Fu Wang

Fu Wang

Senior Engineer, CMA Earth System Modeling and Prediction Centre, WMO Expert

Honors & Awards

Honors & Awards

  • 2022, The 17th China Young Female Scientist Team Award — “FY Satellite High-Precision Calibration and Positioning Technology Team”, conferred by the All-China Women’s Federation and the China Association for Science and Technology. National-level team award (15/16).
    Contribution: Built a quality monitoring platform using the domestic NWP model as reference, replacing foreign model data; the improved data was applied in CMA-GFS and other systems, enhancing forecast accuracy; supported the FY-5 mission planning through observation simulation based on domestic NWP.

  • 2023, First Batch of National Meteorological Industry Demonstration Innovation Studio — “Zhang Yong Innovation Studio (Satellite Calibration and Validation)”, conferred by the China Agriculture, Forestry, Water Resources and Meteorological Workers’ Union and the CMA Office. Provincial/ministerial-level team title (6/9).
    Contribution: Conducted long-term infrared channel calibration traceability and bias monitoring for FY satellite imagers and sounders aligned with data assimilation needs; participated in field experiments to build a star-ground evidence chain; contributed to national standards and L1 radiation correction workflows, supporting operational L1/L2 satellite data applications.

  • 2025, 2024 Outstanding NWP Technical Report — “Satellite Data Quality Development Effectively Supports the Increase of Data Assimilation Proportion”, conferred by the CMA Forecasting and Networking Department. Bureau-level Excellence Award (3/3).
    Contribution: Connected the full chain of data quality improvement → assimilation application → impact evaluation; assessed the benefits of bias-corrected satellite data on assimilation proportion and forecast performance in the domestic operational NWP model.

  • 2024, 2024 Achievement Supporting Flood Season Meteorological Services, conferred by the CMA Department of Science, Technology and Climate Change. Bureau-level Excellence Award (8/24).
    Contribution: Developed a rapid assimilation method for dense satellite data based on the CMA-MESO 1 km resolution model system, targeting damaging wind forecasting; produced high-resolution real-time environmental analysis fields for severe convective storms; significantly reduced near-surface wind forecast bias, especially for strong winds.

  • 2024, Excellent Conference Presentation Award, Chinese Meteorological Society.