“Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress

MIYOSHI, TAKEMASA; LIEN, GUO-YUAN; SATOH, SHINSUKE; USHIO, TOMOO; BESSHO, KOTARO; TOMITA, HIROFUMI; NISHIZAWA, SEIYA; YOSHIDA, RYUJI; ADACHI, SACHIHO A.; LIAO, JIANWEI; GEROFI, BALAZS; ISHIKAWA, YUTAKA; KUNII, MASARU; RUIZ, JUAN; MAEJIMA, YASUMITSU; OTSUKA, SHIGENORI; OTSUKA, MICHIKO; OKAMOTO, KOZO; SEKO, HIROMU

PROCEEDINGS OF THE IEEE

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Lugar: New York; Año: 2016 vol. 104 p. 2155 - 2179

0018-9219

Following the invention of the telegraph, electronic computer, and remote sensing, ?big data? is bringing another revolution to weather prediction. As sensor and computer technologies advance, orders of magnitude bigger data are produced by new sensors and high-precision computer simulation or "big simulation". Data assimilation (DA) is a key to numerical weather prediction (NWP by integrating the real-world sensor dada into simulation. However, the current DA and NWP systems are not designed to handle the "big data" from next-generation sensors and big simulation. Therefore, we propose "big data assimilation" (BDA) innovation to fully utilize the big data. Since October 2013, the Japan´s BDA project has been exploring revolutionary NWP at 100-mesh refresh every 30 s, orders of magnitude finer and faster than the current typical NWP systems, by taking advantage of the fortunate combination of next-generation technologies: the 10-petaflops K computer, phased array weather radar, and geostationary satellite Himawari-8. So far, a BDA protoype system was developed and tested with real-world retropsective local rainstorm cases. This paper summarizes the activities and progress of the BDA project, and concludes with perspectives toward the post-petascale supercomputing era.