The September 2015 Kanto-Tohoku heavy rainfall event occurred in a stationary linear convective system between Typhoons Kilo and Etau. We investigated the influence of sea surface temperature (SST) on the local heavy rainfall event using a regional air-sea strongly coupled data assimilation system based on the local ensemble transform Kalman filter (LETKF) and a nonhydrostatic atmosphere model (NHM) coupled with an ocean-surface wave model and a multilayer ocean model with an Advanced Microwave Scanning Radiometer 2 (AMSR2) level 2 (L2) SST product. From the validation of SST analyzed by the coupled data assimilation system with the Japanese geostationary multi-functional transport satellite 2 hourly SST product and in-situ observations at a moored buoy, we demonstrated that the coupled system with the AMSR2 L2 SST led to an improvement in the SST analysis. Based on the verification using radiosonde observations and radar-rain gauge rainfall analysis, the analysis of the lower-atmospheric components was improved by the air-sea coupled NHM-LETKF.

 The local torrential rainfall event that occurred around 37°N in the Tochigi prefecture was embedded in a stationary linear convective system. The location of the linear convective system corresponded to the synoptic-scale convergence area between the cyclonic circulation associated with Etau and easterly lower-tropospheric winds. Strong southerly winds associated with Etau caused a periodic enhancement of local convection along the convergence area on the upwind side of the linear convective system and resulted in a wave-like train of the total water content around an altitude of 4-8 km on the leeward side. The improvement of SST analysis could not only change the transition of Etau to the extratropical cyclone but also the lower-tropospheric wind field and thereby the location of the stationary linear convective system with embedded local torrential rain.

 Hurricane Joaquin, a notable hurricane that occurred over the Atlantic Ocean in 2015, is studied with an emphasis on its unique hairpin turn that occurred between 2100 UTC 1 October and 0600 UTC 2 October 2015. A series of mesoscale high-resolution numerical simulations are performed with an advanced research version of the Weather Research and Forecasting (WRF) model. The sensitivity of numerical simulations to different cumulus, boundary layer, and microphysical parameterization schemes is examined to investigate the most relevant processes influencing the track evolution of Hurricane Joaquin. It was found that the numerical simulation of Hurricane Joaquin's track is highly sensitive to the choice of cumulus scheme. Large-scale environmental conditions and hurricane inner-core structures are diagnosed. The results indicated that middle- to upper-level steering flows are crucial in influencing Joaquin's track. Further investigation of the large-scale environment (middle- and upper-level trough, blocking high, thermal distribution, etc.) shows that middle-level blocking high plays an important role in Joaquin's movement. The structure of the hurricane core region, including the vertical extent of diabatic heating, vertical velocity, and relative humidity, could also play an important role. Specifically, the asymmetry and local absolute vorticity tendency over the inner-core region and its vicinity have a strong implication for Joaquin's hairpin turn.

 Aluminum oxide (Al₂O₃) and iron oxide (Fe₂O₃) particles have been observed not only in industrial areas and their surroundings, but also in natural atmospheric environments. These types of aerosols can influence aerosol–cloud interactions. In this study, physicochemical properties such as size distribution and the ability to act as cloud condensation nuclei (CCN) as well as ice nucleating particles (INPs) of surrogates of ambient Al₂O₃ and Fe₂O₃ particles were investigated using a CCN counter, the Meteorological Research Institute's (MRI) cloud simulation chamber, the MRI's continuous-flow-diffusion-chamber-type ice nucleus counter (CFDC-type INC), and an array of aerosol instruments. The results indicated that their hygroscopicity parameter (κ-value) ranged from 0.01 to 0.03. This range is compatible with that of surrogates of mineral dust particles and is smaller than typical κ-values of atmospheric aerosols. On the other hand, based on their ice nucleation active surface site (INAS) densities, these materials may act as effective INPs via immersion freezing (i.e., ice nucleation triggered by particles immersed in water droplets). In the cloud chamber experiments, Al₂O₃ and Fe₂O₃ particles continuously nucleated ice crystals at temperatures below −14°C and −20°C, respectively. This result indicates that the Al₂O₃ particles were better INPs than the Fe₂O₃ particles were. Moreover, the INAS density of the Al₂O₃ particles was comparable to that of natural ambient dust.

 In the summer of 2016, 14 cases of jumping cirrus (JC) were observed around the Kanto region in Japan by ground-based, visible-light cameras. The cameras were set at the summit of Mt. Fuji and National Defense Academy (Kanagawa, Japan), and 15-second time-lapse photography was continually taken for the period. The location and spatial scale of the JC were calculated by measurements using the photometry of background stars in the nighttime and the geostationary meteorological satellite Himawari-8 infrared imagery. The environmental conditions of the JC were also investigated using radiosonde and Himawari-8 visible and infrared measurements. Comparing our cases to the JC in the United States of America (USA) reproduced by a three-dimensional, non-hydrostatic cloud model from previous studies, their motions, morphology, spatial and temporal scales showed similarities, although the horizontal scale of the JC and the magnitude of the underlying convection was relatively smaller in our cases. The sounding by the radiosonde in the vicinity of the storms showed that 3 of the 14 cases reached the stratosphere. However, the hydration of the lower stratosphere was not supported by analysis of the brightness temperature difference (BTD) between 6.2 and 10.4 μm measured by Himawari-8. The averaged wind shear across the range of the jumping heights above the anvil was −1.1 m s⁻¹ km⁻¹. The maximum value of the convective available potential energy (CAPE) of the 14 cases was 1384 J kg⁻¹, which is several times smaller than those of the thunderstorm cases observed in the USA in previous numerical JC studies. This indicates that JC occurs from the cumulonimbus anvil top even if the convection is relatively weak. The motion of JC observed by visible-light cameras shows that it can transport moisture above the tops of the anvils of convective clouds regardless of its altitude as cloud ice appears to be sublimated.

 An investigation has been carried out using rainfall observation data, an analysis and forecast data by National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) to explain the environment and processes that lead to heavy rainfall in the early morning over the Korean peninsula during episodes of cloud clusters associated with mesoscale troughs (CCMTs). For this study, nine episodes with a maximum hourly rainfall amount in the early morning (i.e., 0300-0900 LST) are selected from seventeen heavy-rainfall episodes associated with CCMTs during 2001-2011. Case studies on two episodes have revealed that, for both episodes, 1) a low-level trough develops over eastern China and its coastal area during day time; 2) the strong southwesterly band (SWB; an area with wind speeds > 12.5 m s⁻¹) on the pressure level of 925 hPa over the East China Sea, which is located southeast of the trough, strengthens and expands at night time toward the southwestern Korean peninsula; 3) the SWB supplies a large amount of moisture and increases convective instability over the southwestern Korean peninsula with a convection trigger mechanism (i.e., strong horizontal convergence); and 4) heavy rainfall occurs in the early morning over the southwestern Korean peninsula, where the exit region of the SWB is located. A mechanism for the SWB growth is presented. Furthermore, generality of the major results from the two case studies is verified using the results obtained for the composite fields of the nine CCMT episodes.

 For several decades, the interaction between the troposphere and the stratosphere has attracted the attention of climate scientists, not least for the benefit it has on understanding dynamical processes and predictability. This interaction has been revived recently in regard to downward disturbance propagation effects on tropospheric circulations. In the current study, we investigate such interactions over the North Atlantic region in relation to the eddy-driven jet stream. The atmospheric low-frequency variability in the winter over the North Atlantic sector is mainly associated with variations in the latitudinal positions of the North Atlantic eddy-driven jet stream. The Japanese Reanalysis JRA-55 data has been used to analyze the jet latitude statistics. The results reveal robust trimodality of the North Atlantic jet reflecting the latitudinal (i.e., northern, central and southern) positions in agreement with other reanalysis products. 30 major Sudden Stratospheric Warming (SSW) events are analyzed in relation to the three modes or regimes of the eddy-driven jet. The frequency of occurrence of the eddy-driven jet to be in a specific latitudinal position is largely related to the wave amplitude. The stratospheric polar vortex experiences significant changes via upward wave propagation associated with the jet positions. It is found that when the jet is close to its central mode the wave propagation of zonal wave number 2 (WN2) from the troposphere to the stratosphere is significantly high. Eliassen-Palm (EP) fluxes from all waves and zonal wave number 1 (WN1) depict the deceleration of the stratospheric polar vortex for the eddy-driven jet with a latitudinal position close to the northern mode. Plumb wave activity variations originate mainly in the Atlantic sector depending on the North Atlantic eddy-driven jet states. These significant associations between preferred latitudinal positions of the North Atlantic eddy-driven jet and the stratospheric dynamics may be a source of predictability.

 Most studies have focused on variations of tropical cyclone (TC) frequency, intensity, and track over the western North Pacific (WNP), but variability of WNP TC season onset date (TCSO) has been less studied. Recent research has indicated a close association between WNP TCSO and sea surface temperature (SST) over the tropical Indian Ocean and the tropical central-eastern Pacific. This study has found that relationship between TCSO and SST underwent an inter-decadal change in the late 1990s, likely due to a climate shift that occurred around that time. An observed significant correlation between TCSO and SST before the late 1990s has been insignificant since that time. This was confirmed by the fact that El Niño Southern Oscillation (ENSO) at 0.46 positively correlates with TCSO from 1965-1999 (significant at the 95 % level), and the correlation becomes insignificant (0.16) during 1998-2016. Further analysis suggests that the close association between TCSO and SST is robust only for major El Niño events, with consistently extreme late TCSO following major El Niños during the satellite era. Accompanying the decay of major El Niños, tropical equatorial easterly anomalies in the WNP are driven by a Matsuno–Gill-type response to the specific SST anomaly pattern over the tropical Indo–Pacific sector. This in turn induces an anomalous anticyclone, anomalous westerly vertical wind shear, reduced mid-level moisture and suppressed convection over the WNP basin—all of which are unfavorable for WNP TCs, resulting in delayed TCSO following major El Niño events. These inter-decadal changes in the inter-annual correlation between TCSO and ENSO are largely due to the changing influence of moderate El Niño events on TCSO before and after the late 1990s. This study improves understanding of the ENSO–TC relationship, which should aid seasonal outlooks of WNP TC activity.

 We introduce a novel rainfall-estimating algorithm with a random-forest machine-learning method only from Infrared (IR) observations. As training data, we use nine-band brightness temperature (BT) observations, obtained from IR radiometers, on the third-generation geostationary meteorological satellite (GEO) Himawari-8 and precipitation radar observations from the Global Precipitation Measurement core observatory. The Himawari-8 Rainfall-estimating Algorithm (HRA) enables us to estimate the rain rate with high spatial and temporal resolution (i.e., 0.04° every 10 min), covering the entire Himawari-8 observation area (i.e., 85°E-155°W, 60°S-60°N) based solely on satellite observations. We conducted a case analysis of the Kanto–Tohoku heavy rainfall event to compare HRA rainfall estimates with the near-real-time version of the Global Satellite Mapping of Precipitation (GSMaP_NRT), which combines global rainfall estimation products with microwave and IR BT observations obtained from satellites. In this case, HRA could estimate heavy rainfall from warm-type precipitating clouds. The GSMaP_NRT could not estimate heavy rainfall when microwave satellites were unavailable. Further, a statistical analysis showed that the warm-type heavy rain seen in the Asian monsoon region occurred frequently when there were small BT differences between the 6.9-μm and 7.3-μm of water vapor (WV) bands (ΔT6.9-7.3). Himawari-8 is the first GEO to include the 6.9-μm band, which is sensitive to middle-to-upper tropospheric WV. An analysis of the WV multibands' weighting functions revealed that ΔT6.9-7.3 became small when the WV amount in the middle-to-upper troposphere was small and there were optically thick clouds with the cloud top near the middle troposphere. Statistical analyses during boreal summer (August and September 2015 and July 2016) and boreal winter (December 2015 and January and February 2016) indicate that HRA has higher estimation accuracy for heavy rain from warm-type precipitating clouds than a conventional rain estimation method based on only one IR band.

 Geographic and meteorological characteristics of 479 tropical cyclones (TCs) in a study domain in the Southwest Pacific (defined by 135°E-120°W and 5-65°S) over the past 48 TC seasons, from 1969-1970 to 2016-2017, were examined using the latest Southwest Pacific Enhanced Archive of TCs dataset. Examined metrics include the TCs' geographic distributions, numbers, intensities, length in days (TC days), accumulated cyclone energy (ACE), and power dissipation index (PDI). The results show increasing TC activities in the western, northwestern, northern, and central subdomains of the nine subdomains in the study domain. The average latitudes of TC genesis and maximum intensity remained almost unchanged. Most TCs took southward to southeastward paths, and most attained their maximum intensities in the western and central parts of the study domain. The annual number of TCs and TC days decreased over the study period, while the numbers of stronger TCs slightly increased, and stronger TC days increased. The highest annual lifetime-maximum intensity and average annual lifetime-maximum intensity also increased. The highest annual maximum intensification rates did not change much over the study period, nor did ACE and PDI. The results show correlations between the highest annual lifetime-maximum intensity and average sea surface temperature (SST) variations, as well as correlations between TC days and average SST variations in the region.

 Two sets of decadal prediction experiments were performed with Beijing Climate Center climate system model version 1.1 (BCC-CSM1.1) with different initialization strategies. One experiment is relaxing modeled ocean temperature to the Simple Ocean Data Assimilation (SODA) reanalysis data (SODAInit). In the other (EnOI_HadInit) experiment, the modeled ocean temperature were relaxed toward the assimilated ocean data, which were generated by assimilating sea surface temperature (SST) of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) data to the ocean model of BCC-CSM1.1 using Ensemble Optimum Interpolation (EnOI) method. Comparisons between EnOI_HadInit and SODAInit hindcasts show that EnOI_HadInit is more skillful in predicting SST over the North Pacific, the southern Indian Ocean, and the North Atlantic. Improved prediction skill is also found for surface air temperature (SAT) over South Europe, North Africa, and Greenland, which is associated with the skillful prediction of the Atlantic multi-decadal oscillation in EnOI_HadInit. EnOI_HadInit and SODAInit are both skillful in predicting East Asian SAT, which is related to their skillful predictions of the tropical western Pacific SST. The result indicates that assimilated data generated by the ocean model of BCC-CSM1.1 with EnOI assimilation provide better initial conditions than SODA reanalysis data for the decadal predictions of BCC-CSM1.1.

 The properties of tropical convection are evaluated using one-month long simulation datasets produced by the non-hydrostatic icosahedral atmospheric model (NICAM) using 3.5-, 7-, and 14-km horizontal meshes with identical cloud-microphysics configurations. The simulations are targeted on the 2nd Madden-Julian oscillation (MJO) event observed in the CINDY2011/DYNAMO field campaign. An increase in high cloud fraction at 200 hPa level and a reduction in surface precipitation occur as the horizontal resolution increases, corresponding to the reduction in precipitation efficiency due to the shorter residence time inside stronger updrafts that occur at the higher resolution. The increase in high cloud fraction is followed by the warming of the troposphere, which results in an increase in the column water vapor and an elevation in the freezing level. The total water condensation is decreased at higher resolutions, which is likely due to a balance with the decreased outgoing longwave radiation (OLR). The reproduced MJOs, which accounted for a large portion of the tropical convections, were similar in the 3.5-km and 14-km simulations in terms of eastward propagation speeds and structures, including the characteristic westward tilt of the moisture anomaly with height. However, the amplitude of the anomalous MJO circulation was considerably smaller in the 3.5-km simulation. The robust resolution dependence and the interpretations presented in this study underline the necessity for a resolution-aware cloud-microphysics optimization method that will have value in the coming era of global cloud-resolving simulations.

 Future changes in the climatological distribution of clear-air turbulence (CAT) and its seasonality over the North Pacific are estimated on the basis of an ensemble of climate projections under warming for the globally averaged surface air temperature of 2 K relative to preindustrial levels, which includes over 3000 years of ensembles using a 60 km atmospheric general circulation model (AGCM). The AGCM outputs are interpolated to a 1.25° horizontal resolution, and the climatological CAT frequency is computed. The CAT broadly decreases in the midlatitude central to western North Pacific along with the anticyclonic (south) side of its present-day high-frequency band extending from Japan to the eastern North Pacific. Meanwhile, large relative increases are found outside the band, implying an increased risk of CAT encounters. Uncertainty in future CAT changes due to uncertainties in the spatial pattern of sea surface temperature (SST) change is addressed for the first time using six selected Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. The uncertainty is greatest in the boreal winter and spring over the central North Pacific and is associated with an uncertainty in future changes in the jet stream and upper-level synoptic-scale disturbances.

 In this paper, we propose an H-infinity (H_∞) filtering approach for the prediction of bias in post-processing of model outputs and past measurements. This method adopts a minimax strategy that is a solution for zero-sum games. The proposed H_∞ filtering approach minimizes maximum possible errors whereas a recently proposed approach that adopts Kalman filtering (KF) minimizes the mean square errors. The proposed approach does not need the information of noise statistics unlike the method based on the KF, while the training process is required. We show that the proposed approach outperforms the method based on the KF in experiments by applying real weather data in Korea.