OMTO3 README File


Released April 15, 2005

Overview

This document provides a brief description of the OMTO3 data product. OMTO3 contains total ozone,  aerosol index, and ancillary information produced from the TOMS Version 8 (V8) algorithm applied to OMI global mode measurements. In the global mode each file contains a single orbit of data covering a 2000 km pole-to-pole swath, approximately 2600 km wide (sunlit portions only).

The accuracy and precision of total ozone data in OMTO3 is roughly similar to the TOMS data of the preceding 25 years, however, the suitability of OMTO3 data for the analysis of long-term trends has not yet been established. It is expected that there will be at least one update to OMTO3 a year or so after public release of the product, when the long-term performance of the instrument is better understood.

You may refer to release specific information about OMTO3 for details about software versions and known problems.

Algorithm Description

The basic algorithm uses just 2 wavelengths (317.5 and 331.2 nm under most conditions, and 331.2 and 360 nm for high ozone and high solar zenith angle conditions). The longer of the two wavelengths is used to derive the surface reflectivity (ord cloud fraction). Once the surface reflectivity has been established the shorter wavelength, which is heavilt absorbed by ozone, may be used to derive total ozone. The algorithm also calculates the “aerosol index (AI)” from the difference in surface reflectivity derived from the 331.2 and 360 nm measurements. The AI primarily provides a measure of absorption of UV radiation by smoke and desert dust. However, surface effects, such as sea-glint and ocean color, can also enhance the AI, and some types of (non-absorbing) aerosols can produce negative AI values. The AI is used to correct the total ozone derived by the basic algorithm. The AI is also very useful for tracking global transport of smoke and dust, for it is not as affected by clouds as are most other aerosol algorithms, and has the unique feature that it can track these aerosols above and through clouds, as well as over snow/ice covered surfaces.

Other than the three primary wavelengths mentioned above, the OMTO3 algorithm uses additional wavelengths for quality control and error correction in more restricted geophysical situations. These include correction for ozone profile shape errors at large solar zenith angles using 312.5 nm measurements, and the detection of sulfur-dioxide contamination by volcanoes using multiple wavelength pairs. For a more detailed description of the algorithm please refer to the Algorithm Theoretical Basis Document (ATBD) on http://eospso.gsfc.nasa.gov/eos_homepage/for_scientists/atbd/viewInstrument.php?instrument=13. This website contains a description of the most recent updates to the algorithm, along with other related documents related to this algorithm.

This algorithm is one of the two algorithms that will be used to derive total ozone values from OMI. The other is an algorithm based on the Differential Optical Absorption Spectroscopy (DOAS) approach, taking advantage of the OMI's hyperspectral measurements. The DOAS algorithm is undergoing final testing at KNMI/The Netherlands.  The DOAS ATBD is on the above website. Initial comparisons show good overall agreement between the two algorithms, but there are noticeable differences over clouds and snow/ice, as well as at large solar zenith angles. It is anticipated that, after evaluation of the strengths and weaknesses of the two algorithms, a combined approach will be used to produce OMI total ozone data in 2-3 years.

Data Quality Assessment

Overall the quality of total ozone and AI data produced by OMTO3 is similar to that from TOMS. Almost a quarter century of TOMS data processed using an essentially identical algorithm are available (http://toms.gsfc.nasa.gov/). Based on experience with TOMS, the total ozone data provided in OMTO3 should have a root-mean squared error of 1-2%, depending on solar zenith angle, aerosol amount, and cloud cover. These errors are best described as pseudo-random: systematic over small areas with a unique geophysical regime, random over large areas containing a mixture of geophysical regimes. Preliminary analyses show that OMTO3 data compare about as well with Dobson and Brewer stations as did Nimbus-7/TOMS data, but compare better with those ground based instruments than do the most recent data from EP/TOMS. (The last 3 years of EP/TOMS are affected by poorly understood calibration anomalies that are currently being evaluated.) Nevertheless, the present version of OMTO3 data (associated with this README file) are not suitable for trend studies and may contain other problems that were not identified in the preliminary validation studies. Users are strongly advised to consult the OMI Quality Assurance Team for most recent information on our ongoing assessment of OMTO3 data quality.

Product Description

A 2600 km wide OMI scan contains 60 pixels. Due to optical aberrations and small misalignment between the instrument optic axis with the S/C nadir, the pixels on the swath are not symmetrically aligned on the line perpendicular to the orbital plane. However, the latitude and longitude provided with each pixel represent the location of each pixel on the ground to a fraction of a pixel.

The OMTO3 product is written as an HDF-EOS5 swath file. For a list of tools that read HDF-EOS5 data files, please visit these links:

http://disc.gsfc.nasa.gov/Aura/tools.shtml,
http://hdfeos.gsfc.nasa.gov/hdfeos/softwarelist.cfm

A single OMTO3 file contains information retrieved from each OMI pixel over the sun-lit portion of one Aura orbit. The data are ordered in time. The information provided in these files includes latitude, longitude, solar zenith angle, reflectivity and total column ozone, aerosol index, and a large number of ancillary parameters that provide information to assess data quality. The most important of these parameters is the QualityFlags field, which contains the processing error flag in its first byte. Most users should use data with a data quality flag = 0 (good sample) or 1 (glint contamination corrected) only. For a complete list of the parameters, please read the OMTO3 file specification.

For users not interested in the detailed information provided on OMTO3 dataset we are developing several gridded products. Initially, we will grid OMTO3 data in a format identical to that used for TOMS (1˚ x 1.25 ˚ lat/long) and will make it available through the TOMS website. However, to take advantage of the higher spatial resolution of the OMI products we intend to produce higher resolution gridded products for all OMI datasets, including OMTO3. In addition, we intend to make OMTO3 data available in a geographically ordered (rather than time-ordered) format that can be more easily subsetted and manipulated on-line prior to ordering. Please check the Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) website for current information on these products.

Full OMTO3 data, as well as subsets of these data over many ground stations and along Aura validation aircraft flights paths are also available through the Aura Validation Data Center (AVDC) website) to those investigators who are associated with the various Aura science teams. B. R. Bojkov is the point of contact at the AVDC.

Questions related to the OMTO3 dataset should be directed to the GES DAAC. For questions and comments related to the OMTO3 algorithm and data quality please contact Kai Yang . Please send a copy of your e-mail to P. K. Bhartia, who has the overall responsibility for this product.