Overview

This document describes the OMI SO₂ product (OMSO2) produced from global mode UV measurements of the Ozone Monitoring Instrument (OMI). OMI was launched on July 15, 2004 on the EOS Aura satellite, which is in a sun-synchronous ascending polar orbit with 1:45pm local equator crossing time. The data collection started on August 17, 2004 (orbit 482) and continues to this day with only minor data gaps. The minimum SO₂ mass detectable by OMI is about two orders of magnitude smaller than the detection threshold of the legacy Total Ozone Mapping Spectrometer (TOMS) SO₂ data (1978-2005) [Krueger et al 1995: http://toms.umbc.edu]. This is due to smaller OMI footprint and the use of wavelengths better optimized for separating O₃ from SO₂.

 

The product file, called a data granule, covers the sunlit portion of the orbit with an approximately 2600 km wide swath containing 60 binned pixels or scenes per viewing line. During normal operations, 14 or 15 granules are produced daily, providing fully contiguous coverage of the globe. Currently, OMSO2 products are not produced when OMI goes into the zoom mode for one day every 452 orbits (about 32 days).

 

Since 11 May 2008 signal suppression (anomaly) has been observed in Level 1B Earth radiance data for scene numbers 39-42 (unit based), but only for northern Latitudes (see OMI instrumental effects). The anomaly manifests itself as positive or negative stripes in SO2 data (discontinuity with cross-track viewing angle). It is recommended not to use the SO2 data for affected scene numbers in northern hemisphere.

 

For each OMI scene we provide 4 different estimates of the column density of SO₂ in Dobson Units (1DU=2.69 ∙10¹⁶ molecules/cm²) obtained by making different assumptions about the vertical distribution of the SO₂. However, it is important to note that in most cases the precise vertical distribution of SO₂ is unimportant. The users can use either the SO₂ plume height, or the center of mass altitude (CMA) derived from SO₂ vertical distribution, to interpolate between the 4 values:

 

·        Planetary Boundary Layer (PBL) SO₂ column (ColumnAmountSO2_PBL), corresponding to CMA of 0.9 km.

 

·        Lower tropospheric SO₂ column (ColumnAmountSO2_TRL), corresponding to CMA of 2.5 km.

 

·        Middle tropospheric SO₂ column, (ColumnAmountSO2_TRM), usually produced by volcanic degassing, corresponding to CMA of 7.5 km, 

 

·        Upper tropospheric and Stratospheric SO₂ column (ColumnAmountSO2_STL), usually produced by explosive volcanic eruption, corresponding to CMA of 17 km.

 

The accuracy and precision of the derived SO₂ columns vary significantly with the SO₂ CMA and column amount, observational geometry, and slant column ozone. OMI becomes more sensitive to SO₂ above clouds and snow/ice, and less sensitive to SO₂ below clouds. Preliminary error estimates are discussed below (see Data Quality Assessment). Details about software versions and known issues are available in the OMSO2ReleaseDetails file.

 

Algorithm Description

 

We use two different algorithms to produce SO₂ column data from OMI. The PBL columns are produced using the Band Residual Difference (BRD) algorithm [Krotkov et al 2006], while TRL, TRM and STL columns are produced with the Linear Fit (LF) algorithm [Yang et al 2007]. Both algorithms use a recently modified version (Version 8.5) of TOMS total ozone algorithm (OMTO3) [Bhartia and Wellemeyer 2002] as a linearization step to derive an initial estimate of total ozone assuming zero SO₂. (See OMTO3 README file for more detail). The residuals at the 10 wavelengths are then calculated as the difference between the measured and computed N-values (N=-100*log₁₀(I/F), I is Earth radiance and F is solar irradiance ) using a vector forward model radiative transfer code that accounts for multiple Rayleigh scattering, ozone absorption, Ring effect, and surface reflectivity, but assumes no aerosols. Cloudy scenes are treated as mixture of two opaque Lamberian surfaces, one at the terrain pressure and the other at Radiative Cloud Pressure (RCP) derived using OMI-measured Rotational Raman scattering at around 350 nm (see OMCLDRR README file for more detail). In the presence of SO₂, the residuals contain spectral structures that correlate with the SO₂ absorption cross-section. The residuals also have contributions from other errors sources that have not yet been identified. To reduce this interference, a median residual for a sliding group of SO₂-free and cloud-free scenes (OMTO3 radiative cloud fraction < 0.15) covering ±15^o latitude along the orbit track is subtracted for each spectral band and cross-track position [Yang et al 2007].

 

Both the BRD and LF algorithms use the corrected residuals as their inputs to derive SO₂ column amount. The BRD algorithm works best in presence of anthropogenically produced SO₂, since they do not affect the total ozone derived by the OMTO3 algorithm. This algorithm uses differential residuals at the three wavelength pairs with the largest differential SO₂ cross-sections to maximize sensitivity to anthropogenic emissions in the PBL. Each pair residual is converted to SO₂ slant column density (SCD) using differential SO₂ cross-sections data at constant temperature (275 K) [Bogumil et al 2003]. The SCDs of the three pairs are averaged and the average SCD is converted to the total SO₂ vertical column density (VCD) using a constant air-mass factor (AMF) of 0.36. This AMF was estimated for cloud- and aerosol-free conditions, using a solar zenith angle of 30^o, nadir viewing direction, a surface albedo of 0.05, a surface pressure of 1013.3hPa, a 325 DU mid-latitude ozone profile and a typical measured summer SO₂ vertical profile over the Eastern US. Krotkov et al [2008] provide an estimate of how the AMFs vary with observing conditions.

 

SO₂ produced by volcanic degassing and eruptions can produce large errors in OMTO3 derived total ozone and can make the retrieval highly non-linear. The linear Fit (LF) algorithm was developed to handle such cases. The LF algorithm minimizes different subsets of residuals by simultaneously adjusting total SO₂, ozone and includes a quadratic polynomial in the spectral fit. The subsets are determined by the process of dropping the shortest wavelength bands one at a time until the 322nm band is reached. The largest SO₂ retrieval is reported as the final estimate. The assumed gaseous vertical profiles correspond to the standard OMTO3 ozone profiles. The SO₂ weighting functions are approximated using OMTO3 layer Efficiency factors in Umkehr layers 0, 1 and 3, for ColumnAmountSO2_TRL, ColumnAmountSO2_TRM, and ColumnAmountSO2_STL data, correspondingly. Treatment of aerosols and clouds is the same as in the OMTO3 algorithm.

 

 

Data Quality Assessment

 

The sliding median empirical residual correction essentially acts as a high-pass filter reducing cross-track and low frequency latitudinal biases, but allowing high frequency (i.e. scene by scene) noise in the residuals to propagate into retrieved background SO₂ data. The resulted errors are best described as pseudo-random (i.e. having different systematic and random components depending on spatial and temporal scales) Gaussian-like distribution with a nominal mean of zero. The errors usually reduce much slower than the square root of the number of measurements averaged.

 

We provide separate Quality Flags (QF) for each of the products that are based on SO₂ consistency criteria between the individual wavelength pairs. The OMSO2 scene quality flag is an automatic assessment of the SO₂ values for the corresponding scene by the OMSO2 retrieval algorithm. It is used primarily as an indicator of the validity of the retrieved SO₂ values. A user of OMSO2 data is advised to examine the first bit of the quality flag. If this bit is equal to zero, the retrieved SO₂ value is likely to be good. But if it is equal to 1, this indicates that during the retrieval, the algorithm has determined that the scene does not exhibit characteristics that are consistent with the presence of SO₂. Also the quality flag includes other information, such the geometrical and geophysical conditions, that are relevant to the quality of SO₂ retrieval. For detailed information about the OMSO2 quality flag, please consult the OMSO2 file specification). Preliminary analysis of the QF values has shown that they work best for large volcanic events, but miss many real PBL and low level degassing emissions. Therefore, independent verification of the real SO₂ signal is strongly recommended. Below are data quality assessments for each SO₂ product after applying the sliding median empirical residual correction and ignoring QF. For all products the noise increases with increasing solar zenith angle at high latitudes and in the region of South Atlantic radiation Anomaly. 

 

ColumnAmountSO2_PBL: Due to reduced OMI sensitivity to SO₂ in PBL this product should be used only under optimal viewing conditions: radiative cloud fraction <0.2, solar zenith angle < 40^o and near-nadir viewing angles (cross track positions 20 to 40).  The noise standard deviation (sigma) is ~1.5 DU in the tropics, but increases with latitude, viewing and solar zenith angles and total ozone. Given this large noise only plumes from strong anthropogenic sources of SO₂ (such as smelters and coal burning power plants) and from strong regional pollution can be detected in scene data [Carn et al 2007a; Krotkov et al 2008]. Averaging over a larger area or for a longer time reduces the noise but slower than the square root of the number of scenes averaged. The sigma reduces to ~0.8 DU when 4 scenes are averaged and approaches 0.4 DU with increasing number of averaged scenes. The SO₂ detection limit is roughly twice of the 1 sigma noise.

 

The SO₂ retrieval accuracy depends on the uncertainty in both SCD and in average photon path, characterized by the error in assumed air-mass factor (AMF). The AMF error is systematic and increases with deviation of the observational conditions from those assumed in the operational algorithm. For cloud-free scenes, the AMF can be corrected using OMI slant column ozone (SCO) data as described in Krotkov et al [2008].  For large SCO values >1500 DU (i.e. high ozone and/or high solar zenith and viewing angles, mostly at high latitudes), the AMF becomes very small, so valid PBL SO₂ retrievals are not expected. In addition, aerosols and sub pixel clouds affect the AMF in different ways depending on their vertical distribution. Though clouds screen PBL SO₂, we have not attempted to correct for this effect. For this reason we do not recommend using this product when the radiative cloud fraction (RCF) exceeds 0.2. 

 

ColumnAmountSO2_TRL: Due to increased sensitivity to elevated SO₂, the 1 sigma noise in TRL data is reduced to ~0.7 DU under optimal observational conditions in the tropics. The data can be used for cloudy, clear and mixed scenes as well as for elevated terrain. However, the TRL data contain filled values when terrain pressure or RCP is less than ~500hPa. In such cases the cloud blocks most of the SO₂. As a result, the SO₂ weighting function approaches zero, no LF retrieval is done and the fill value is stored in the output.

 

ColumnAmountSO2_TRM are optimized for typical volcanic degassing from volcanoes with vents at ~5km altitude or above and emissions from effusive eruptions. The standard deviation of TRM retrievals in background areas is about 0.3 DU at low and mid-latitudes. The cloud-related fill values in TRM data occurs only when the OMI measured cloud top is higher than ~8-10 km. Biases in the TRM retrievals due to latitude and viewing angle are removed to the 0.1 DU level by the median residual background corrections. Both the bias and standard deviations increase with solar zenith angle. We recommend that the TRM retrievals be used for volcanic degassing cases at all altitudes because the PBL retrievals are restricted to optimal viewing conditions and TRL data are overestimated for high altitude emissions (>3km). In general, SO₂ releases at altitudes less than ~7.5 km will be underestimated, but these errors can be corrected off-line using the averaging kernel [Yaong et al 2007] if the actual SO2 vertical distribution is known.

 

Analysis of daily OMSO2 data for degassing volcanoes at high altitude (~5 km) has shown that significant trends in SO₂ burdens, linked to variability of source SO₂ emissions, can be detected [Carn et al., 2008a]. Preliminary surveys of global volcanic OMSO2 data indicate that the current sensitivity of the algorithm permits detection of volcanoes emitting on the order of 10³ tons SO₂/day or more in daily data (under optimal viewing conditions). Detection of weaker sources usually requires temporal averaging of the OMSO2 data.

 

 

ColumnAmountSO2_STL data are intended for use with explosive volcanic eruptions where the cloud is placed in the upper troposphere or stratosphere (UTLS).  At these altitudes the averaging kernel is weakly dependent on altitude, so that differences in actual cloud height from 17 km produce only small errors. The biases with latitude and viewing angle are generally less than 0.2 DU. The noise level in background data is about 0.2 DU. This sensitivity has permitted tracking of volcanic SO₂ clouds in the UTLS for great distances from the source [e.g., Carn et al., 2007b, Carn et al., 2008b]. Both the bias and standard deviation increase near the northern terminator, similar to but reduced from the TRM results. Artifacts due to ozone profile errors are reduced from the TRM data by about 30%. One should see no fill values due to cloud screening in the STL data.

 

The LF algorithm still has large error when it comes to high SO₂ loading cases.  The LF algorithm as implemented in the v1.1.1 OMSO2 is expected to provide good retrieval when SO₂ loading is less than  50 DU. When SO₂ loadings are higher than 100 DU the LF algorithm underestimates the true SO₂ amount, the higher the loading the larger the underestimation [Yang et al 2007]. Comparisons between total SO₂ burdens calculated using OMSO2 and EP-TOMS SO₂ data for volcanic clouds in the UTLS have shown agreement to within 20% for SO2 column amounts of <100 DU.

 

 

 

Product Description

 

The OMSO2 product is written as HDF-EOS5 swath file. Data files are available from Goddard Earth sciences Data and Information Services Center (GES DISC) web site. For a list of tools that read HDF-EOS5 data files, please visit this link: http://disc.gsfc.nasa.gov/Aura/tools.shtml

 

A file, also called a granule, contains SO₂ and associated information retrieved from each OMI scene from the sun-lit portion of an Aura orbit. The data are ordered in time sequence. The information provided on these files 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 four assumed vertical profiles. 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 data archive, please, contact GES DISC. For questions and comments related to the OMSO2 algorithm and data quality please contact Nickolay Krotkov (Nickolay.A.Krotkov@nasa.gov), who has the overall responsibility for this product, with copies to Kai Yang (Kai.Yang.1@gsfc.nasa.gov) Arlin J. Krueger (akrueger@umbc.edu), and Simon Carn (scarn@umbc.edu). 

 

The subsets of OMSO2 data over many ground stations and along Aura validation aircraft flights paths are also available through the Aura Validation Data Center (AVDC) web site.

 

References

 

Bhartia, P. K. and C. W. Wellemeyer (2002), OMI TOMS-V8 Total O3 Algorithm, Algorithm Theoretical Baseline Document: OMI Ozone Products, edited by P. K. Bhartia, vol. II, ATBD-OMI-02, version 2.0.  Available: http://eospso.gsfc.nasa.gov/eos_homepage/for_scientists/atbd/docs/OMI/ATBD-OMI-02.pdf

 

Carn, S. A., A. J. Krueger, N. A. Krotkov, K. Yang, and P. F. Levelt  (2007a), Sulfur dioxide emissions from Peruvian copper smelters detected by the Ozone Monitoring Instrument, Geophys. Res. Lett., 34,  L09801, doi:10.1029/2006GL029020.

 

Carn, S.A., N.A. Krotkov, K. Yang, R.M. Hoff, A.J. Prata, A.J. Krueger, S.C. Loughlin, and P.F. Levelt (2007b), Extended observations of volcanic SO₂ and sulfate aerosol in the stratosphere, Atmos. Chem. Phys. Discuss., 7, 2857-2871. (http://www.atmos-chem-phys-discuss.net/7/2857/2007/acpd-7-2857-2007.html)

 

Carn, S.A., A.J. Krueger, N.A. Krotkov, S. Arellano, and K. Yang (2008a), Daily monitoring of Ecuadorian volcanic degassing from space, J. Volcanol. Geotherm. Res., (in press).

 

Carn, S.A., A.J. Krueger, N.A. Krotkov, K. Yang, and K. Evans (2008b), Tracking volcanic sulfur dioxide clouds for aviation hazard mitigation. Natural Hazards, Special Issue on Aviation Hazards from Volcanoes (in press).

 

Krotkov,N.A., B. McClure, R. Dickerson, S. Carn, Can Li, P.K. Bhartia, K. Yang, A. Krueger, Z. Li, P. Levelt, H. Chen, P.Wang, and D. Lu (2008), Ozone Monitoring Instrument (OMI) SO₂ validation over NE China, J. Geophys. Res., Aura validation  special issue, (in press)

 

Krotkov, N.A., S.A. Carn, A.J. Krueger, P.K. Bhartia, and K. Yang (2006). Band residual difference algorithm for retrieval of SO2 from the Aura Ozone Monitoring Instrument (OMI). IEEE Trans.Geosci. Remote Sensing, AURA special issue, 44(5), 1259-1266, doi:10.1109/TGRS.2005.861932, 2006

 

Krueger, A.J., L.S. Walter, P.K. Bhartia, C.C. Schnetzler, N.A. Krotkov, I. Sprod, and G.J.S. Bluth (1995) Volcanic sulfur dioxide measurements from the total ozone mapping spectrometer instruments. J. Geophys. Res., 100(D7), 14057-14076, 10.1029/95JD01222.

 

Bogumil, K., J. Orphal, T. Homann, S. Voigt, P. Spietz, O.C. Fleischmann, A. Vogel, M. Hartmann, H. Kromminga, H. Bovensmann, J. Frerick, J.P. Burrows (2003), Measurements of molecular absorption spectra with the SCIAMACHY pre-flight model: instrument characterization and reference data for atmospheric remote-sensing in the 230-2380nm region, Journal of Photochemistry and Photobiology, A:Chemistry, 157 , 167-184.

 

Yang, K., N. Krotkov, A. Krueger, S. Carn, P. K. Bhartia, and P. Levelt (2007), Retrieval of Large Volcanic SO₂ columns from the Aura Ozone Monitoring Instrument (OMI): Comparisons and Limitations, J. Geophys. Res., 112, D24S43, doi:10.1029/2007JD008825