E10 Exposing Long-Term Characteristics of Surface Air Quality through MERRA-2 Reanalysis Data

Monday, 29 January 2024
Hall E (The Baltimore Convention Center)
Suhung Shen, GMU and NASA GSFC, Greenbelt, MD; and B. Deshong, X. Pan, L. Iredell, J. Wei, and D. Meyer

This study aims to reveal and assess the long-term characteristics of the surface air quality, utilizing the reanalysis data from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). The investigation includes the understanding of the distribution of spatial data values and the global as well as regional patterns and variations in air quality. This research focuses on critical air quality indicators, including surface ozone, total PM2.5 (particulate matter with a diameter of 2.5 micrometers or smaller), and five components of fine particulate matter (PM2.5), which encompass black carbon, organic carbon, dust, sulfate, and sea salt.

In this study, a notable point of examination is the comparison between the data from the periods pre-EOS and post-EOS around the year 2000. During this period, changes were made to the way satellite aerosol observations were used in the assimilation system. By analyzing these distinct temporal segments, the research seeks to discern any consequential shifts or variations in air quality dynamics, particularly related to the changes in input satellite aerosol observations.

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is responsible for preserving MERRA-2 data and offering a range of data services tailored to users' diverse requirements. These services encompass tasks like selecting specific portions of data, online visualization, and analysis, accessing long time series data, and delivering online tutorials. This presentation will showcase how to effectively use these data tools and services.

The image illustrates the log10-scale total surface PM2.5 concentration averaged over 20 years from 2003 to 2022. This visualization was generated using Giovanni, an online tool available at GES DISC.


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