Impacts of Assimilating GOES‐16 ABI Channels 9 and 10 Clear Air and Cloudy Radiance Observations With Additive Inflation and Adaptive Observation Error in GSI‐EnKF for a Case of Rapidly Evolving Severe Supercells

Details

• Journal Title:
  Journal of Geophysical Research: Atmospheres
• Personal Author:
  Johnson, Aaron ; Wang, Xuguang ; Jones, Thomas
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; NSSL (National Severe Storms Laboratory) ; CIMMS (Cooperative Institute for Mesoscale Meteorological Studies)
• Description:
  The unprecedentedly high space and time resolution of infrared radiance observations from GOES-16 Advanced Baseline Imager (ABI) present an opportunity to improve analyses and short-term forecasts of rapidly evolving convective-scale processes such as the initiation and organization of severe supercell thunderstorms. Such a case is used for experiments aimed at better understanding the assimilation of ABI all-sky radiance observations in GSI-EnKF. Experiments assimilating ABI channel 10 are used to demonstrate and understand the impacts of implementing additive inflation and adaptive observation error for ABI radiance assimilation in GSI-EnKF. The experiments using channel 10 are then compared to experiments using ABI channel 9 and both channels together. The impact of additive inflation is to increase lead time of one of the two supercells by about 20 min, and to enable improved prediction of the second supercell. The improvement occurs because the development of deepening cumulus is accelerated where ABI observes clouds to appear that are not present in the ensemble background forecast. The impact of the adaptive observation error is to increase the strength and persistence of the developing supercells in forecasts initialized from ensemble mean analyses. Compared to the ABI channel 10 radiance, ABI channel 9 provides 10 min of additional lead time for the second supercell, likely because it better constrains an upper-level shortwave in clear air.
• Keywords:
  Clouds Remote Sensing Thunderstorms Remote Sensing
• Source:
  JGR Atmospheres 127(11): e2021JD036157
• DOI:
  https://doi.org/10.1029/2021JD036157
• Document Type:
  Journal Article
• Funding:
  Grant no. NA16OAR4320115
• Rights Information:
  Other
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha256:593653f3c31668374e6e9417b4b980e0b1752c27baa20705e4c97b61b0315a9f
• Download URL:
  https://repository.library.noaa.gov/view/noaa/45378/noaa_45378_DS1.pdf
• File Type:
  [PDF - 3.77 MB ]