Characterization of Particle Size Distribution Uncertainties using SAGE III/ISS Extinction Spectra

Characterization of Particle Size Distribution Uncertainties using SAGE III/ISS Extinction Spectra

A new algorithm was developed to infer particle size distribution parameters from the Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) extinction spectra using a lookup table (LUT) approach. Here, the SAGE-based extinction ratios were matched to LUT values and, using these matches, weighted statistics were calculated to infer the median particle size distribution values as well as quantify the uncertainty in these estimates. This was carried out by solving for both single and bimodal lognormal distributions. The work presented herein falls under 2 general headings: 1. a theoretical study was carried out to determine the accuracy of this methodology; 2. the solution algorithm was applied to the SAGE III/ISS records with a brief case study analysis of the 2022 Hunga Tonga eruption.

Monthly zonal median radii in the months following the Hunga Tonga eruption.

Monthly zonal median radii in the months following the Hunga Tonga eruption.

Image Source:

Knepp, T. N., Kovilakam, M., Thomason, L., and Miller, S. J.: Characterization of Particle Size Distribution Uncertainties using SAGE II and SAGE III/ISS Extinction Spectra, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2023-207, in review, 2023.


Spatial Coverage:

Global


Temporal Coverage:

June 2017 - February 2024


Instruments Used

SAGE III

Platform Type Platform Relevant Instrument Study Area

Satellite

ISS

SAGE III

Aerosols


Access Data

doi.org/10.5067/ISS/SAGEIII/PSD_L2-V1.1

Data Files:

https://xfr139.larc.nasa.gov/Data-In-Action/SAGE-PSD

Downloading Scripts Examples


Relevant Publications

Knepp, T. N., Kovilakam, M., Thomason, L., and Miller, S. J.: Characterization of Particle Size Distribution Uncertainties using SAGE II and SAGE III/ISS Extinction Spectra, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2023-207, in review, 2023.