Status and Outlook of the OMI Surface UV (OMUVB) product OMI Science Team Meeting Baltimore, June 7, 2007 Aapo Tanskanen

OMI Surface UV Algorithm OMTO3 Level 2 data contains the satellite measurement data required for calculation of the first two terms However, the diurnal variation of the cloud conditions is not caught by using only OMI measurements Methods and sources of data for aerosol correction are being investigated. The intention is to introduce an aerosol correction in ECS 3.

Example: UV Index (clear-sky and cloud corrected)

Processing Status and Data Release The currently processed ECS 2 based OMUVB data corresponds to a time period from the launch of Aura to July 27, 2006 (last orbit 10744) AVDC provides OMUVB overpass data for over 100 sites that has been used for validation. New sites can be added Level 2 HDF5-EOS and Level 3 (1x1 degrees TOMS) data are available at FMI's FTP site, and will become available at DAAC this summer. FMI has developed a web application for online plotting of OMUVB data with GrADS using 1x1 degrees gridded data

Summary of the findings of the validation paper submitted to the JGR special issue on Aura validation: VALIDATION OF DAILY ERYTHEMAL DOSES FROM OMI WITH GROUND-BASED UV MEASUREMENT DATA Aapo Tanskanen (1), Anders Lindfors (1), Anu Määttä (1), Nickolay Krotkov (2), Jay Herman (3), Jussi Kaurola (1), Tapani Koskela (1), Kaisa Lakkala (4), Vitali Fioletov (5), Germar Bernhard (6), Richard McKenzie (7), Yutaka Kondo (8), Michael O'Neill (9), Harry Slaper (10), Peter den Outer (10), Alkiviadis F. Bais (11), Johanna Tamminen (1) (1) Finnish Meteorological Institute, Helsinki, Finland (2) GEST Center, University of Maryland, Baltimore, USA (3) NASA Goddard Space Flight Center, Greenbelt, Maryland, USA (4) FMI’s Arctic Research Centre, Sodankylä, Finland (5) MSC/Environment Canada, Ontario, Canada (6) Biospherical Instruments, San Diego, USA (7) National Institute of Water and Atmospheric Research, Lauder, Central Otago, New Zealand (8) University of Tokyo, Tokyo, Japan (9) Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, USA (10) National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands (11) Aristotle University of Thessaloniki, Laboratory of Atmospheric Physics, Thessaloniki, Greece Several additional groups are validating the OMI surface UV data, which indicates that there is a great interest in this product

OMUVB Validation Daily erythemal doses derived from OMI measurements were compared with those calculated from ground-based measurements Science questions Can we continue the TOMS UV time series with surface UV derived from OMI measurements? Is the plane-parallel-cloud (PPC) model based method for cloud correction superior to the simple Lambertian Equivalent Reflectivity (LER) based cloud correction method? Does the new surface albedo climatology fix the problem of the underestimation of surface UV at seasonally snow covered terrain?

Ground-based Reference Data 17 measurement sites representing various measurement conditions 18 spectral UV instruments with high level QA/QC

Analysis of the comparison results Scatterplots, error distributions snow cover (R s >0.10) snow free (R s <0.10) Statistical quantities Median bias (less sensitive to outliers than the average) Percentages of the OMI-derived doses within 10, 20, and 30% with the reference data Usual quantities, such as correlation coefficient and root-mean-square were abandoned, because correlation originates mostly from seasonality and the error distributions are not normal distributions

OMI surface UV does not catch the diurnal variation in cloud conditions, because attenuation of the UV radiation by clouds is estimated using a single overpass measurement The clouds over the Greenland icecap are optically thin, and therefore, their effect on surface UV is small. For a typical reference site, the satellite-derived daily doses differ more from the reference data because of uncertainty related to cloud attenuation.

Relative uncertainty of the OMI derived dose increases as a function of the observed cloud optical thickness

Negative bias at Mauna Loa, due to Scattering from air and from highly reflecting clouds below the observation site increase the effective albedo and the observed UV doses The satellite-derived ozone column represents an average over a large footprint, whereas the ozone column above the elevated observatory is systematically about 5% less than the mean

Small positive bias at clean sites

Positive bias at sites affected by absorbing aerosoles or trace gases Arctic haze ? megacity rural urban urban city forest fires?

Surface albedo climatology works at some polar sites, but fails at some other. Coastal Antarctic sites are extremely challenging for the surface UV algorithm NSF monitoring site at Palmer

Conclusions OMI measurements are suitable for continuation of the global satellite-derived surface UV time series using a surface UV algorithm similar to the original TOMS UV algorithm Two alternative cloud correction methods were compared: plane-parallel cloud model method and the method based on Lambertian equivalent reflectivity One cloud correction method was not found systematically superior to the other However, a comparison of spectral irradiances would likely show the advantages of the plane-parallel cloud method that accounts for the spectral dependency of cloud modification factor

Validation of the spectral irradiances are needed in order to better quantify the positive bias of the satellite-derived UV due to absorbing aerosols and trace gases Validation results imply that in the further development of the surface UV algorithm we need to focus on Correction for absorbing aerosols and trace gases Surface albedo climatology The validation tools developed, and the ground-based data gathered for this study lay a good basis for further development of the OMI surface UV algorithm User feedback has been of great help and gives us motivation for further work.