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Abstract: This work is a contribution to a large project, aimed at the development of an advanced environmental assessment modelling system to be used in Japan. The modelling system here considered consisted of the RAMS and HYPACT coupled models. The RAMS code was modified to properly simulate local scale phenomena using a fine mesh size of 250 m. In this direction, the main aim here was to investigate the effect of the choice of the turbulence closure scheme on the dispersion of pollutants. Our modified version of the RAMS/HYPACT model chain was validated using field experiments which were carried out by the Japan Atomic Energy Research Institute (JAERI) in the area of Mt. Tsukuba (Japan). The mean flow, turbulence and concentration fields obtained using two alternative turbulence closure schemes are compared. A discussion on the different performances of the turbulence closures is presented and the influence of the closure schemes over the plume dispersion is investigated. [Copyright &y& Elsevier]

Despite advancements in remote sensing applications for grassland management, studies following the 2011 Fukushima Daiichi nuclear disaster have often been constrained by limited satellite imagery with insufficient focus on pasture changes. Utilizing different resolutions of optical satellite data is essential for monitoring spatiotemporal changes in grasslands. High resolutions provide detailed spatial information, whereas medium-resolution satellites offer an increased frequency and wider availability over time. This study had two objectives. First, we investigated the temporal changes in a mountainous pasture in Japan from 2007 to 2022 using high-resolution data from QuickBird, WorldView-2, and SPOT-6/7, along with readily available medium-resolution data from Sentinel-2 and Landsat-5/7/8. Second, we assessed the efficacy of different satellite image resolutions in capturing these changes. Grazing ceased in the target area after the 2011 Fukushima Daiichi nuclear accident owing to radiation. We categorized the images as grasses, broadleaf trees, and conifers. The results showed a 36% decline using high-resolution satellite image analysis and 35% using Landsat image analysis in the unused pasture area since grazing suspension in 2011, transitioning primarily to broadleaf trees, and relative stabilization by 2018. Tree encroachment was prominent at the eastern site, which has a lower elevation and steeper slope facing north, east, and south. WorldView-2 consistently outperformed Landsat-8 in accuracy. Landsat-8's classification variation impedes its ability to capture subtle distinctions, particularly in zones with overlapping or neighboring land covers. However, Landsat effectively detected area reductions, similar to high-resolution satellites. Combining high- and medium-resolution satellite data leverages their respective strengths, compensates for their individual limitations, and provides a holistic perspective for analysis and decision-making. [ABSTRACT FROM AUTHOR]

Meteorological information used for disaster prevention has developed rapidly in terms of both type and specificity. The latest forecasting models can predict weather with very high resolutions that can characterize disaster risk at the local level. However, this development can lead to an overdependency on the information and a wait-and-see attitude by the public. At the same time, residents share and use various types of information for disaster response, such as local conditions, in addition to official disaster information. Our research in Japan verified the practicality and efficiency of synergistically integrating these types of information by examining actual evacuation cases. The current numerical forecasting models sufficiently identify locality from the viewpoint of various administrative scales such as prefectures, municipalities, and school districts, but the improvements to these models have failed to improve residents' judgment in successful evacuation cases. We therefore analyzed the relationship between meteorological information and residents' disaster response and confirmed that they were strongly correlated and were contributing factors in preventing disasters. We revealed differences between a community's disaster prevention culture and the disaster information provided. This led us to propose a new concept in community disaster prevention that we call the "disaster response switch," which can serve as a data-driven risk management tool for communities when used in combination with advanced meteorological disaster information. [ABSTRACT FROM AUTHOR]

As computational techniques advance, the scope of digital twins (DTs) is expanding to encompass entire cities, oceans, or even the Earth. Digital twins of oceans can provide highly comprehensive insights and predictions, thus enabling better-informed decision-making regarding ocean-related activities and management. Here, a numerical model of the Seto Inland Sea (SIS), Japan, was built as a basis to establish a digital twin of the SIS. Spatially varying filtering parameters and grid resolutions were applied to facilitate the robust and accurate simulation of coastal and oceanic processes even under varying extreme conditions. The modeling results were validated using observational datasets from forty-two tidal stations, one mooring system, and thirteen water thermometers. The results represented tidal variations, with NRMSE values below 0.15 and R2 values exceeding 0.87 at all tidal stations. The NRMSE and R2 values for currents were approximately 0.14 and 0.76, respectively. The model reproduced the extreme storm surge event causing a sea level rise of 1.5 m near Osaka City resulting from Typhoon Jebi in 2018. The model was shown to enable analyses of complex circulations and hazards in the SIS by accurately replicating barotropic and baroclinic processes. After additional modules are added, this model will serve as a basis for constructing a digital twin of the SIS. [ABSTRACT FROM AUTHOR]

Ocean bottom distributed acoustic sensing (OBDAS) is emerging as a new measurement method providing dense, high-fidelity and broad-band seismic observations from fibre-optic cables deployed offshore. In this study, we focus on 35.7 km of a linear telecommunication cable located offshore the Sanriku region, Japan, and apply seismic interferometry to obtain a high-resolution 2-D shear wave velocity (VS) model below the cable. We first show that the processing steps applied to 13 d of continuous data prior to computing cross-correlation functions (CCFs) impact the modal content of surface waves. Continuous data pre-processed with 1-bit normalization allow us to retrieve dispersion images with high Scholte-wave energy between 0.5 and 5 Hz, whereas spatial aliasing dominates dispersion images above 3 Hz for non-1-bit CCFs. Moreover, the number of receiver channels considered to compute dispersion images also greatly affects the resolution of extracted surface-wave modes. To better understand the remarkably rich modal nature of OBDAS data (i.e. up to 30 higher modes in some regions), we simulate Scholte-wave dispersion curves for stepwise linear VS gradient media. For soft marine sediments, simulations confirm that a large number of modes can be generated in gradient media. Based on pre-processing and theoretical considerations, we extract surface wave dispersion curves from 1-bit CCFs spanning over 400 channels (i.e. ∼2 km) along the array and invert them to image the subsurface. The 2-D velocity profile generally exhibits slow shear wave velocities near the ocean floor that gradually increase with depth. Lateral variations are also observed. Flat bathymetry regions, where sediments tend to accumulate, reveal a larger number of Scholte-wave modes and lower shallow velocity layers than regions with steeper bathymetry. We also compare and discuss the velocity model with that from a previous study and finally discuss the combined effect of bathymetry and shallow VS layers on earthquake wavefields. Our results provide new constraints on the shallow submarine structure in the area and further demonstrate the potential of OBDAS for high-resolution offshore geophysical prospecting. [ABSTRACT FROM AUTHOR]

This review introduces the technique of helium ion microscopy along with some unique applications of this technology in the fields of electronics and biology, as performed at the National Institute of Advanced Industrial Science and Technology, Japan, over the last several years. Observations of large-scale integrated circuits, analyses of low-dielectric-constant films with minimal damage, and assessments of copper metal in insulating films are discussed. The special characteristics of this technique are explained, including low-energy input to the material and minimal secondary electron energy resulting from helium ion irradiation. Applications to electronic materials, such as tuning the electrical conductivity of graphene films by helium ion beam irradiation and the formation of nanopore arrays on graphene films with nanometer-scale control, are presented. The use of helium ion microscopy to examine cellular tissues based on the low damage imparted by the ion beam is also evaluated. [ABSTRACT FROM AUTHOR]

This study quantitatively and chronologically analyzed the technology management of Japanese biotechnology companies using the patent application data of platforms and products, including patent categorization methods. Nine listed platform companies were analyzed. The results showed that most of the companies continuously maintained their initial platform technologies by filing updated patents, but without filing patents of new platform technologies. Their business models were shifted from a platform model to a platform-product, hybrid model and not a product-focused model. Their product patents generated from platform technologies were mainly for tools, diagnostics, and cell processing technologies, not therapeutics, except in one case; related therapeutics patents were mainly filed by corporate partners. Existing papers that analyzed Japanese biotechnology companies were verified to be partially correct based on our high-resolution patent categorization data; these results supported the usefulness of our approach. [ABSTRACT FROM AUTHOR]

We theoretically and empirically demonstrate the usability of the zero-crossing method for quick microtremor surveys in earthquake engineering (i.e. microtremor array surveys), namely shallow (< a few kilometres) surveys with small-scale (< 1 kilometre in radius) mobile seismic arrays with a short observation time (< a few hours). The zero-crossing method is a type of spatial autocorrelation (SPAC) method that determines phase velocities based on multiple frequencies at which the SPAC coefficient curve crosses zero. It is theoretically shown that the zero-crossing method is robust against incoherent noise and that the use of the first zero crossings (i.e. those at the lowest frequencies) is more robust against inadequate conditions of the microtremor wavefield than the use of later zero crossings (i.e. those at higher frequencies). We used microtremor array data with maximum array radii and observation durations of 400 m and 120 min on average, respectively, at 445 observation sites in the Kanto Plain, Japan, for validating the practicality of using the first zero crossings. As an illustration of the robustness against low signal-to-noise ratios (SNRs), we show that with the zero-crossing method, low-sensitivity (i.e. low-SNR) seismometers provide the same analysis results as those obtained with high-sensitivity seismometers, even when the power spectral densities for the low-sensitivity seismometers are close to the self-noise level. We then show that a reference phase velocity dispersion curve (RPVDC), created mainly based on the first zero crossings at each site, has a spatial distribution that well corresponds to the geology and topography and is consistent with that obtained in a previous study. We inverted five RPVDCs to model 1-D S -wave profiles and validated them using S -wave profiles obtained from velocity logs at nearby deep (e.g. hundreds of metres) boring wells. The accuracy of phase velocities at the later zero crossings for three-sensor/four-sensor arrays and all zero crossings for two-sensor arrays are statistically examined (maximum of 9805 data) based on a comparison with the RPVDCs. The disadvantage of the zero-crossing method is that it can only provide information on phase velocities at discrete wavelengths up to a maximum wavelength of 2.6 r (i.e. corresponding to the first zero-crossing point), where r is the radius of a seismic array. Therefore, the RPVDCs were then used to examine the upper limit of the analysable wavelength ranges for the conventional SPAC method for microtremor array surveys. Based on a few hundred three-sensor/four-sensor arrays, it was found that for arrays with radii larger than several tens of metres, three-quarters of the upper limit wavelengths (ULWs) stayed within 5 r. For arrays with radii smaller than this value, the ULWs strongly depended on the array radius; the ULWs dramatically increased with decreasing array radius. For example, for arrays with an r value of 0.6 m, half of 336 data ranged between 26 r and 54 r , and the maximum ULW reached 186 r. This strong size dependence can be explained by differences in SNR. [ABSTRACT FROM AUTHOR]

An accident occurred when an aircraft landed at Narita International Airport, Japan, on 20 June 2012. The aircraft encountered rapid changes of winds together with strong turbulence, although the weather was fair. In the present study, a two‐domain nested regional weather prediction models are used. The results in the outer domain show that southwesterly winds associated with a synoptic extratropical cyclone were locally accelerated to the southwest of the airport resulting in strong vertical shear. The simulation in the inner domain reproduces horizontal convective rolls, which are similar to those observed by a Doppler lidar at the airport. The wind velocity component parallel to the runway had a spatial variation of about 10 m s −1. The present approach using a large eddy simulation is useful for clarifying environments and features of horizontal convective rolls and forecasting low‐level wind shear associated with them, which can be a significant risk for aircraft. Plain Language Summary: Synoptic/mesoscale fronts and downbursts (strong downdrafts from a thunderstorm and diverging winds after they hit the ground) are known to be serious threats to airplanes during takeoff and landing. However, it is less known that there is another type of danger under fair weather conditions. An aircraft landing at Narita International Airport, Japan, in the afternoon of 20 June 2012 encountered rapid changes of wind and turbulence and made a hard landing, resulting in several injuries and damage to the fuselage. A Doppler lidar, a remote sensing device for monitoring low‐level winds at the airport observed alternating regions of strong and weak winds aligned southwest–northeast, perpendicular to the runway. In order to clarify the detailed structure and mechanism of these disturbances, numerical simulations using a fine‐resolution (horizontal resolution: 100 m) nested in a coarse resolution (horizontal resolution: 1 km) are made. The simulations show that horizontal convective rolls, which occur in convective boundary layers with strong vertical shear (vertical gradient of horizontal wind speed) were prevailing. These rolls are associated with the rapid changes in wind speed and turbulence similar to those observed by the Doppler lidar and flight recorder. The present study demonstrates that the large eddy simulation is useful for clarifying the structure and mechanisms of horizontal convective rolls, which caused the aircraft accident, and also for forecasting them. Key Points: Horizontal convective rolls that caused an aircraft accident in a fair weather condition were successfully reproduced by a numerical modelCharacteristics of the rolls and turbulence as observed by a Doppler lidar and flight recorder are clarified based on the model resultsCapability of accessing and operationally predicting potentially hazardous rolls by use of a large eddy simulation is demonstrated [ABSTRACT FROM AUTHOR]

An intense rainband associated with Typhoon 1326 (Wipha) induced a fatal debris flow on Izu Oshima, Japan, on October 15 - 16, 2013. This rainband formed along a local front between the southeasterly humid warm air around the typhoon and the northeasterly cold air from the Kanto Plain. In this paper, the Japan Meteorological Agency Nonhydrostatic Model was optimized for the "K computer", and ultra-high-resolution (500 - 250 m grid spacing) numerical simulations of the rainband with a large domain were conducted. Two of main factors that affect a numerical weather prediction (NWP) model, (1) grid spacing and (2) planetary boundary layer (PBL) schemes [Mellor-Yamada-Nakanishi-Niino (MYNN) and Deardorff (DD)], were investigated. Experiments with DD (Exps_DD: grid spacings of 2 km, 500 m, and 250 m) showed better reproducibility of the rainband position than experiments with MYNN (Exps_MYNN: grid spacings of 5 km, 2 km, and 500 m). Exps_DD simulated distinct convective-scale up/downdraft pairs on the southeast/northwest sides of the front, whereas those of Exps_MYNN were not clear. Exps_DD yielded stronger cold pools near the surface than did Exps_MYNN. These differences in the boundary layer structures likely had a large impact on the position of the front and the associated rainband. Exps_DD with the 500-m grid spacing showed the best precipitation performance according to the Fractions Skill Score. To check other factors which influence precipitation forecast, model domain sizes, lateral boundary conditions in nesting simulations, and terrain representations were investigated. In the small domain experiments, the rain-planband shapes were very different from the observations. In the experiment using a nesting procedure, the deterioration of the forecast performance was acceptably reduced. The model with fine terrains reproduced the intense rain over the island. These results demonstrate that the ultra-high-resolution NWP model with a large domain has the possibility to improve predictions of heavy rain. [ABSTRACT FROM AUTHOR]

P and S waves radiating from repeating earthquakes are analysed to identify subtle changes in seismic wave velocity associated with the Mw 9.0 Tohoku-Oki earthquake at shallow and deep zones in NE Japan. Accurate measurement of the changes in traveltimes of P and S waves needs high precision of the repeating earthquake's hypocentre parameters, but a large area of NE Japan was damaged so that usual hypocentre relocation methods may not be applicable. Therefore, we develop a new inversion method to simultaneously determine velocity changes of the structure as well as hypocentre parameters of repeating earthquakes. We represent arrival time differences of body waves from a pair of repeating earthquakes occurring before and after a target large earthquake by linear equations of relative locations, origin times and station correction factors, and determine these parameters by using a least-squares method. Arrival time differences at stations for a set of 25 repeating earthquakes are measured by comparing the observed waveforms. Applying the inversion method to these data, we find that traveltime delays up to about 0.04 s for the S wave are widely distributed in NE Japan close to the large slip area of the Tohoku-Oki earthquake. Traveltime delays for P waves are much smaller than those for S waves. The spatial change of traveltime delays are not well correlated with those of strong motions. This implies that the traveltime delays are not caused only in the shallow subsurface. To investigate where the seismic velocity changes occur, we separately analyse the repeating earthquakes occurring in the north and south regions of NE Japan, and observe a spatial shift of large station correction factors for the S wave: large station correction factors estimated from the repeating earthquakes located in the north are shifted to the south area of NE Japan, while those from the repeating earthquakes of the south are shifted to the north area. From comparisons of these spatial changes in the observed time differences with results obtained from forward modeling of direct S wave, the velocity decrease of about 0.1 per cent is inferred to extend in N-S direction in the middle of NE Japan with a depth of approximately 25 km. Our results provide important evidence that the medium changes after a megathrust earthquake such as the 2011 Tohoku-Oki earthquake are not limited to surface layers due to the effects of strong ground motion, but extend deeper in the crust. [ABSTRACT FROM AUTHOR]

The vertical distribution profiles of the water vapor mixing ratio (w) were measured by Raman lidar at the Meteorological Research Institute, Japan, during the period from 2000 to 2004. The measured values were compared with those obtained with radiosondes, hygrometers on a meteorological observation tower, and global positioning system (GPS) antennas near the lidar site. The values of w obtained with the lidar were lower than those obtained with the corrected Meisei RS2-91 radiosonde by 1.2% on average and higher than those obtained with the corrected Vaisala RS80-A radiosonde by 17% for w ≥ 0.5 g kg-1. The lidar data were higher than those radiosondes’ data by 19% or 33% for w < 0.5 g kg-1. The vertical variations of w obtained with the lidar differed from those obtained with the Meisei RS-01G radiosonde and Meteolabor Snow White radiosonde by 5% on average for w ≥ 0.5 g kg-1. The lidar data were lower than those radiosondes’ data by 37% or 39% for w < 0.5 g kg-1. The temporal variations of w obtained with the lidar and the hygrometers on the meteorological tower agreed to within 0.4% at a height of 213 m, although the absolute values differed systematically by 9%–14% due to the incomplete overlap of the laser beam and the receiver’s field of view at heights between 50 and 150 m. The precipitable water vapor obtained with the lidar indicated a mean positive bias of 2 mm (9%–11%) relative to those obtained with GPS. The lidar water vapor calibration coefficient that was calculated using RS2-91 radiosonde data varied by 11% during an 18-month period. Therefore, it is necessary to develop an accurate, yet convenient, method for determining the calibration coefficient for the use of the lidar. [ABSTRACT FROM AUTHOR]

Simple Summary: Recently, the risk of tick-borne diseases (TBD) has drawn increasing attention from a public health perspective. Information about where ticks are distributed is important for the prevention of TBDs. In this study, we used the MaxEnt model to predict the potential distribution of six major tick species out of 16 tick species collected in the Kanto region, the central part of Japan, based on land-use, climate, and wildlife distribution, and to investigate the factors that contribute to each distribution of ticks. The distribution of raccoons contributed to the distribution of five tick species, and forest connectivity was a strong contributor to the distribution of all species. Background: Tick distributions have changed rapidly with changes in human activity, land-use patterns, climate, and wildlife distributions over the last few decades. Methods: To estimate potential distributions of ticks, we conducted a tick survey at 134 locations in western Kanto, Japan. We estimated the potential distributions of six tick species (Amblyomma testudinarium Koch, 1844; Haemaphysalis flava Neumann, 1897; Haemaphysalis kitaokai Hoogstraal, 1969; Haemaphysalis longicornis Neumann, 1901; Haemaphysalis megaspinosa Saito, 1969; and Ixodes ovatus Neumann, 1899) using MaxEnt modeling based on climate patterns, land-use patterns, and the distributions of five common wildlife species: sika deer (Cervus nippon Temminck, 1838), wild boar (Sus scrofa Linnaeus, 1758), raccoon (Procyon lotor Linnaeus, 1758), Japanese raccoon dog (Nyctereutes procyonoides Gray, 1834), and masked palm civet (Paguma larvata C.E.H. Smith, 1827)). Results: We collected 24,546 individuals of four genera and 16 tick species. Our models indicated that forest connectivity contributed to the distributions of six tick species and that raccoon distribution contributed to five tick species. Other than that, sika deer distribution contributed to H. kitaokai, and wild boar distribution, bamboo forest, and warm winter climate contributed specifically to A. testudinarium. Conclusions: Based on these results, the dispersal of some tick species toward residential areas and expanded distributions can be explained by the distribution of raccoons and by forest connectivity. [ABSTRACT FROM AUTHOR]

The development of new methods for estimating precise forest structure parameters is essential for the quantitative evaluation of forest resources. Conventional use of satellite image data, increasing use of terrestrial laser scanning (TLS), and emerging trends in the use of unmanned aerial systems (UASs) highlight the importance of modern technologies in the realm of forest observation. Each technology has different advantages, and this work seeks to incorporate multiple satellite, TLS- and UAS-based remote sensing data sets to improve the ability to estimate forest structure parameters. In this paper, two regression analysis approaches are considered for the estimation: random forest regression (RFR) and support vector regression (SVR). To collect the dependent variable, in situ measurements of individual tree parameters (tree height and diameter at breast height (DBH)) were taken in a Japanese cypress forest using the nondestructive TLS method, which scans the forest to obtain dense and accurate point clouds under the tree canopy. Based on the TLS data, the stem volume was then computed and treated as ground truth information. Topographic and UAS information was then used to calculate various remotely sensed explanatory variables, such as canopy size, canopy cover, and tree height. Canopy cover and canopy shapes were computed via the orthoimages derived from the UAS and watershed segmentation method, respectively. Tree height was computed by combining the digital surface model (DSM) from the UAS and the digital terrain model (DTM) from the TLS data. Topographic variables were computed from the DTM. The backscattering intensity in the satellite imagery was obtained based on L-band (Advanced Land Observing Satellite-2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2)) and C-band (Sentinel-1) synthetic aperture radar (SAR). All satellite (10–25 m resolution), TLS (3.4 mm resolution) and UAS (2.3–4.6 cm resolution) data were then combined, and RFR and SVR were trained; the resulting predictive powers were then compared. The RFR method yielded fitting R2 up to 0.665 and RMSE up to 66.87 m3/ha (rRMSE = 11.95%) depending on the input variables (best result with canopy height, canopy size, canopy cover, and Sentinel-1 data), and the SVR method showed fitting R2 up to 0.519 and RMSE up to 80.12 m3/ha (rRMSE = 12.67%). The RFR outperformed the SVR method, which could delineate the relationship between the variables for better model accuracy. This work has demonstrated that incorporating various remote sensing data to satellite data, especially adding finer resolution data, can provide good estimates of forest parameters at a plot level (10 by 10 m), potentially allowing advancements in precision forestry. [ABSTRACT FROM AUTHOR]

Recent extreme weather events like the August 2016 flood disaster have significantly affected farmland in mid-latitude regions like the Tokachi River (TR) watershed, the most productive farmland in Japan. The August 2016 flood disaster was caused by multiple typhoons that occurred in the span of two weeks and dealt catastrophic damage to agricultural land. This disaster was the focus of our flood model simulations. For the hydrological model input, the rainfall data with 0.04° grid space and an hourly interval were provided by a regional climate model (RCM) during the period of multiple typhoon occurrences. The high-resolution data can take account of the geographic effects, hardly reproduced by ordinary RCMs. The rainfall data drove a conceptual, distributed rainfall–runoff model, embedded in the integrated flood analysis system. The rainfall–runoff model provided discharges along rivers over the TR watershed. The RCM also provided future rainfall data with pseudo-global warming climate, assuming that the August 2016 disaster could reoccur again in the late 21st century. The future rainfall data were used to conduct a future flood simulation. With bias corrections, current and future flood simulations showed the potential inundated areas along riverbanks based on flood risk levels. The crop field-based agricultural losses in both simulations were estimated. The future cost may be two to three times higher as indicated by slightly higher simulated future discharge peaks in tributaries. [ABSTRACT FROM AUTHOR]