Assimilating All-Sky Himawari-8 Satellite Infrared Radiances: A Case of Typhoon Soudelor (2015)

Abstract

Japan’s new geostationary satellite Himawari-8, the first of a series of the third-generation geostationary meteorological satellites including GOES-16, has been operational since July 2015. Himawari-8 produces high-resolution observations with 16 frequency bands every 10 min for full disk, and every 2.5 min for local regions. This study aims to assimilate all-sky every-10-min infrared (IR) radiances from Himawari-8 with a regional numerical weather prediction model and to investigate its impact on real-world tropical cyclone (TC) analyses and forecasts for the first time. The results show that the assimilation of Himawari-8 IR radiances improves the analyzed TC structure in both inner-core and outer-rainband regions. The TC intensity forecasts are also improved due to Himawari-8 data because of the improved TC structure analysis.

Assimilating Every‐10‐minute Himawari‐8 Infrared Radiances to Improve Convective Predictability

“…We applied the spatial thinning to Himawari‐8 observations, and observations from every other observation grid were assimilated to mitigate a negative impact of ignoring the horizontal observation error correlation on the analysis. This thinning distance was much shorter than that in Honda, Miyoshi, et al () and Honda, Kotsuki, et al (). While previous literatures focused on large‐scale phenomena (i.e., TC), we aim to predict smaller‐scale isolated and unorganized convective activities so that denser data should be used.…”

“…This study aims to present a proof‐of‐concept experiment in which the predictability of isolated and unorganized convective activities is improved by assimilating the real every‐10‐min Himawari‐8 infrared radiances. The spatiotemporal scale of our targeted convective activity is much smaller than the previous studies (i.e., Honda, Miyoshi, et al, ; Zhang et al, , ). We investigated how to effectively use satellite radiance observations to improve the simulation of rapidly developing precipitating systems of isolated convective cells governed by nonlinear dynamics.…”

“…We used the method proposed by Tompkins and Janiskova () to estimate the cloud fraction profile for input to RTTOV. The configuration of RTTOV used in this study has thoroughly been evaluated by the previous studies (e.g., Baran et al, ; Okamoto, ; Vidot et al, ) and has been applied to assimilate real all‐sky Himawari‐8 radiances into a mesoscale model (Honda, Miyoshi, et al, ; Honda, Kotsuki, et al, ). We applied no parallax correction, which may bring some errors in estimating radiances especially at the edge of cloud systems (see Kostka et al ()).…”

“…The conventional observations are assimilated only in D1 for all experiments. While only clear‐sky radiances of Himawari‐8 are assimilated in the JMA's operational numerical weather prediction system, we assimilated all‐sky Himawari‐8 radiances as done by Honda, Miyoshi, et al () and Honda, Kotsuki, et al (). In this study, the length of the assimilation window was set to 10 min in the D2 domain of the Him8 and Him8‐RIP experiments, so that the atmospheric state variables were analyzed every 10 min.…”

“…Zhang et al () presented a proof‐of‐concept observing system simulation experiment that indicated that assimilating all‐sky GOES‐16 satellite radiances can improve the analysis and forecast of a TC. Honda, Miyoshi, et al () improved the TC analysis and forecast by assimilating the real Himawari‐8 all‐sky infrared radiances. Kunii et al () and Honda, Kotsuki, et al () revealed that Himawari‐8 data assimilation can improve the forecast of TC‐induced rainfall.…”