ON THE PREDICTABILITY OF TROPICAL CYCLONES THROUGH ALL-SKY INFRARED SATELLITE RADIANCE ASSIMILATION

Open Access
- Author:
- Minamide, Masashi
- Graduate Program:
- Meteorology and Atmospheric Science
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- May 01, 2018
- Committee Members:
- Fuqing Zhang, Dissertation Advisor/Co-Advisor
Fuqing Zhang, Committee Chair/Co-Chair
Eugene Edmund Clothiaux, Committee Member
David Jonathan Stensrud, Committee Member
John Harlim, Outside Member - Keywords:
- data assimilation
satellite
tropical cyclones
numerical weather prediction - Abstract:
- The impacts of assimilating all-sky infrared satellite radiances, in particular from the new-generation geostationary satellites GOES-R (GOES-16) and Himawari-8, for convection-permitting initialization and prediction of tropical cyclones are explored. Community Radiative Transfer Model (CRTM) is newly connected to the ensemble Kalman filter (EnKF) data assimilation system developed at Penn State University (PSU) and built around the Weather Research and Forecasting model (WRF). Adaptive Observation Error Inflation (AOEI) method and Adaptive Background Error Inflation (ABEI) method are newly proposed to alleviate the large representativeness error in assimilating all-sky satellite radiances that arises from the strong nonlinearity in the observation operator. The impacts of assimilating all-sky satellite radiances for tropical cyclone initializations are investigated through perfect and imperfect Observing System Simulation Experiments (OSSEs) and Observing System Experiments (OSEs) using multiple infrared geostationary satellites including GOES-16, Himawari-8 and GOES-13. It is found that the assimilation of the infrared radiance can accurately constrain the dynamic and thermodynamic state variables. EnKF analyses are able to capture the developing the convective systems and even the individual cells, including the convective activities within the inner-core region of tropical cyclones. Deterministic forecasts initialized from the EnKF analyses exhibit the significant improvement from the forecast without the all-sky satellite radiance assimilation, and become capable of simulating the rapid intensification of tropical cyclones. This dissertation highlights the encouraging prospects of future improvement in tropical cyclone prediction through assimilating all-sky infrared radiance from highly spatiotemporally resolving geostationary satellites.