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New algorithm improves observation of sulfur dioxide in the atmosphere by OMI

Ozone Monitoring Instrument can detect sulfur emissions from volcanoes and fossil-fuel power plants

New algorithm improves observation of sulfur dioxide in the atmosphere by OMI

Fig. 3 from Li et al. (2013), comparing the two PBL SO2 algorithms. Images depict monthly mean SO2, August 2006, over the eastern United States: (left) PCA algorithm data; (right) BRD algorithm data. Circles indicate locations of known sources of SO2.

New algorithm improves observation of sulfur dioxide in the atmosphere by OMI

The Goddard Earth Sciences Data and Information Service Center (GES DISC) has now made available for the new Ozone Monitoring Instrument (OMI) SOPlanetary Boundary Layer (PBL) Level 2 data product (OMSO2).

Although one of the primary goals of the Ozone Monitoring Instrument (OMI) on the National Aeronautics and Space Administration (NASA) Aura satellite is to quantify the concentration and distribution of ozone in the atmosphere, this versatile instrument is also capable of detecting other trace gases. Two of these gases, nitrogen dioxide (NO2) and sulfur dioxide (SO2), are produced by both natural and human (anthropogenic) processes. NO2 results from high-temperature combustion, so it stems from wildfires, as well as the tailpipes of automobiles and the effluent stacks of thermal power plants. SO2 is produced when sulfur-containing fossil fuels (primarily coal) are burned for energy, but large amounts of SO2 can also be released to the atmosphere by volcanic eruptions. One reason climate scientists are interested in volcanic SO2 in the atmosphere is that major volcanic eruptions can inject sufficient SO2 into the stratosphere and form sulfate aerosols that block sunlight and temporarily cool the planet’s temperature.


The OMI science team has recently released a new version of the OMI SO2 Planetary Boundary Layer (PBL) data product, ColumnAmountSO2_PBL. This data product is based on a new data processing method that involves Principal Component Analysis (PCA). In addition, erroneous data induced by the OMI “row anomaly”, which occurs when the instrument is acquiring data, are now assigned a fill-value, making it more convenient for data users to exclude those measurements.  Note:  The OMSO2 data product, described below, contains four ColumnAmount SO2 data products, each of which is generated by an algorithm that is optimized for a specific layer of the atmosphere.


The PCA algorithm for OMI SO2 PBL data replaces the Band Residual Difference (BRD) algorithm and is most suitable for air quality-related research and applications. It should be noted that this product is a retrieval of SO2 total column density throughout the whole atmosphere, and PBL refers to the a priori profile assumed in this product. This profile has SO2 predominately in the PBL. The BRD algorithm was successful at detecting low concentrations of SO2, but it tended to produce noisy data and was prone to biasing at high latitudes. The new algorithm significantly improves the quality of the SO2 PBL data. Users who have previously acquired the OMI SO2 produced by the BRD algorithm are now urged to download the SO2 data produced with the PCA algorithm.


The new PCA algorithm is fully described in the OMSO2Readme_V120_20140926 document, which includes suggestions for users regarding the use of the data quality flag and methods that can be used for data filtering. The ReadMe document notes that the best quality data are acquired from the center of the OMI scanning swath, because data from the swath edges exhibit more noise. The algorithm may also occasionally overestimate SO2 concentrations over remote oceanic regions, when pollution or volcanic plumes with sizable SO2 above the planetary boundary layer travel to these regions via long-range transport.


Three other OMI SO2 data products are more suited for the observation of volcanic SO2 in the atmosphere. ColumnAmountSO2_TRM is optimized for the normal release of SO2 from mountain volcanoes (above 5 km altitude). ColumnAmountSO2_STL is for powerful volcanic eruptions that inject a large cloud of SO2 into the upper troposphere or stratosphere. ColumnAmountSO2_TRL is useful for quantifying SO2 emissions from degassing volcanoes.


Product Description 


The OMSO2 data product is written as an HDF-EOS5 swath file. Data files are available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). For a list of tools that read HDF-EOS5 data files, please visit


Each OMSO2 file contains SO2 and associated information retrieved from an OMI scene from the sun-lit portion of an Aura orbit. The data are ordered in time sequence. The associated information includes latitude, longitude, solar zenith angle, OMTO3 reflectivity (LER), and independent estimates of the SO2 vertical columns, as a well as a number of ancillary parameters that provide information to assess data quality. Four values of SO2 column amounts are provided, corresponding to the four assumed vertical profiles (ColumnAmountSO2_PBL, ColumnAmountSO2_TRM, ColumnAmountSO2_STL, and ColumnAmountSO2_TRL) Independent information is needed to decide which value is most applicable. For a complete list of the parameters, please read the OMSO2 file specification.

For general assistance with the data archive, please contact the GES DISC ( For questions and comments related to the OMSO2 algorithm and data quality, please contact Nickolay Krotkov (, who has the overall responsibility for this product, with a CC: copy to Can Li (


Definition: The planetary boundary layer (PBL) is the lowest part of Earth’s atmosphere. In this part of the atmosphere, winds are affected by friction with the Earth surface, and the temperature and moisture content of the air vary rapidly. The top of the PBL can range from < 100 meters to 3,000 meters above the surface of the Earth.


Reference: Li, C., J. Joiner, N. A. Krotkov, and P. K. Bhartia (2013), A fast and sensitive new satellite SO2 retrieval algorithm based on principal component analysis: Application to the ozone monitoring instrument, Geophys. Res. Lett., 40, doi:10.1002/2013GL058134.



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Last updated: Sep 23, 2015 10:50 AM ET