Capability Demonstration of a JEDI‐Based System for TEMPO Assimilation: System Description and Evaluation
Year: 2026
Type: article
Abstract: The launch of the Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission in 2023 marked a new era in air quality monitoring by providing high‐frequency, geostationary observations of column NO 2 across most of North America. In this study, we present the first implementation of a TEMPO NO 2 data assimilation system using the Joint Effort for Data assimilation Integration (JEDI) framework. Leveraging a four‐dimensional ensemble variational (4DEnVar) approach and an Ensemble of Data Assimilations (EDA), we demonstrate a novel capability to assimilate hourly NO 2 retrievals from TEMPO alongside polar‐orbiting TROPOspheric Monitoring Instrument (TROPOMI) data into NASA's GEOS Composition Forecast (GEOS‐CF) model. The system is evaluated over the CONUS region for August 2023, using a suite of independent measurements including Pandora spectrometers, AirNow surface stations, and aircraft‐based observations from Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) and Synergistic TEMPO Air Quality Science (STAQS) field campaigns. Results show that the assimilation system successfully integrates geostationary NO 2 observations, improves model performance in the column, and captures diurnal variability. However, assimilation also leads to systematic reductions in NO 2 levels, which improves agreement with some data sets (e.g., Pandora, AEROMMA) but degrades comparisons with others (e.g., STAQS). These findings highlight the importance of joint evaluation across platforms and motivate further development of dual‐concentration emission assimilation schemes. While the system imposes high computational costs, primarily from the forecast model, ongoing efforts to integrate AI‐based model emulators offer a promising path toward scalable, real‐time assimilation of geostationary atmospheric composition data.
DOI: 10.1029/2025ms005482
Authors: Maryam Abdi-Oskouei, Jérôme Barré, Shih-Wei Wei, Cheng-Hsuan Lu, Ashley Griffin, Clementine Hardy Gas, Francois Hebert, Stephen Herbener, Eric Lingerfelt, Evan Parker, Christian Sampson, Steven Vahl, Fabio L. R. Diniz, Benjamin Johnson, Cheng Dang, Yannick Tremolet, Benjamin Ruston, Viral Shah, K. Emma Knowland, Ricardo Todling, Ronald Gelaro, Caroline R. Nowlan, Gonzalo González Abad, Xiong Liu, Brian McDonald, Eleanor Waxman, Andrew W. Rollins, Kristen Zuraski, Jeff Peischl, Laura Judd, Lukas C. Valin, Thomas F. Hanisco, Benjamin Menetrier, Cory Martin, Daniel Holdaway, Anna Shlyaeva, Dominikus Heinzeller, Steven Pawson, Thomas Auligné
Institutions: Goddard Space Flight Center, University Corporation for Atmospheric Research, State University of New York, University at Albany, State University of New York, National Aeronautics and Space Administration, Morgan State University, Smithsonian Institution, Harvard University, Center for Astrophysics Harvard & Smithsonian, NOAA Chemical Sciences Laboratory, National Oceanic and Atmospheric Administration, NOAA Earth System Research Laboratory, Quantinuum (United Kingdom), Quantinuum (United States), Langley Research Center, Environmental Protection Agency, NOAA Environmental Modeling Center, NOAA Office of Modeling and Development
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,650
OpenAlex ID: W4414592489