Department Seminar: Kazuyuki Miyazaki
Title: Global tropospheric chemistry reanalysis and emission estimates using multi-constituent satellite observations
Abstract: Global tropospheric chemistry reanalysis is a systematic approach to create a long-term global data record of atmospheric composition, consistent with chemical transport 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 and emission variability. At JPL, 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 using multiple data sets of ozone, CO, NO2, HNO3, and SO2 from multiple satellite sensors. Intercomparisons of multiple chemical reanalysis products, including TCR-2 and CAMS, are conducted under the IGAC TOAR-II project. 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. Meanwhile, 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%. Our analysis provides a test of the efficacy of emissions controls for co-benefiting air quality and climate.
The importance of forecast model performance on chemical data assimilation has been investigated using multiple chemical transport models that include GEOS-Chem. The multi-model data assimilation framework provides possible uncertainty ranges in data assimilation due to model errors. We also showed that the sensitivity of ozone to NOx emissions varied by a factor of 2 for end-member models, revealing fundamental differences in the representation of fast chemical and dynamical processes. Meanwhile, 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 potential to constrain both local pollution and global background ozone in conjunction with chemical data assimilation.