Japan Geoscience Union Meeting 2023

Presentation information

[E] Online Poster

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI26] Data assimilation: A fundamental approach in geosciences

Tue. May 23, 2023 1:45 PM - 3:15 PM Online Poster Zoom Room (8) (Online Poster)

convener:Shin ya Nakano(The Institute of Statistical Mathematics), Yosuke Fujii(Meteorological Research Institute, Japan Meteorological Agency), Takemasa Miyoshi(RIKEN), Masayuki Kano(Graduate school of science, Tohoku University)

On-site poster schedule(2023/5/22 17:15-18:45)

1:45 PM - 3:15 PM

[MGI26-P09] Estimation of AMSU-A radiance observation impacts in an AGCM-LETKF data assimilation system: Comparison with EFSO and observing system experiments

*Akira Yamazaki1, Koji Terasaki2, Takemasa Miyoshi3,1, Shunsuke Noguchi4 (1.Application Laboratory, Japan Agency for Marine-Earth Science and Technology, 2.Meteorological Research Institute, Japan Meteorological Agency, 3.RIKEN, 4.Department of Earth and Planetary Sciences, Faculty of Science, Kyushu University)

Keywords:AMSU-A satellite radiance observation, Observation impact, Forecast sensitivity to observations

The impacts of assimilating AMSU-A satellite radiances with sensitive channels to the upper troposphere and the lower stratosphere were evaluated using an AGCM–local ensemble transform Kalman filter (LETKF) data assimilation system. Two streams of data-denial experiments for the AMSU-A observations have been performed for about a month in the Northern and Southern Hemisphere (SH) winters. Accumulating observation impact (OI) effects by cycling (repeating) data denials were quantified through the data assimilation system's tropospheric and stratospheric general circulation. It was discovered that adding the AMSU-A observations aided in reducing total OI by all observations of each data assimilation cycle; this is the opposite of the estimation of AMSU-A OI by the ensemble-based forecast sensitivity to observations (EFSO); however, such contributions could stabilize the data assimilation cycles. In both experiments, the accumulated AMSU-A OI was most evident in the upper troposphere, particularly in the SH midlatitudes where the westerly jets exist, and observations of the other types are sparse. The estimated AMSU-A OI by EFSO was also the most valuable (beneficial) in a similar space. Results demonstrated that AMSU-A OI tended to accumulate just downstream where EFSO estimated beneficial OI signals and that the accumulation of AMSU-A OI was tied to dynamic processes in the upper-tropospheric and general stratospheric circulation. Therefore, EFSO helps estimate the beneficial distributions of accumulated AMSU-A OI by considering their dynamical propagation.