A5027116302- Meteorological Phenomena and Simulations
- Precipitation Measurement and Analysis
- Climate variability and models
- Soil Moisture and Remote Sensing
- Atmospheric aerosols and clouds
- Geophysics and Gravity Measurements
- Tropical and Extratropical Cyclones Research
- Image Processing and 3D Reconstruction
- Ocean Waves and Remote Sensing
- Wind and Air Flow Studies
- Ionosphere and magnetosphere dynamics
- GNSS positioning and interference
- Plant Water Relations and Carbon Dynamics
- Geophysical Methods and Applications
- Fluid Dynamics and Turbulent Flows
- Atmospheric and Environmental Gas Dynamics
- Internet of Things and Social Network Interactions
- Engineering Applied Research
- Hydrology and Watershed Management Studies
- Magnetic confinement fusion research
- Nuclear reactor physics and engineering
Japan Meteorological Agency
2017-2025
The University of Tokyo
2022-2025
Meteorological Research Institute
2020-2025
Sphere Institute
2022
Japan Agency for Marine-Earth Science and Technology
2022
Kochi University of Technology
2022
Kyushu University
2022
National Institute of Meteorology
2022
Data assimilation (DA) methods for convective‐scale numerical weather prediction at operational centres are surveyed. The include variational (3D‐Var and 4D‐Var), ensemble (LETKF) hybrids between (3DEnVar 4DEnVar). At several centres, other algorithms, like latent heat nudging, additionally applied to improve the model initial state, with emphasis on convective scales. It is demonstrated that quality of forecasts based data from DA significantly better than simple downscaling larger‐scale...
Abstract We develop a single‐moment bulk cloud microphysics scheme consistent with observations using dual‐polarization radar and disdrometer. In particular, we will introduce non‐spherical properties of hydrometeor realistic rain droplet size distributions. All the hydrometeors are assumed to be oblate, particularly snow is characterized by combination stellar, irregular, column. The shape new distribution function determined based on 3‐year disdrometer rescaled dimensionless optimizing...
Abstract Using detailed radar observation data for Typhoon Faxai, which made landfall in the Tokyo metropolitan area 2019, a sensitivity test of boundary layer (BL) schemes numerical weather prediction (NWP) model was conducted gray-zone simulations with grid spacing 250 m. We compared results our using an NWP observations that captured BL and secondary circulation structures Faxai. used three based on Reynolds-averaged model, large-eddy simulation (LES) model: Mellor–Yamada–Nakanishi–Niino...
The regional data assimilation system at the Japan Meteorological Agency employs a variational on basis of non-hydrostatic model ASUCA (named ASUCA-Var). This paper reviews configurations and current status ASUCA-Var. To consider consistency analysis prognostic variables, control variables ASUCA-Var include soil basic atmospheric variables. background-errors based are calculated every three hours for land sea grid points to better reflect representative error covariance structure, taking...
Abstract In this study, the single-moment 6-class bulk cloud microphysics scheme used in operational numerical weather prediction system at Japan Meteorological Agency was improved using observations of Global Precipitation Measurement (GPM) core satellite as reference values. The original has following biases: underestimation ice compared to brightness temperature GPM Microwave Imager (GMI) and lower-troposphere rain reflectivity Dual-frequency Radar (DPR). Furthermore, validation...
Abstract We describe a collaborative analysis study involving numerical models and observation data for the Tokyo metropolitan area called ULTra-sIte Measuring Atmosphere of Metropolitan Environment (ULTIMATE) project. It evaluates cloud microphysics schemes using extensive area. have access to various remote sensing in situ operational research purposes, particularly by enhancing observations ground validation EarthCARE satellite, which is set launch 2023. This focuses on dual-polarization...
Abstract A few high-wind observations have been obtained from satellites over the ocean around tropical cyclones (TCs), but impact of data assimilation such sea on forecasting has not clear. The spaceborne synthetic aperture radar (SAR) provides high-resolution and wide-area surface wind speed center a TC. In this study, SAR (OWSAR) regional model forecasts was investigated. assimilated were estimated board Sentinel-1 RADARSAT-2 . bias OWSAR depends speed, observation error variance...
Abstract We conducted field observations using two water vapor Raman lidars (RLs) in Kyushu, Japan, to clarify the characteristics of a moist low-level jet (MLLJ), which plays fundamental role formation and maintenance mesoscale convective systems (MCSs). The RLs observed inside outside an MLLJ, providing moisture MCS with local heavy precipitation on 9 July 2021. Our revealed that MLLJ contained large amounts below mixing layer height 1.6 km. amount might be intensified by convergences...
Abstract We describe a collaborative analysis study involving numerical models and observation data for the Tokyo metropolitan area, called ULTIMATE (ULTra-sIte Measuring Atmosphere of Metropolitan Environment) project. It evaluates cloud microphysics schemes using extensive area. have access to variety remote sensing in-situ area operational research purposes, particularly by enhancing observations ground validation EarthCARE satellite, which is set launch in 2023. This focuses on...
Abstract Spaceborne precipitation radar such as Global Precipitation Measurement (GPM)/dual‐frequency (DPR) provides valuable observations of systems in three dimensions. Assimilation GPM/DPR data is becoming an important technique for improving the accuracy forecasting to complement scarce ground‐based observations. This study presents a new, one‐dimensional maximum‐likelihood estimation (1D‐MLE) method developed by authors that enables relative humidity profiles according non‐Gaussian...
Abstract Water vapour advection from the sea causes extremely heavy rainfall in Japan. Therefore, accurately describing water distribution over a forecast model's initial conditions should improve prediction accuracy of events. Thus, we assimilated shipborne precipitable (PWV) observed by Global Navigation Satellite Systems (GNSS) onboard ships to show its impact on event July 2020. We obtained GNSS observations during continuous observation campaign conducted at sea, one few world. In this...
This study hybridizes the background error covariance (BEC) of hourly atmospheric three-dimensional variational data assimilation (3DVar) in Local Analysis (LA) operated at Japan Meteorological Agency using flow-dependent BEC derived from singular vector-based Mesoscale Ensemble Prediction System (MEPS) and static BEC. The impact introducing hybrid into 3DVar is examined, along with its sensitivities to various factors like ensemble size that augmented by lagged forecasts, weight given...
The assimilation of cloudy and rainy microwave observations is under investigation at Météo-France with a method called "1D-Bay+3D/4D-Var". This comprises two steps: (i) Bayesian inversion (ii) the retrieved relative humidity profiles in 3D/4D-Var framework. In this paper, estimators for are used: either weighted average (WA) or maximum likelihood (ML) kernel density function. Sensitivity studies over first step conducted different degrees freedom: observation error, channel selection...
Abstract We conducted an observational survey using a ground-based water vapor Raman lidar (RL) during the warm season in Japan to investigate structure of low-level inflows that contribute formation mesoscale convective system (MCS). After passage front, moisture convergence contributed initiation and development numerous clouds composed MCS. The RL observations showed vertical profiles mixing ratio (WVMR) associated with into MCS exceeded 20 g kg −1 below 500 m above sea level, which is...
Abstract Quantification of latent heating associated with precipitation at midlatitudes is essential for understanding weather and climate. While the Spectral Latent Heating (SLH) algorithm, which retrieves profiles using satellite-borne radars, has been developed tropical precipitation, it cannot be applied to midlatitude because their different characteristics. In this study, SLH algorithm global developed. Part I, look-up tables (LUTs) that tie characteristics are constructed Local...
Abstract A new algorithm for estimating the latent heating profile precipitation in extratropics was developed to extend current spectral (SLH) that applies only tropics. The incorporates normalized relative height into estimation deep stratiform precipitation. successfully determines cloud base heights, above and below which cooling occur, from adapts well quite diverse related extratropics. Another important improvement is detection of multiple layers profiles are not implemented tropics,...