A5073821300- Target Tracking and Data Fusion in Sensor Networks
- Speech and Audio Processing
- Neural Networks and Applications
- Meteorological Phenomena and Simulations
- Energy Load and Power Forecasting
- Solar Radiation and Photovoltaics
- Wind Energy Research and Development
Japan Meteorological Agency
2024
Meteorological Research Institute
2024
NOAA has been developing a hybrid 3DEnVar-based Three-Dimensional Real-Time Mesoscale Analysis (3D-RTMA) that integrates non-variational cloud analysis. The goal of the 3D-RTMA system is to generate three-dimensional representation atmosphere for situational awareness and 3-D analysis record. envisioned run with 15-minute cadence at 3 km horizontal resolution. Besides providing full-column standard meteorological fields such as temperature, water vapor, wind, well hydrometeors (i.e., clouds,...
This study applies a multigrid beta filter (MGBF) for covariance localization in ensemble-variational (EnVar) data assimilation instead of the conventional recursive (RF) to achieve faster computation large number processors. The parallelization efficiency MGBF is higher than that RF because all-to-all communication change computational region each processor not necessary. However, MGBF-based additionally requires horizontal variable exchange between processors; its cost proportional grid...