Articles | Volume 11, issue 5
Atmos. Meas. Tech., 11, 2983–2994, 2018
Atmos. Meas. Tech., 11, 2983–2994, 2018

Research article 22 May 2018

Research article | 22 May 2018

Assessing snow extent data sets over North America to inform and improve trace gas retrievals from solar backscatter

Matthew J. Cooper et al.

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Cited articles

Arola, A., Kaurola, J., Koskinen, L., Tanskanen, A., Tikkanen, T., Taalas, P., Herman, J. R., Krotkov, N., and Fioletov, V.: A new approach to estimating the albedo for snow-covered surfaces in the satellite UV method, J. Geophys. Res., 108, 4531,, 2003.
Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G., and Wagner, T.: Megacity emissions and lifetimes of nitrogen oxides probed from space, Science, 333, 1737–1739,, 2011.
Boersma, K. F., Eskes, H. J., and Brinksma, E. J.: Error analysis for tropospheric NO2 retrieval from space, J. Geophys. Res.-Atmos., 109, D04311,, 2004.
Brasnett, B.: A Global Analysis of Snow Depth for Numerical Weather Prediction, J. Appl. Meteorol., 38, 726–740,<0726:AGAOSD>2.0.CO;2, 1999.
Brodzik, M. J. and Stewart, J. S.: Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent, Version 5,, 2016.
Short summary
To accurately infer air pollutant concentrations from satellite observations, we must first know the reflectivity of the Earth’s surface. Using a model, we show that satellite observations are better able to observe NO2 near the surface if snow is present. However, knowing when snow is present is difficult due to its variability. We test seven existing snow cover data sets to assess their ability to inform future satellite observations and find that the IMS data set is best suited for this task.