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Since the fall of 2004, the Ozone Monitoring Instrument(OMI) has been providing global monitoring of volcanic SO2 emissions,helping to understand their climate impacts and to mitigate aviationhazards. Here we introduce a new-generation OMI volcanic SO2 datasetbased on a principal component analysis (PCA) retrieval technique. To reduceretrieval noise and artifacts as seen in the current operational linear fit(LF) algorithm, the new algorithm, OMSO2VOLCANO, uses characteristicfeatures extracted directly from OMI radiances in the spectral fitting,thereby helping to minimize interferences from various geophysical processes(e.g., O3 absorption) and measurement details (e.g., wavelength shift).To solve the problem of low bias for large SO2 total columns in the LFproduct, the OMSO2VOLCANO algorithm employs a table lookup approach toestimate SO2 Jacobians (i.e., the instrument sensitivity to aperturbation in the SO2 column amount) and iteratively adjusts thespectral fitting window to exclude shorter wavelengths where the SO2absorption signals are saturated. To first order, the effects of clouds andaerosols are accounted for using a simple Lambertian equivalent reflectivityapproach. As with the LF algorithm, OMSO2VOLCANO provides total columnretrievals based on a set of predefined SO2 profiles from the lowertroposphere to the lower stratosphere, including a new profile peaked at 13 km for plumes in the upper troposphere. Examples given in this studyindicate that the new dataset shows significant improvement over the LFproduct, with at least 50 % reduction in retrieval noise over the remotePacific. For large eruptions such as Kasatochi in 2008 (∼ 1700 kt total SO2) and Sierra Negra in 2005 (> 1100 DU maximumSO2), OMSO2VOLCANO generally agrees well with other algorithms thatalso utilize the full spectral content of satellite measurements, while theLF algorithm tends to underestimate SO2. We also demonstrate that,despite the coarser spatial and spectral resolution of the Suomi NationalPolar-orbiting Partnership (Suomi-NPP) Ozone Mapping and Profiler Suite(OMPS) instrument, application of the new PCA algorithm to OMPS dataproduces highly consistent retrievals between OMI and OMPS. The new PCAalgorithm is therefore capable of continuing the volcanic SO2 datarecord well into the future using current and future hyperspectral UVsatellite instruments

atmospheric measurement techniques

New-generation NASA Aura Ozone Monitoring Instrument (OMI) volcanic SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; dataset: algorithm description, initial results, and continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)