Abstract. Arctic snow cover extent (SCE) trends and rates of change reported across recent climate assessments vary due to the time period of available data, the selection of snow products, and methodological considerations. While all reported trends are strongly negative during spring, more uncertainty exists in autumn. Motivated to increase the confidence in SCE trend reported in climate assessments, we quantify the impact of (1) year-over-year increases in time series length over the past

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... decades, (2) choice of reference period, (3) the application of a statistical methodology to improve inter-dataset agreement, (4) the impact of dataset ensemble size, and (5) product version changes. Results show that the rate of change during May and June has remained consistent over the past decade as time series length has increased, and is largely insensitive to the choice of reference period. Although new product versions have increased spatial resolution, use more advanced reanalysis meteorology to force snow models, and include improved remote sensing retrieval algorithms, these enhancements do not result in any notable changes in the observed rate of Arctic SCE change in any month compared to a baseline set of older products. The most impactful analysis decision involves the scaling of dataset climatologies using the NOAA snow chart climate data record as the baseline. While minor for most months, this adjustment can influence the calculated rate of change for June by a factor of two relative to different climatological baselines.