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

Accurate representation of surface reflectivity is essential to tropospheric trace gas retrievals from solar backscatter observations. Surface snow cover presents a significant challenge due to its variability; however, the high reflectance of snow is advantageous for trace gas retrievals. We first examine the implications of surface snow on retrievals from the upcoming TEMPO geostationary instrument for North America. We use a radiative transfer model to examine how an increase in surface reflectivity due to snow cover changes the sensitivity of satellite retrievals to NO2 in the lower troposphere. We find that a substantial fraction (> 50 %) of the TEMPO field of regard can be snow covered in January, and that the average sensitivity to the tropospheric NO2 column substantially increases (doubles) when the surface is snow covered. We then evaluate seven existing satellite-derived or reanalysis snow extent products against ground station observations over North America to assess their capability of informing surface conditions for TEMPO retrievals. The Interactive Multisensor Snow and Ice Mapping System (IMS) had the best agreement with ground observations (accuracy = 93 %, precision = 87 %, recall = 83 %, F = 85 %). Multiangle Implementation of Atmospheric Correction (MAIAC) retrievals of MODIS observed radiances had high precision (90 % for Aqua and Terra), but underestimated the presence of snow (recall = 74 % for Aqua, 75 % for Terra). MAIAC generally outperforms the standard MODIS products (precision = 51 %, recall = 43 % for Aqua; precision = 69 %, recall = 45 % for Terra). The Near-real-time Ice and Snow Extent (NISE) product had good precision (83 %) but missed a significant number of snow covered pixels (recall = 45 %). The Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data set had strong performance metrics (accuracy = 91 %, precision = 79 %, recall = 82 %, F = 81 %). We use the F score, which balances precision and recall, to determine overall product performance (F = 85 %, 82(82) %, 81 %, 58 %, 46(54) % for IMS, MAIAC Aqua(Terra), CMC, NISE, MODIS Aqua(Terra) respectively) for providing snow cover information for TEMPO retrievals from solar backscatter observations. [ABSTRACT FROM AUTHOR]