A New Paradigm in Model Data Fusion for the Atmosphere Observation System Constellation

Andrew Gettelman, NCAR, Boulder, CO; and A. M. da Silva, D. J. Posselt, and G. R. Carmichael
[09-Jan-2023] Abstract  Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g. data assimilation) and some are single purpose and customized (e.g. for model validation). Here we discuss how best practices for integrating models and observations are being integrated into the development of the NASA led Atmospheric Observation System, an international constellation of earth orbiting satellites designed to advance our understanding and prediction of clouds, aerosols, precipitation and climate. We highlight how AOS measurements, integrated with models, can improve predictions of the earth system (including atmosphere, land surface, oceans, cryosphere and chemistry) across scales from weather to climate. To achieve this improvement and maximize the return on investment in our observation systems, we need to take a more holistic, integrated and coordinated approach to models, observations and their uncertainties, in order to maximize the benefit for Earth system prediction and impacts on society.