discuss the feasibility of the Himawari follow-on program, impacts of a hyperspectral sounder on a geostationary satellite (GeoHSS) is assessed using an observing system simulation experiment. Hypothetical GeoHSS observations are simulated by using an accurate reanalysis dataset for a heavy rainfall event in western Japan in 2018. The global data assimilation experiment demonstrates that the assimilation of clear-sky radiances of the GeoHSS improves the forecasts of the representative meteorological field and slightly reduces the typhoon position error. The regional data assimilation experiment shows that assimilating temperature and relative humidity profiles derived from the GeoHSS improves the heavy rainfall in the Chugoku region of western Japan as a result of enhanced southwesterly moisture flow off the northwestern coast of the Kyushu Island. These results suggest that the GeoHSS provides valuable information on frequently available vertically resolved temperature and humidity and thus improves the forecasts of severe events.

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This study investigated rainfall trends and their associations with tropical cyclones (TCs) during the period of 1979-2019, using TC best-track data from the Regional Specialized Meteorological Center Tokyo - Typhoon Center and daily rainfall data from 138 meteorological stations in Vietnam. The radius of influence of TCs on local rainfall was limited to 500 km from TC centers. The average annual number of TCs affecting Vietnam has decreased slightly in the last two decades compared to previous decades. The ratio of TC-induced rainfall to total rainfall attained the highest value of 37.3% in the central region, in July. The temporal distribution of TC-induced rainfall coincided with the frequency of TCs, with an active period from June to November. During 1979-2019, the non-TC rainfall was the main contributor to the change in total rainfall, especially in relation to the decline in the north and the increase in the coastal South Central region. The rainfall trend during the entire period was principally explained by the interdecadal shift in the late 1990s. Rainfall intensity and the number of heavy rainfall days were intensified for total rainfall and non-TC rainfall, indicating that TCs contributed minimally to the changes of extreme rainfall events during 1979-2019.

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Japan underwent a nationwide self-restraint of human activities in spring 2020 to prevent the spread of the COVID-19 infection. In order to evaluate the effect of suppressed human activities on temperature in the Tokyo Metropolitan area, a statistical analysis was made for temperature anomalies during the self-restraint period using hourly data on the AMeDAS network. The temperature anomaly was defined by the departure from the value that would have been observed without self-restraint, estimated from regression analysis for temperatures at surrounding non-urban stations. It was found that the temperature in central Tokyo (Kitanomaru Park) had a negative anomaly of −0.49°C with a 95% confidence range of ±0.19°C on the average over the strong self-restraint period from April to May. The anomaly was larger in the nighttime than in the daytime, and was found in an area spreading for several tens of kilometers, with a decreasing magnitude according to the distance from Tokyo. These facts indicate a possibility that the reduction of anthropogenic heat release during the self-restraint period resulted in substantial decrease of temperature in the Tokyo Metropolitan area.

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Strong winds are one of the several factors contributing to natural disasters. Although in recent years, the intensity and frequency of strong winds has decreased, different areas are differently affected by such winds; these winds still have the potential to cause adverse impacts on life and property. In Korea, strong winds are also responsible for the incidence of increased number of accidents and forest fires. Therefore, in this study, relationship between wind speed and damage was analyzed, and the threshold value of damage-causing wind speed was estimated. We first analyzed the relationship between wind speed and damage occurrences based on the daily maximum wind speed and daily maximum instantaneous wind speed data, and data on damage related to strong winds. Second, we examined the validity regarding the regional segmentation of the Korean criteria of special weather report for strong winds using the critical success index and cumulative percentile distributions to estimate the damage-causing threshold value for each region. We found that damage resulting from very strong wind speeds in Korea had not occurred in recent times. In addition, considerable damage had occurred because of low-speed wind compared to the current criteria for high wind advisory. However, the incidence of damage was higher when wind speed was stronger than the current criteria for high wind advisory. Based on threshold estimation, the study areas were categorized into areas with high threshold values (coastal, mountainous, and island), and those with low threshold values (inland areas). A notable difference was observed between the threshold values of the two categories of areas. This necessitated the regional segmentation of the criteria of special weather report on strong winds.

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Aircraft observations were conducted over the eastern mountainous areas of the United Arab Emirates (UAE) in September 2017 to characterize the microphysical properties of diurnal convective clouds. Aerosol particle and cloud condensation nuclei (CCN) measurements indicate that the air mass had a continental nature, resulting in high cloud droplet concentrations of 600-800 cm⁻³. Two case studies were undertaken to obtain the vertical profiles of hydrometeors up to the cloud top. The ice particle number concentrations in the updraft core were a few particles L⁻¹, which is similar to the primary ice nucleating particle (INP) number concentrations estimated from immersion freezing of high concentration dust particles in the convectively mixed boundary layer. The ice particle number concentrations were several tens of particles L⁻¹ outside the updraft core in the upper levels. INP measurements and the observed cloud microphysical structure suggest that drizzles, frozen via the immersion freezing nucleation of dust particles, formed graupel embryos and ice particles, with concentrations of one to two orders of magnitude greater than those of the primary INPs, which may be generated via secondary ice production and/or ice particle accumulation from primary ice nucleation in clouds with relatively warm cloud top temperatures (approximately −12°C).

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The thermal stress along a marathon course in Tokyo is evaluated using a radiation balance model. The wet-bulb globe temperatures (WBGTs) for runners and spectators are calculated based on the surrounding building and tree geometries using the Solar LongWave Environmental Irradiance Geometry model. Analysis is conducted in terms of summer days in August 2018, which was during the hottest summer in the past 5 years. The WBGT classification for runners along the outward leg (until around 14 km) reaches the “Warning” level (WBGT = 26.5°C) despite of the many shadows on the street in the early morning (until 0645 JST). The WBGT increases around the Imperial Palace because the road has a sky view factor of over 95%, and no obstacles to make shadows on the street at around 0750 JST. The WBGT classification for runners reaches the level of “Severe warning”. For spectators, the difference of average WBGT from the runners are about 0.1°C although the difference could be significant locally due to partial shading on a road side.

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Heavy rainfalls often occur when a tropical cyclone (TC) exists on the sea off the south coast. These pre-typhoon rainfalls (PRE) is associated with the northward moisture transport ahead of the TC. In this paper, we examine the northward moisture transport by the ageostrophic winds associated with typhoon T0918 (Melor) and its impact on PRE. According to a numerical simulation conducted in the previous study (Saito 2019), we analyzed the northward moisture fluxes by reproduced geostrophic and ageostrophic winds. Although the southerly ageostrophic winds are dominant mainly in the upper levels, the ageostrophic winds contribute to enhance the poleward water vapor transport for the upper and middle levels above 3 km.

To see the impact of the ageostrophic moisture transport on PRE, we conducted a sensitivity experiment where the model moisture in middle and upper levels over the sea off the south coast of western Japan was reduced. Precipitation over western Japan was decreased about 30% when the contributions in moisture fluxes by ageostrophic winds were removed. This result suggests that the northward ageostrophic winds associated with a TC enhance PRE by moistening the middle and upper atmosphere.

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This study investigated the impact of sea surface temperature (SST) on a snowfall event of late January 2018 on Kanto, Honshu, Japan, associated with an extratropical cyclone (south-coast cyclone) along the Pacific side, during the Kuroshio large meandering period by a regional atmospheric model. We addressed SST impacts on the snowfall event under almost the same synoptic-scale conditions, such as extratropical cyclone, in a framework of lateral boundary forcing. We conducted control experiments (KLM) with SST of the Kuroshio large meandering, and sensitivity experiments (NKLM) prescribed non-Kuroshio large meandering SSTs. Observational results showed that SST anomalies south of Tokai, and east of northern Kanto and Tohoku could be candidates to modify a snowfall event. As simulated results, timings of snowfall and precipitation associated with the extratropical cyclone was reproduced. Unlike what has been suggested, the SST impact south of Tokai on snowfall was not clear. However, the SST east of northern Kanto and Tohoku showed a significant impact. This impact was explained by southward advection of modified air-mass from east of northern Kanto and Tohoku. Additional sensitivity experiments supported this result. This study implies the importance of the SST anomaly east of northern Kanto and Tohoku for snowfall in Tokyo.

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Since March 2012, multi-year ground-based observation of atmospheric aerosol particles has been carried out in Tsukuba, Japan to characterize the aerosol particle number concentrations (NCs), air mass origin relevance, and specifically, their cloud condensation nuclei (CCN) and ice nucleating particle (INP) characteristics. The CCN NCs at any water supersaturation (SS) exhibit strong seasonality, being higher in winter and lower in summer; this pattern is similar in the polluted urban environment in East Asia and contrary to that in the Pacific coastal region. The hygroscopicity (κ) is generally high in early autumn and low in early summer, likely due to the seasonal difference of synoptic-scale systems. In contrast, the INP NCs and ice nucleation active surface site density (n_s) at defined temperature (−15 to −35°C) and SS (0%-5%) lack clear seasonal influence. The average INP NCs and n_s in this study were comparable at warmer temperatures and approximately one order of magnitude lower at colder temperatures, compared with those in other urban locations under limited dust impact. Moreover, the n_s values were one to four orders of magnitude lower and exhibited weaker temperature dependence than previous parameterizations on mineral dust particles.

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We quantified the global bromine- and iodine-mediated tropospheric ozone loss using global chemical transport model simulations. We tested three datasets of very short-lived substances (VSLS) emissions, three datasets of sea surface iodide concentrations, and an explicit representation of the effects of multi-phase reactions at the air-sea boundary on dry deposition. We then determined optimal model settings based on the evaluation using the ship-borne and aircraft-campaign observations over the ocean. Our evaluation suggested that the explicit representation of multi-phase reaction effects substantially reduced model biases of ozone in the lower troposphere (up to 11%). Moreover, the impacts of using different datasets of VSLS emissions and sea-surface iodide concentrations were relatively small. The global bromine- and iodine-mediated chemical ozone losses were estimated to account for 4% and 17% of the total chemical loss, respectively, while the global iodine-mediated dry deposition loss of ozone was estimated to account for 22% of the global total dry deposition. These bromine- and iodine-mediated ozone losses decreased surface ozone concentrations over the ocean by 10% and 23%, respectively. The observational constraint on model simulations made by this study supports that bromine and iodine substantially impact global tropospheric ozone through atmospheric chemical reactions and dry deposition processes.

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Aerosol effects on deep convective cloud (DCC) have been recognized as one of the complex subjects in climatic studies because of the difficulty in quantifying the sole effect of aerosols on DCC. The complexity further arises if the atmosphere has very strong temporal and spatial variations such as that of Indo-Pacific Warm Pool (IPWP) region. Considering the strong influence of IPWP region on global climate change and water circulation, we investigated aerosol effects on DCC over this region by using data of 2015-2016 El Niño and the 2017-2018 La Niña events. We developed a spectral analysis based framework to identify and decouple the influences of major external factors on aerosol-DCC relationship. We found that temporal variations of aerosols, clouds, and meteorology longer than 2 days' time scale can have larger influences than their diurnal and spatial variations on aerosol-DCC relationship. By removing the effects of those spatial and temporal variations of different scales, the study suggests that aerosols of IPWP region can affect DCC properties with time lags less than ∼5 hours and by increasing cloud-top height, cloud coverage, and DCC number concentration with the increase of aerosols.

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Synoptic circulation patterns associated with heavy snowfall events in Sapporo are examined using large ensemble simulation with 60-km global climate experiments. For snowfall, a 5-km dynamically downscaled model from the 20-km regional simulation is utilized. To identify synoptic circulation patterns, self-organizing maps (SOMs) are applied, and their response to a warming climate is examined. The authors find that heavy snow events predominantly occur due to low pressure anomalies to the north/east of Hokkaido or over central Japan, and by high pressure anomalies over the Siberian continent. The 4 K warming climate shows robust decreases in heavy snowfall amounts associated with low pressure anomalies over central Japan and increases in heavy snowfall amounts under patterns with high pressure anomalies over Siberia. This is attributed to surface air temperature characteristics in future climates, as precipitation in the former with surface winds transporting warm, moist air from the south and east, develops predominantly above 0°C in the +4 K climate, while the latter, often resulting in intense snow band events, continues to be dominated by temperatures near or below zero.

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The apparent hydrological sensitivity, defined as the global-mean precipitation change per increase of the global-mean temperature, is investigated for scenarios induced by different forcing agents. Simulations with a climate model driven individually by four different climate forcers, i.e. sulfate, black carbon, solar insolation and carbon dioxide (CO₂), are analyzed in the context of energy balance controls on global precipitation to explore how different forcing agents perturb different energy components grouped into fast and slow responses. Similarities and differences among the forcing agents are found in ingredients of the tendency contributing to the hydrological sensitivity from various energy budget components. Specifically, the sulfate and solar forcings induce the hydrological sensitivity of ∼2.5%K⁻¹ due to the slow response of radiative cooling whereas the black carbon induces a significantly negative hydrological sensitivity (∼−6.0%K⁻¹) due to the strong atmospheric heating. The CO₂-induced hydrological sensitivity is found in between (∼1.2%K⁻¹) as a result from the slow response of radiative cooling and its partial compensation by the atmospheric heating. The findings provide a quantitative basis for interpreting climatic changes of global precipitation driven by a mixture of various natural and anthropogenic forcings.

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This paper describes a simple snow-cover model (SSCM) that was developed primarily to evaluate the hazard to traffic posed by snow avalanches. The SSCM requires only air temperature and precipitation or snow depth as input data, and we simplified the physical processes that affect the snowpack in the model. Snow pit observations and the calculation for avalanche cases were carried out to verify the SSCM output. The SSCM was able to reproduce the change in the snowpack properties fairly well. Further, the snow stability index, which shows the ratio of shear strength to shear stress in the snow, indicated that the SSCM can be used to provide a reliable estimate of avalanche hazard.

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Array weather radar (AWR), a kind of distributed phased array radar, includes at least three Phased Array Front Ends (PAFE). Every three PAFEs are grouped for synchronous scanning to ensure that the Data Time Difference (DTD) at the same point in the fine detection area is less than 2 s. This paper adopts the multiple-Doppler wind synthesis method to synthesize the wind field of the small-DTD AWR data and discusses the sensitivity analysis on the wind fields under the different DTDs. The analysis experiment includes the wind fields under two types of precipitation systems. One is a convective precipitation system with unstable airflow, and the other is a non-convective precipitation system with stable airflow. The statistical analysis showed that, due to the advection effect and intrinsic evolution of the precipitation systems, the bigger the DTD is, the bigger the wind field error is. When the DTD is greater than 24 s, the wind field obtained by the convective precipitation system has more errors. When the DTD is greater than 84 s, the wind field obtained by the non-convective precipitation system has more errors.

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Based on the drought severity index (DSI), which is derived from the ratio of evapotranspiration (ET) to potential evapotranspiration (PET) and normalized difference vegetation index (NDVI), as measured by remote sensing, we replaced the ET/PET ratio with soil moisture (0-10 cm) to establish an improved index (IDSI) and evaluated the drought situation in Inner Mongolia. The two components in IDSI are independently derived; however, the effects of evapotranspiration are contained in the soil moisture, and even precipitation changes could be reflected. We used monthly IDSI data for Inner Mongolia to evaluate drought throughout the growing season (May–September) during 2001-2010. The IDSI showed that 2001, 2007, and 2009 were years with significant drought. Areas that experienced extreme drought were less extensive than those found by the DSI because we removed the ET/PET component, which already contains the effects of the NDVI. IDSI results not only contained the degree of precipitation change for a given month through soil moisture, but also reflected the influence of water and heat in the previous month through the NDVI. Moreover, IDSI results were generally consistent with agricultural drought disaster records.

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An extreme rainfall event brought precipitation amounts exceeding 1000 mm in Kyushu district, southwestern Japan, in early July 2020. Especially, an elongated and stagnated mesoscale convective system formed around the Kuma River in central Kyushu district produced localized heavy rainfall with precipitation amounts larger than 600 mm in 13 hours. Characteristics of this extreme rainfall event were investigated using distributions of radar/raingauge-analyzed precipitation amounts (RAP) and statistically compared with those during the warm seasons (April–November) in 2009-2019. The results are shown as follows; (1) nine heavy rainfall areas of linear-stationary type (LS-HRAs) were extracted, (2) spatial and temporal scales of two LS-HRAs among them respectively exceeded 270 km and 10 hours, (3) the maximum RAP exceeding 100 mm in LS-HRAs were comparable to those in previous extreme rainfall events, (4) large accumulated three-hour precipitation amounts exceeding 200 mm were more frequently observed than those in the previous events, and (5) the accumulated five-day precipitation amount integrated around Kyushu Island was the largest since 2009. This study also showed that the large area-integrated precipitation amount was produced mainly from widespread precipitation systems associated with the Baiu front, while the nine LS-HRAs significantly contributed localized heavy rainfall.

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A system with existing snowfall sensors, which is used to control the operation of the sprinkler snow removal system, was developed to acquire data that can be used to generate snowfall distribution with high spatiotemporal resolution. This had advantages such as low installation and management costs, as well as flexibility with respect to the configuration of its observation points. The results confirmed that this system, developed for experimental purposes in Nagaoka City (Niigata Prefecture), made it possible to generate the snowfall amount distribution as well as the precipitation rate within a 25 km × 30 km area at 10-min intervals based on in-situ measurements conducted at 16 ground-based points. A comparison of the system with other observation systems confirmed that it could detect detailed spatial snowfall variations, which could not be achieved using existing the ground-based observation networks, and provide sufficient observation accuracy for winter road management. Since many snowfall sensors are installed on the Sea of Japan side of mainland of Japan, this system has the potential for extensive application in the snowy areas of Japan characterized by heavy snowfall at temperatures of approximately 0°C.

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