Chemical Reanalysis Products

Overview

This web page provides access to a 15-year (2005-2021) global data set of the chemical concentrations O3, NO2, CO, SO2, OH, NO, HNO3, CH2O, PAN, and Aerosols (sulfate, NH3, NH4) and emissions of NOx, CO, and SO2 that are important for air quality and climate.

Products
Publications

What is chemical reanalysis?

Chemical reanalysis a technique that combines observational information from multiple satellite sensors and provides comprehensive information on tropospheric composition variations. In our chemical reanalysis developed at JPL, multi-constituent measurements of O3, NO2, CO, HNO3, and SO2 from the OMI, GOME-2, SCIAMACHY, MLS, TES, and MOPITT satellite instruments were assimilated into a global chemical transport model using an ensemble Kalman filter technique. The methodology is explained in our publications (Miyazaki et al., 2015, 2017, 2019, 2020a, 2020b). The current product has strong observational constraints, especially on ozone and NOx emissions.

Figure 1: Schematic picture
Figure 1: Schematic picture of multi-constituent data assimilation used in the chemical reanalysis
Figure 2: Time series of assimilated satellite measurements
Figure 2: Time series of assimilated satellite measurements

What’s available?

Time period 2005-2021
Horizontal resolution 1.1°×1.1°
Vertical layers 27 pressure levels from 1000 to 60 hPa
Temporal resolution Two-hourly, six-hourly, or monthly
Variables
  • Meteorological fields: u, v, t, q, ps
  • Chemical concentrations: O3, NO2, CO, SO2, OH, NO, HNO3, CH2O, PAN, Aerosols (sulfate, NH3, NH4)
  • Emissions: NOx, CO, SO2, and lightning NOx
  • Model and data assimilation diagnostics

For chemical concentrations, we provide data for species that are already validated against independent observations (Miyazaki et al., 2020b).

How is this useful?

Chemical reanalysis data sets have great potential to contribute to studies that could improve the understanding of the processes controlling the atmospheric environment and their roles in changing climate. For example:

  • The consistent concentration and emission data provide comprehensive information on atmospheric composition variability from regional to global scales
  • The reanalysis data provide initial and boundary conditions for climate and chemical simulations
  • The emission data can be used to study emission variabilities and to evaluate bottom-up emission inventories from seasonal to decadal scales

The uncertainty information and know issues of the current product are described in Miyazaki et al. (2020b) based on comparison against independent observations.

Expected applications

  • The data sets have great potential to contribute to studies that improve the understanding of atmospheric composition variability at daily to decadal scales, the processes controlling the atmospheric environment, and their roles in changing climate
  • It can also be used as initial and boundary conditions for climate and chemical simulations
  • The emission products can be used to study emission variabilities and to evaluate bottom-up emission inventories

What is going on?

  • The chemical reanalysis products will continue to be updated using the latest satellite observations.
  • Comparisons against other reanalysis products, including CAMS and MERRA-2 reanalyses, have been made (Huijnen et al., 2019; Park et al., 2020; Elguindi et al., 2020; Ryu and Min, 2020) and will further be updated.
  • To improve the quality and capability of chemical reanalysis for various applications, additional observational constraints will be added by assimilating the recently developed advanced satellite data, such as multi-spectral tropospheric ozone retrievals from AIRS/OMI (Fu et al., 2018; Miyazaki et al., 2019).
  • The multi-model multi-constituent chemical data assimilation (MOMO-Chem) framework provides possible uncertainty ranges in the reanalysis fields due to model errors, which are quantified, for instance, in 4 %–31 % for NOx and 13 %–35 % for CO regional emissions. This information will be used to evaluate reanalysis uncertainty.
  • A next generation chemical reanalysis is being developed using a more advanced chemical data assimilation system and will be updated on this website.

Dataset Citation and DOI

Miyazaki, K., Bowman, K., Sekiya, T., Eskes, H., Boersma, F., Worden, H., Livesey, N., Payne, V. H., Sudo, K., Kanaya, Y., Takigawa, M., and Ogochi, K., (2019). Chemical Reanalysis Products. Jet Propulsion Laboratory. https://doi.org/10.25966/9qgv-fe81

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