Towards a Seamless Global Aerosol Dataset for Generating a Long-Term Earth Radiation Budget Climate Data Record

Abstract:

Improved climate prediction requires an understanding of the processes controlling the flow of energy within the Earth-atmosphere system. This in turn requires an accurate description of how radiant energy is distributed at the top-of-atmosphere (TOA), within the atmosphere, and at the surface for a range of time and space scales. A central objective of the Clouds and the Earth’s Radiant Energy System (CERES) is to produce a long-term climate data record of Earth’s radiation budget. CERES relies on a number of data sources, including broadband radiometers, high-resolution spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. While TOA radiation budget is largely determined directly from accurate broadband radiometer measurements, the surface radiation budget is derived indirectly through radiative transfer model calculations initialized using imager-based retrievals and assimilation data. In order to accurately characterize surface radiation budget variations from interannual to decadal timescales, it is paramount that the input stream be free of artificial jumps associated with instrument and/or algorithm changes. Otherwise, distinguishing real climate system changes from artifacts in the data record will be exceedingly difficult.

CERES instruments are currently flying on Terra (1999), Aqua (2002) and Suomi-NPP (2011) satellites. Aerosol retrievals for CERES Terra and Aqua data products are inferred from the MODIS imager. The aerosol retrievals are directly averaged over CERES footprints when the CERES level-2 products are created, and ingested into an aerosol assimilation system for generating computed Level-3 surface fluxes. The prime dataset for Terra and Aqua aerosol retrievals are generated from the MODIS Atmosphere team at NASA GSFC. In order to ensure consistency with MODIS, our current plan is to eventually adapt the MODIS algorithm to VIIRS imager radiances in order to minimize algorithm changes between the satellites.

This presentation will discuss the importance and challenges of using input datasets that seamlessly transition across multiple platforms flying CERES instruments with special emphasis on aerosols and surface radiation budget.