P6       All-sky infrared radiance assimilation using GOES-16 ABI in WRFDA.

Guerrette, Jonathan (JJ), Zhiquan (Jake) Liu, and Chris Snyder, NCAR/MMM

Constraining convective and microphysical processes with data assimilation requires using observations that resolve those processes at relevant scales.  In this work we use infrared (IR) radiances from the Advanced Baseline Imager (ABI) onboard the GOES-16 satellite, which records full-disk images every 15 minutes with 2 km resolution at nadir.  We conduct two 3DEnVar cycling DA experiments in WRFDA at 3km resolution that focus on a severe storm that spanned central Kansas to eastern Nebraska on 1 May 2018.  This work aims to improve forecast lead-time of the spatial and temporal positioning of this storm, for which there were verified reports of tornadoes and hail.  In addition to GTS, AMDAR, and GNSSRO, a control clear-sky experiment uses ABI radiances that have not been flagged as cloudy by a new online cloud-detection algorithm in WRFDA.  A separate all-sky experiment uses ABI pixels affected by hydrometeors and an observation error inflation (OEI) parameterization based on pixel cloudiness.  OEI enables usage of cloudy pixels that would otherwise degrade the DA analysis due to overfitting of non-Gaussian model departures.  We will present our assessment of GOES-ABI all-sky radiances for improving the predictability of North American continental severe storms.