Advancing Regional Air Quality and Atmospheric Composition Analysis: Introducing the TRACER-1 Tropospheric Chemistry and Emissions Reanalysis

Regional air quality (AQ) and atmospheric composition (AC) have significant impacts on human health, the economy, and climate change. Model simulations are vital for understanding regional AQ/AC as in situ monitoring has large spatiotemporal voids. However, accurate predictions of regional AQ/AC are challenging due to the vast spatial and temporal variations in emissions and distribution of atmospheric trace gases and aerosols that arise from large variability in chemical production, removal, and local meteorological conditions. To investigate regional-to-sub-regional AC/AQ, this study focuses on the development of the Tropospheric Regional AC and Emissions Reanalysis (TRACER-1) dataset for the continental United States (CONUS) using a state-of-the-art forecast and assimilation system. We use the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and the Data Assimilation Research Testbed (DART) ensemble assimilation system to prepare the reanalysis from 2005-2024. To obtain the optimal estimate of AC states at every assimilation cycle, we assimilate a comprehensive range of in situ and satellite AC observations that will include AIRNOW surface observations and total/partial column and/or profile retrievals of CO, O₃, NO₂, SO₂, aerosol optical depth (AOD), and nitric acid (HNO₃) from MOPITT, MODIS, OMI, SCIAMACHY, GOME-2, and TES. The regional reanalysis is initiated with chemical IC/BCs from NASA Jet Propulsion Laboratory’s Multi-mOdel Multi-cOnstituent Chemical data assimilation (MOMO-Chem) global reanalysis and NCAR’s Whole Atmosphere Community Climate Model. We update emission estimates iteratively using a state augmentation approach during each assimilation cycle. We will present preliminary results from TRACER-1 for the AQ/AC reanalysis sensitivity experiments along with case studies to highlight the capabilities of the TRACER-1 framework. The TRACER-1 dataset is a significant step forward towards quantifying long-term tropospheric AQ/AC trends, investigating the nexus between regional AQ and climate change, and evaluating AQ and public health impacts during extreme air quality incidents.