Big Data Assimilation

p2-1 January 22 14:40-15:40

Development of long-term high-resolution regional reanalysis system over Japan with NHM-LETKF nested in JRA-55

S.Fukui(Tohoku University), T.Iwasaki(Tohoku University), K.Saito(The University of Tokyo), H.Seko(Meteorological Research Institute)


We are developing a regional reanalysis system covering Japan and its surrounding area with a 5-km grid spacing over ~60 years using the JMA’s nonhydrostatic model (NHM) nested in JRA-55 and the local ensemble transform Kalman filter (LETKF). The assimilated data are limited to the conventional observations, such as surface pressure observations and radiosonde observations, to keep the consistency in reanalysis quality throughout the entire reanalysis period. The reanalysis dataset is expected to enable us to investigate local long-term trends and to compare past meso-scale extreme events to each other.

Before conducting a long-term reanalysis, regional reanalysis experiments were conducted to optimize the NHM-LETKF system from the perspective of long-term reanalysis. The first guess fields given from the deterministic runs, not from ensemble mean fields of the perturbed runs, avoided the smooth analysis fields. The assimilation of data associated with typhoons encouraged to simulate the actual position and intensity of typhoons over the ocean where the observations were sparse.

Contact information

Dr. Shin Fukui Tohoku University