Aerosol single scattering albedo (SSA) is a key parameter for evaluating aerosol radiative effects and identifying aerosol type. However, current satellite-based SSA retrievals are both limited and subject to high uncertainty, while more accurate ground-based observations suffer from insufficient global coverage. Here we apply an Ensemble Kalman Filter (EnKF) data synergy technique to generate two monthly mean SSA datasets over land by synergizing OMI and POLDER data with AERONET observations. These two datasets are referred to as Merged-OMI and Merged-POLDER. The two datasets are available in NETCDF4 format, spanning latitudes from -89.5° to 89.5° and longitudes from -179.5° to 179.5°, at 1° spatial resolution. The Merged-OMI dataset provides SSA at 440 nm from October 2004 to December 2023, while the Merged-POLDER dataset includes SSA at 440, 550, 670, 865, and 1020 nm from March 2005 to December 2013.
Data sourced from Zenodo website https://zenodo.org/records/15268786 .
This data application uses ensemble Kalman filtering (EnKF) data fusion technology to combine OMI and POLDER data with AERONET observation results to generate two land monthly average single scattering albedo (SSA) datasets.
The data quality is good.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.ZENODO.DB7081.2026
10.5281/zenodo.15268786
