Assimilation of satellite data in improving numerical simulations of tropical cyclones: Lessons learned from field programs in last decade

Tropical cyclones originate over the ocean where conventional data are very sparse. Satellites provide a very useful source of data for studying tropical cyclones. During the last decade, major tropical cyclone field experiments (e.g., TCSP, NAMMA, RAINEX, PREDICT, TCS08/TPARC, GRIP) were conducted in the science community. These field programs not only offered an opportunity to study tropical cyclone genesis, intensification and evolution through its intense observing periods (IOPs), but also provided a good platform to evaluate impact of the satellite data on numerical simulations and the predictability of tropical cyclones.

Over the last decade, the author, her students, and collaborators have conducted numerical simulations with satellite data assimilation for major tropical cyclone cases during these aforementioned field programs. The impact of satellite data from TRMM, GOES, QuikSCAT, AIRS etc. on the numerical simulation of major tropical cyclones during the field experiments is examined. The influence of satellite data quality, types, and coverage on the predictability of tropical cyclone is evaluated. The potential benefits and challenges of assimilating satellite data in numerical prediction of tropical cyclone are also suggested. The overall lessons learned from the case studies from field programs in last decade will be summarized and presented.