Extending the Earth Observing System Capability into the ITM: OSSEs in the Whole Atmosphere Models
Abstract
In the forthcoming decade the Ionosphere-Thermosphere-Mesosphere (ITM) domain of the Earth Observing System (EOS) will be an exciting frontier for the data-constrained analysis and forecasting in the operational and research whole atmosphere models. As expected, the current and planned ITM space-borne missions along with the ground-based network will provide the complimentary set of observations of optical emissions, winds, temperature, density, neutral composition and plasma to evaluate and constrain the whole atmosphere-ionosphere model predictions. The whole atmosphere models can properly accept the solar-geomagnetic inputs at the top boundary and ingest the observed meteorology of Numerical Weather Prediction (NWP) systems between the surface and ~40-50 km, providing a link between terrestrial and space weather predictions. Assimilation of the research ITM data (emissions and retrieved quantities) that are not ingested in the NWP systems will further improve WA predictions above the stratopause. We will discuss a design of OSSE/OSE studies in the ITM relying on the community (WACCM-X) and operational (WAM-IPE) models with observed solar-geomagnetic inputs and the meteorology of NWP systems of NOAA (Global Forecast System) and NASA (Goddard Earth Observing System of GMAO) to represent the so-called "Nature Run" atmosphere-ionosphere state and to extend operational EOS workflows into the ITM. Performance of OSSEs will enhance the anticipated science return of new mission by suggesting the optimal ITM observing strategies during the mission development and synergizing novel and existing observations. The challenges of the ITM data analysis, including the direct assimilation of the thermospheric emissions, will be discussed along with the adaptation of data assimilation algorithms that require the rapid ingestion of diverse observations to constrain the fast ITM dynamics in the entire whole atmosphere domain.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFMSM25C1991Y