818 Assimilation of GOES ABI, CrIS-FSR, and Other New Radiance Data in RAP Version 5

Tuesday, 14 January 2020
Hall B (Boston Convention and Exhibition Center)
H. Lin, CIRA/Colorado State Univ. and NOAA/ESRL/GSD, Boulder, CO; and S. Weygandt, M. Hu, H. Wang, J. M. Brown, A. Back, C. Alexander, and S. G. Benjamin

Satellite radiance data have been shown to have consistent, statistically significant, positive impact within the Rapid Refresh (RAP) model system. The RAP uses the Gridpoint Statistical Interpolation (GSI) hybrid variational/Ensemble Kalman Filter (EnKF) data assimilation system, with ensemble information for the regional assimilation coming from the 80-member global ensemble data assimilation system.

We have recently finalized the next satellite assimilation upgrade package for the coming RAP version 5 (RAPv5) NCEP operation upgrade (planned for spring 2020). This RAPv5 radiance upgrade package includes the assimilation of the GOES-16 Advanced Baseline Imager (ABI) infrared radiance data, the Cross-track Infrared Sounder Full-Spectral-Resolution (CrIS-FSR) data both from S-NPP and NOAA-20, and the Advanced Technology Microwave Sounder (ATMS) data from NOAA-20. The evaluation of ABI O-B bias and standard deviation for different cloud mask and different surface within the RAP domain is performed. Research work associated with error tuning and quality control has been conducted through hourly RAP retrospective runs with forecast verification to maximize the ABI data impact. The RAP ABI assimilation work began with the three water vapor channels (channels. 8-10) and will be expanded to include a total of 9 infrared channels (excluding the ozone channel). We also plan to expand the ABI assimilation work into the High-Resolution Rapid Refresh (HRRR).

The direct broadcast/readout data with lower data latency are critical to the hourly updating RAP/HRRR models with the short cutoff time. The data impact from assimilation of the direct broadcast/readout CrIS-FSR and ATMS data is also evaluated for the RAP model and the subsequent HRRR model (starting from HRRR/Alaska) through a series of extensive retrospective experiments. In addition, we are examining the data usage/coverage improvements and overall forecast skill impacts from use of the direct readout feeds with the short-term forecast verification against the traditional radiosonde observations as well as the CrIS observed radiance observations.

A series of RAP retrospective runs has been conducted to evaluate the forecast impact from the new change and/or new instruments/data separately and/or combined together. At the conference, we will present these results and report on progress to date in all aspects of satellite radiance assimilation updates for the RAPv5.

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