Improving NCEP Global Aerosol Forecasts by Data Assimilation of VIIRS Aerosol Products

Aerosols have been recognized as an influential factor affecting climate, weather and air quality. Currently, most operational centers (e.g., ECMWF, JMA, and UKMO, etc.) already have aerosol forecast capabilities to eventually take the feedback of aerosols with radiation/cloud into account. On the other hand, aerosol data assimilation (DA) has also been developed at many operational centers to improve the aerosol predictions. The NEMS Global Forecasting System (GFS) aerosol component (NGAC) was implemented into NCEP operation in September 2012. It’s until now a Gridpoint Statistical Interpolation (GSI) three dimensional variational (3DVAR) data assimilation (DA) system has been used in NGAC. This study will evaluate the improvement of NGAC aerosol forecasts based on DA system.

In the aerosol analysis system, NGAC simulations are the first guess. They are also utilized for the background error statistics calculation via NMC method. Aerosol Optical Depth (AOD) Enterprise Algorithm measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS, on board the S-NPP) are used as input observations. The AOD product for every model layer is achieved by the operator which developed with Community Radiative Transfer Model (CRTM) in GSI system. Ultimately, this aerosol DA system will be used to feed operational purpose of NCEP. The primary results with and without DA will be demonstrated by comparing with observations from Aerosol Robotic Network (AERONET) in selected time period.