Toward High-Resolution Regional Atmospheric Reanalysis for Japan: An Overview of the ClimCORE Project
Year: 2022
Pages: 6153-6158
DOI Bookmark: 10.1109/BigData55660.2022.10020656
Authors
- Hisashi Nakamura, The University of Tokyo, Research Center for Advanced Science and Technology, Japan
- Kenichi Kuma, The University of Tokyo, Research Center for Advanced Science and Technology, Japan
- Kazutoshi Onogi, The University of Tokyo, Research Center for Advanced Science and Technology, Japan
- Takafumi Miyasaka, The University of Tokyo, Research Center for Advanced Science and Technology, Japan
- Yasutaka Makihara, The University of Tokyo, Research Center for Advanced Science and Technology, Japan
- Junichi Ishida, Japan Meteorological Agency, Japan
- Makoto Iida, The University of Tokyo, Research Center for Advanced Science and Technology, Japan
Abstract
An overview is provided of on-going production of regional atmospheric reanalysis data RRJ-ClimCORE for Japan and its surrounding maritime domain. The data can reproduce the past atmospheric conditions four-dimensionally with high spatial and temporal resolutions, through assimilating fine-resolution observational data into a state-of-the-art operational regional forecast system. The reanalysis data will have wide-ranging potential applications in society, including disaster prevention and risk management planning, and system designing for renewable energy through deep learning.
Similar Articles
- Watershed Reanalysis: Towards a National Strategy for Model-Data Integration
- Climatologies Based on the Weather Research and Forecast (WRF) Model
- Research on Laser Atmospheric Transmittance on the Sea
- Producing and Sharing Regional Weather Forecast Data for e-Science Applications
- Multi-scale Forecasting and Targeting of Tropical Cyclones in the Western Pacific
- Study on Standardization of Detection Data of Atmospheric Microparticle Lidar Based on Metadata
- DeepRainX: Integrated Image Nowcast Based on Deep Learning And Physical Models
- Weather Map Prediction Using RGB Metaphorical Feature Extraction for Atmospheric Pressure Patterns
- Analysis of Atmospheric Drag Acceleration and Engineering Realization of Space Target
- A New Method for Atmospheric Temperature and Humidity Profile Inversion Based on COSMIC-2 Occultation Data and Deep Learning