Articles | Volume 11, issue 5
Atmos. Meas. Tech., 11, 2983–2994, 2018
https://doi.org/10.5194/amt-11-2983-2018
Atmos. Meas. Tech., 11, 2983–2994, 2018
https://doi.org/10.5194/amt-11-2983-2018

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.

Data sets

IMS Daily Northern Hemisphere Snow and Ice Analysis at 1 km, 4 km, and 24 km Resolutions, Version 1 National Ice Center https://doi.org/10.7265/N52R3PMC

Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent, Version 5 M. J. Brodzik and J. S. Stewart https://doi.org/10.5067/3KB2JPLFPK3R

MODIS/Aqua Snow Cover Daily L3 Global 0.05Deg CMG, Version 6 D. Hall and G. A. Riggs https://doi.org/10.5067/MODIS/MYD10C1.006

MODIS/Terra Snow 90 Cover Daily L3 Global 0.05Deg CMG, Version 6 D. Hall and G. A. Riggs https://doi.org/10.5067/MODIS/MOD10C1.006

Download
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.