1. Surface Reflectivity from OMI: Effects of snow on OMI NO 2 retrievals Gray O’Byrne 1, Randall Martin 1,2, Joanna Joiner 3, Edward A. Celarier 3 1 Dalhousie University 2 Harvard-Smithsonian Center for Astrophysics 3 NASA Goddard Space Flight Center Locating Cloud Free OMI scenes We use the MODIS/Aqua cloud mask to determine the presence of clouds within the OMI field of view. Using MODIS to screen for clouds ensures that an OMI scene is cloud free even when surface reflectivity is unknown. We account for horizontal displacement of the clouds during the time between the MODIS and OMI overpass (~12 minutes). MODIS Cloud Mask Potential Transport Cloud Free OMI Scenes! Snow-Free Surface Reflectivity 0.1 0 0.2 We filter the Lambertian-Equivalent Reflectivity (LER) retrieved from OMI [Joiner and Vasilikov, 2006] to exclude clouds and aerosols as determined by MODIS. Deserts are more reflective then vegetation and ocean. White space indicates persistent cloud. Surface Reflectivity of Seasonal Snow Cover (LER) This is the surface reflectivity we measure for scenes that are both cloud free (as determined by MODIS) and snow covered, as flagged in the OMI product according to the NISE dataset. Surface reflectivity over snow varies considerably from the value of 0.6 that is typically used in current OMI retrievals. Annual Mean Surface Reflectivity (LER) at 354nm We compare our results to the climatology of surface reflectivity from OMI (OMLER) of Kleipool et. al [2008]. Our product is lower by ~0.01 over land with the exception of Africa and the Middle-East where residual aerosol contamination is expected in our product. In these dusty regions our product is higher by ~0.005 on average. Differences due to seasonal snow cover are evident in the northern hemisphere. Some isolated regions such as the Aral Sea, Lake Eyre (Australia) and Salt Lake (US) are up to 0.2 higher in our product. Above minus OMLER (354nm) Effect on OMI NO 2 – Challenges with Clouds and Snow Here we compare the OMI NO2 product [Bucsela et al., 2006] over the cities of Calgary and Edmonton (in the highly reflective region in South-Central Canada) for three different snow-on-ground categories. The current fixed surface reflectivity for snow used in OMI cloud and NO 2 retrievals leads to trends of increasing NO 2 with snow and cloud. Errors in the a priori surface reflectance will introduce errors in the OMI (O2-O2) cloud fraction retrieval, so we make the distinction between reported and real cloud fractions. Fractional Bias in tropospheric NO 2 Over Snow-Covered Lands All Scenes With Cloud Mask The top panel shows the bias between the OMI NO 2 columns for cloudless scenes (determined by MODIS) retrieved with our snow-covered surface reflectivity versus columns calculated with the surface reflectivity (and cloud data) used in the current OMI NO 2 product. The error in the a priori surface reflectance leads to non- zero cloud fractions being reported for these cloudless scenes. In practice scenes with high cloud fractions are often masked to ensure good sensitivity to the boundary layer. The bottom panel shows the bias once scenes with OMI cloud fractions greater then 0.3 are removed. Most positive biases are removed, but negative biases remain unchanged. This work was supported by the Canadian Foundation for Climate and Atmospheric Science. The authors would like to acknowledge Jim Gleason for his helpful comments. References: Bucsela, E. J., E. A. Celarier, M. O. Wenig, J. F. Gleason, J. P. Veefkind, K. F. Boersma, and E. J. Brinksma (2006), Algorithm for NO2 vertical column retrieval from the ozone monitoring instrument, IEEE Trans. Geosci. Remote Sens., 44(5), 1245-1258. Joiner, J. and A. P. Vasilkov (2006), First results from the OMI rotational Raman scattering cloud pressure algorithm, IEEE Trans. Geosci. Remote Sens., 44(5), 1272-1282. Kleipool, Q. L., M. R. Dobber, J. F. de Haan, and P. F. Levelt (2008), Earth surface reflectance climatology from 3 years of OMI data, Journal of Geophysical Research-Atmospheres, 113(D18). Mean NO 2 Column (molec/cm 2 ) Reported OMI Cloud Fraction Winter OMI NO 2 over Calgary & Edmonton Retrievals of NO 2 from the OMI/Aura satellite instrument are being widely applied to improve understanding of air quality and NOx emissions. OMI NO 2 retrievals depend on information about surface reflectivity. We use observations from the MODIS/Aqua satellite instrument, which flies 12 minutes ahead of OMI, to exclude clouds from OMI observations and determine surface reflectivity for cloud-free conditions. The resultant dataset is used to evaluate surface reflectivity inferred from other techniques, and to assess the implications for OMI NO 2 retrievals over snow. Summary 0 -0.1 0.1 0.5 0 1 0 -0.5 1 0.5