Using Citizen Science Reports to Evaluate Estimates of Surface Precipitation Type
Authors: Sheng Chen, Jonathan J. Gourley, Yang Hong, Qing Cao, Nicholas Carr, Pierre-Emmanuel Kirstetter, Jian Zhang, Zac Flamig
Journal: Bulletin of the American Meteorological Society
Publication Date: In Print 2/2016

Important Conclusions: Consistency in results from city to city give an indication that the citizen science reports of rain and snow from the meteorological Phenomena Identification Near the Ground app (mPING) provide useful information about the quality of the MRMS precipitation type algorithm. The MRMS surface precipitation type algorithm has a slight propensity to produce too much rain where there is snow; this suggests some modifications are needed to the temperature thresholds and motivates probabilistic approaches.

Significance: This is the first paper to comprehensively evaluate the MRMS rain-snow product using mPING crowd-sourced observations.