Register here: https://harvard.zoom.us/meeting/register/tJcucO6srDgoGN1GFfS3HDyt57ah23r003CJ

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Abstract

Chemical reanalysis is a systematic approach to create a long-term data record of atmospheric composition, consistent with model processes and observations, using data assimilation. Chemical reanalysis has made considerable progress in recent years and offers unique global coverage of decadal trends during the satellite data records for studies of atmospheric composition variability. In this talk, I will discuss the following recent chemical reanalysis results from multi-constituent data assimilation using multiple data sets of ozone, CO, NO₂, HNO₃, and SO₂ from the multiple satellite sensors:

(1) An updated global chemical reanalysis data set of multi-constituent concentration and emission fields, the Tropospheric Chemistry Reanalysis version 2 (TCR-2), was produced for the period 2005–2020. The consistent concentration and emission data products provide unique information on decadal changes in the atmospheric environment. The reanalysis fields have been used to understand the processes controlling air pollution, for instance, during the KORUS-AQ campaign. Our results show the important balance of dynamics and emissions both on pollution and the assimilation system performance. Intercomparisons of multiple chemical reanalysis products are conducted under IGAC TOAR-II.

(2) The estimated emissions can be employed for the elucidation of detailed distributions of the anthropogenic and biomass burning emissions of co-emitted species in all major regions. For instance, anthropogenic NOx emissions dropped by at least 18 to 25% regionally during the worldwide COVID lockdowns in 2020, which decreased the global total tropospheric ozone burden by up to 2%. COVID-19 mitigation left a global atmospheric imprint that altered atmospheric oxidative capacity and climate radiative forcing due to ozone, CH4, and aerosols. Our analysis provides a test of the efficacy of emissions controls for co-benefiting air quality and climate.

(3) We also explored the potential of chemical reanalysis for the evaluation of multi-model simulations from ACCMIP and CCMI, in order to provide regionally and temporally representative model performance and to ensure more accurate predictions for the chemistry-climate system as emergent constraints. Chemical reanalysis can play a crucial role in assessing the changes and efficacy of short-lived climate pollutants (SLCP), that are an increasingly important component of greenhouse gas budgets, and evaluating climate model simulations.

(4) The importance of forecast model performance on chemical data assimilation has been investigated using three different chemical transport models that include GEOS-Chem. Harnessing assimilation increments in both NO_x and ozone, we show that the sensitivity of ozone to NO_x emissions varied by a factor of 2 for end-member models, revealing fundamental differences in the representation of fast chemical and dynamical processes. Recent progress toward a GCHP-based chemical data assimilation system will also be addressed.

(5) The new capability of satellite instruments provides detailed spatial and temporal patterns for various species. Multispectral retrievals from the NASA TRopospheric Ozone and its Precursors from Earth System Sounding (TROPESS) including CrIS/TROPOMI, AIRS/OMI, TES/OMI along with IASI- GOME-2 provide improved vertical sensitivity to the lower troposphere, whereas geostationary satellite measurements from GEMS, TEMPO, and Sentinel-4 provide hourly observations at high spatial resolution. These observations have great potentials to constrain both local pollution and global background ozone in conjunction with chemical data assimilation.