Data Assimilation & Prediction

(COMPLETED) Incorporating the GOES-R Geostationary Lightning Mapper Assimilation into the GSI for use in the NCEP global system

Project Period: July 1, 2014 to June 30, 2016
Principal Investigator(s): Milija Zupanski
Co-Principal Investigator(s): Karina Appodaca
Other Investigators: John Derber (NOAA/NCEP/EMC)

Sponsor(s): National Oceanic and Atmospheric Administration (NOAA)


The upcoming launch of GOES-R satellite with the Geostationary Lightning Mapper (GLM) instrument aboard will provide a unique opportunity to measure total lightning over land and oceans. Since lightning can be related to other model variables through the observation operator, the impact of lightning observations can be transferred via data assimilation to standard model variables such as pressure, temperature and wind. Lightning observations will be especially relevant over the oceans with scarce data available. As lightning is inherently related to storms, lightning observations over the oceans will provide unique information about the tropical cyclone environment. However, lightning observations have not been used in NOAA operations.


In the proposed work we plan to enhance the NCEP operational Gridpoint Statistical Interpolation (GSI) data assimilation system by adding lightning assimilation capability to GSI. We propose to


  1. adopt and optimize the GLM lightning observation operator that is suited for NOAA global data assimilation system (GDAS),
  2. incorporate the lightning observation operator in GSI, and
  3. evaluate the impact of assimilating GLM lightning observations.

This research is in synergy with several NOAA-sponsored projects conducted at CIRA that include JCSDA, HFIP, and GOES-R Risk Reduction.