Accounting for the Fact that Snow Falls Slower than Rain
When calibrating satellite observations with ground-based ones, estimated precipitation rates are improved by considering that snow takes longer to fall compared to rain.
SOURCE: Geophysical Research Letters
The correlation between satellite retrievals (GPROF) and ground-based (MRMS) observations of precipitation is highest for very short lead times in the case of rainfall (top left), where it decreases sharply with time, while the correlation stays high for longer in the case of snowfall (top right). Credit: You et al. [2019], Figure 3
Satellite estimates of precipitation are the only way to achieve the complete spatial coverage needed to understand how the water cycle may respond to warming, specifically, whether it speeds up or slows down. These estimates rely on indirect measures such the brightness temperature of cloud tops, which need to be calibrated with ground-based observations.
You et al. [2019] highlight the need to consider the time lag between satellite retrievals and ground-based estimates of precipitation, especially in the case of snowfall, when correcting the former with the latter. While the lag is small—of the order of a fraction of an hour—it is significant on climate time scales in reducing apparent discrepancies between the two types of measurements. This is therefore relevant to improved monitoring and understanding of the global water cycle.
Citation: You, Y., Meng, H., Dong, J., & Rudlosky, S. [2019]. Time‐lag correlation between passive microwave measurements and surface precipitation and its impact on precipitation retrieval evaluation. Geophysical Research Letters, 46, 8415–8423.https://doi.org/10.1029/2019GL083426
—Alessandra Giannini, Editor, Geophysical Research Letters
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