Presentation Information
[U15-04]Impact of Satellite Data Assimilation on Tropical Cyclone Analysis, Forecasting, and Disaster Mitigation★Invited Papers
*Zhaoxia Pu1 (1.University of Utah, USA)
Keywords:
Tropical Cyclones,Data Assimilation,Satellite,Forecasting,Disaster Mitigation
Accurate monitoring and prediction of tropical cyclones are critical for disaster preparedness and risk reduction. Recent advances in satellite remote sensing provide high-resolution observations of atmospheric thermodynamic structure, surface winds, precipitation, and air–sea interactions, creating new opportunities to improve numerical weather prediction through advanced data assimilation. This presentation summarizes recent developments in satellite data assimilation for tropical cyclones and evaluates their impacts on cyclone analysis, track and intensity forecasting, and associated hazard information relevant to disaster mitigation.
Multiple satellite observations—including microwave and infrared radiances, ocean surface winds, and temperature and moisture profile retrievals (e.g., from GOES-R, GPM, CYGNSS, Aeolus, and TROPICS)—are assimilated within state-of-the-art data assimilation frameworks to better constrain vortex structure and surrounding environmental conditions in both research and operational models (e.g., HWRF and HAFS). The assimilation results demonstrate systematic improvements in the initial representation of cyclones, reductions in forecast track and intensity errors, and enhanced characterization of rainfall and wind distributions that are directly linked to disaster impacts.
Beyond forecast skill, the integration of satellite-constrained analyses into disaster information systems contributes to more reliable early warning, improved situational awareness, and more effective decision-making for preparedness and response. Remaining challenges include observation bias correction, quality control of rapidly evolving inner-core signals, and consistent coupling between atmospheric and oceanic processes. Emerging satellite constellations and coupled Earth system data assimilation frameworks provide promising pathways for further advancement.
These results demonstrate that satellite data assimilation serves as a key bridge between Earth observation, numerical prediction, and the utilization of disaster information, thereby supporting the integration of diverse hazard information and enhancing societal resilience to tropical cyclone disasters.
Multiple satellite observations—including microwave and infrared radiances, ocean surface winds, and temperature and moisture profile retrievals (e.g., from GOES-R, GPM, CYGNSS, Aeolus, and TROPICS)—are assimilated within state-of-the-art data assimilation frameworks to better constrain vortex structure and surrounding environmental conditions in both research and operational models (e.g., HWRF and HAFS). The assimilation results demonstrate systematic improvements in the initial representation of cyclones, reductions in forecast track and intensity errors, and enhanced characterization of rainfall and wind distributions that are directly linked to disaster impacts.
Beyond forecast skill, the integration of satellite-constrained analyses into disaster information systems contributes to more reliable early warning, improved situational awareness, and more effective decision-making for preparedness and response. Remaining challenges include observation bias correction, quality control of rapidly evolving inner-core signals, and consistent coupling between atmospheric and oceanic processes. Emerging satellite constellations and coupled Earth system data assimilation frameworks provide promising pathways for further advancement.
These results demonstrate that satellite data assimilation serves as a key bridge between Earth observation, numerical prediction, and the utilization of disaster information, thereby supporting the integration of diverse hazard information and enhancing societal resilience to tropical cyclone disasters.