PNNL

The Science

Aerosol optical depth (AOD) is a measure of how much aerosol particles prevent direct sunlight from reaching the ground. AOD products are typically provided by several potentially different instruments and often have different accuracies and temporal resolutions. Generating a high temporal resolution merged dataset for a twenty-one-year period (1997-2018) using data from four ground-based instruments deployed at the Southern Great Plains atmospheric observatory helps preserves the advantages (high quality) and reduces the disadvantages (patchy records) of the individual datasets. This generation addresses: (1) the varying data quality and resolutions of individual AOD records and (2) the uncertainty of the merged AOD data and its relevance for users.

The Impact

Merging this first-of-its-kind AOD dataset with other products can help provide a comprehensive picture of how aerosol loading relates to specific climate-associated factors. For example, combining this dataset with wildfire data would make it possible to correlate AOD changes with wildfire history and improve our understanding of the relationship between wildfires and aerosol burdens. Furthermore, using the AOD dataset in concert with surface radiation information could help reduce the uncertainties in radiative forcing over different time scales due to aerosol perturbations.

Summary

AOD measurements from individual instruments can be considered as a group of records with overlapping time intervals. Combining these records into a single product can give AOD data with excellent time continuity compared with measurements from a single instrument. This work demonstrates how to straightforwardly obtain the combined AOD and its uncertainty using an intuitively understandable approach that focuses on user-specified needs for the first time.

The combined two-decadal dataset successfully builds on the accuracy of the individual AODs, their extended measurement duration, and their high temporal resolution. Thus, this dataset—with its clear data format and public access—will allow users to analyze the variability of aerosol loading over a range of time scales and demonstrate the importance of this variability in forcing climate change. An additional benefit for researchers is that the combined AOD dataset can be aggregated to coarser time scales (e.g., daily, monthly, or annual averages) to become consistent with those used in model predictions and other relevant data products.

PNNL Contact

Evgueni Kassianov, Pacific Northwest National Laboratory, Evgueni.Kassianov@pnnl.gov 

Funding

This research was supported by the Office of Science of the U.S. Department of Energy as part of the Atmospheric Radiation Measurement user facility.