M2O2: Multi Mission Observation Operator
Principal Investigator (PI): Meemong Lee,, NASA's Jet Propulsion Laboratory
The goal of the Multi-Mission Observation Operator (M2O2) is to create a streamlined interface mechanism between the atmospheric chemistry model developers and the atmospheric sounding mission data providers by infusing mission-generic observation integration technologies developed under NASA's Advanced Information System Technology (AIST) program. M2O2 will address a major challenge in utilizing the space-based observations within the atmospheric chemistry modeling and assimilation community, which involves linking between the model analysis and the observed atmospheric state in the level 2 mission data products (L2 data). The state-of-the-practice is to develop an observation operator for each atmospheric component of an atmospheric sounding mission, which often involves laborious data preparation. A wide range of observation operators with their own ad-hoc ways of handling L2 data greatly hinders integration of observations from multiple missions. Developing a generic observation operator that provides the link between the model analysis and mission observations requires an automated "assimilation-purpose" data preparation service and representation coordinate transformation.
M2O2 will develop a model transformer that shields the cost function analysis process from the mission-specific L2 data and demonstrates the mission-generic global assimilation process for four types of space-based observations: ozone (O3), carbon monoxide (CO), carbon dioxide (CO2), and column carbon dioxide (x CO2). The global assimilation process will be delivered to the GEOS-Chem-Adjoint working group that maintains data assimilation services for atmospheric chemistry community. The M2O2 will also develop a data transformer to provide the model transformer "assimilation-purpose" L2 data, referred to as L2# data, by applying a set of information filters and quality-control filters. The data transformer will be integrated within the Goddard Earth System Data and Information Service Center (GES DISC) as a web-service for providing "on-demand" observation information from four types of atmospheric sounding missions: Microwave Limb Sounder (MLS), Tropospheric Emission Spectrometer (TES), Atmospheric Infrared Sounder (AIRS), and Orbiting Carbon Observatory-2 (OCO-2). The model transformer and the data transformer collectively perform as a mission-generic observation operator in the assimilation process, allowing the atmospheric chemistry modeling community to effectively utilize L2 data products
Our proposal directly addresses the needs identified by the Advancing Collaborative Connections for Earth Science Systems (ACCESS) announcement in following three areas:
1) Work with modeling and model analysis communities to effectively find, understand, and appropriately use Earth science observational data. M2O2 will allow the atmospheric chemistry modeling community to access space-based observations of O3, CO, CO2, and x CO2 as "assimilation-purpose" data products from GES DISC.
2) Automate the discovery of heterogeneous data meeting customizable criteria based on data content, data quality, metadata, and production. The M2O2-service will automatically apply assimilation-purpose data-quality control for three types of atmospheric constituents from four types of atmospheric sounding missions based on the observation conditions employing the meta data (e.g., cloud, aerosol optical depth).
3) Improve users' ability to mine useful information from distributed, large volumes of heterogeneous data. The M2O2 service will provide a uniform interface to heterogeneous L2 data products from four of NASA's Distributed Active Archive Denters (DAACs), reducing the transferred data volume and increasing the information content for global data assimilation of the respective atmospheric constituents.
L2# data service : Deployed by GES DISC
L2# assimilation service: Deployed by GEOS-Chem-Adjoint working group from multiple missions.
Last Updated: Feb 18, 2020 at 1:35 PM EST