[M-SD35] Future Missions of Satellite Earth Observation

[MSD35-P08] A platform to design and pre-evaluate frequent satellite observing systems for innovating weather, ocean and land surface prediction

*Takemasa Miyoshi¹, Shun Ohishi¹, Hirofumi Tomita¹, James Taylor¹, Michael Goodliff¹, Jianyu Liang¹, Rakesh Teja Konduru¹, Masaki Satoh², Shuhei Matsugishi², Shunji Kotsuki³, Atsushi Okazaki³, Takumi Honda², Kozo OKAMOTO⁴, Yasutaka Ikuta⁴, Koji Terasaki⁴, Hisashi Yashiro⁵, Kaya Kanemaru⁶, Akira Yamazaki⁷ (1.RIKEN, 2.University of Tokyo, 3.Chiba University, 4.JMA/MRI, 5.NIES, 6.NICT, 7.JAMSTEC)

Keywords:OSSE, numerical experimental platform, data assimilation, satellite data

We propose to develop a unique platform with advanced data assimilation technology, realizing numerical simulation experiments for the advanced evaluation of future satellite missions in their design phase. This will provide a scientific, objective approach to an effective design of future satellite missions to maximize the benefit to practical applications such as hydrometeorological prediction and resource control of fisheries. The authors have been leading data assimilation research to explore the best mix of computer model simulations and real-world data for weather forecasting, taking advantage of new-generation technologies such as the supercomputers K and Fugaku, as well as Himawari-8 and -9 satellites. The authors’ previous research revealed that every-10-minute Himawari-8 observations could lead to a large improvement in typhoon and heavy rainfall predictions, though every-30-minute observation was insufficient. We would expect that frequent observations would also be beneficial for ocean and land surface prediction. Therefore, we aim to develop a platform for numerical experimentation to evaluate potential future satellite missions such as quasi-zenith orbiters and small cube-sat constellations for frequent observation over Japan and its surrounding area. This platform will be useful for designing future satellite missions with high cost-benefit performance.