ReFRACtor: Reusable Software Framework for Retrieval of Satellite Atmospheric Composition
Abstract
Over the last ten years, during NASA's Earth Observing Systems (EOS) era, epitomized by the Aura, Aqua and Terra platforms, a wealth of Earth science observations have been and continue to be collected. During this period, retrieval methodologies for atmospheric composition have matured considerably. EOS missions such as TES (Bowman et al. 2006), OCO-2 (Boesch et al. 2015), OMI (Liu et al, 2010), AIRS (Warner et al, 2010), MOPITT (Deeter et al. 2003), and MLS (Livesey et al. 2004) all use the optimal estimation retrieval approach (Rodgers, 2000), thus creating a defacto standard method of deriving atmospheric composition products from Earth observations. Yet, each science team continues to rebuild these models and techniques with software that is useful only to their particular mission and consequently cannot be readily adapted to new Decadal Survey or Earth Venture missions, e.g., GeoCarb. The Reusable Framework for Retrieval of Atmospheric Composition (ReFRACtor) initiative aims to provide an extensible multi-instrument atmospheric composition radiative transfer and retrieval framework that enables software reuse while also improving science. This framework will be reusable and extensible allowing different instrument teams to use the same code base. It will help reduce the cost and risk of L2 development for new atmospheric Earth science missions. Secondly, it supports the data fusion of radiance measurements from multiple instruments through joint retrievals. The framework will be multi-instrument not only in the sense that different instruments can use the same software, but also in the sense that data products can be enhanced from multiple instruments through joint retrievals.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A11F2282M
- Keywords:
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- 0322 Constituent sources and sinks;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 1910 Data assimilation;
- integration and fusion;
- INFORMATICSDE: 1986 Statistical methods: Inferential;
- INFORMATICSDE: 3260 Inverse theory;
- MATHEMATICAL GEOPHYSICS