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Active and passive microwave remote sensing data were used to identify springtime near-surface thaw events in northern China and Mongolia. Typical signatures of the time series (the first 180 days of a year) in the region characterized by three different winter surface conditions, i.e., high-moisture frozen ground, nonfrozen ground, and low-moisture cold (desert/dryland) regions, were analyzed with meteorological records. In all regions, brightness temperature showed an increasing trend during the first 180 days of the year, but backscatter trends decreased in frozen ground regions, increased in nonfrozen ground regions, and were steady in desert regions. Diurnal brightness temperature differences were lesser in regions with than without seasonal freeze-thaw events due to the surface diurnal temperature differences in winter. A method based on these signature analysis results was proposed. First, frozen ground, nonfrozen ground, and desert regions could be distinguished by using two proposed indices, the temporal difference between morning and evening brightness temperatures (TI) and the slope ratio between backscatter and brightness temperature time series (SI). Second, a logistic function of the daily signal difference between active and passive time series (DIi) could detect the beginning and end of the freeze-thaw transition.