We describe a method to remotely sense precipitation and classify its intensity over water, coast, and land surfaces. This method is intended to be used in a nowcasting environment. It is based on data obtained from the Advanced Microwave Sounding Unit (AMSU) onboard NOAA-15. Each observation is assigned a probability to belong to four different classes namely precipitation- free, risk of precipitation, precipitation between 0.5 and 5 mm/h and precipitation higher than 5 mm/h. Since the method is designed to work over different surface types, it mainly relies on the scatteringsignal of precipitation-sized ice particles received at high frequencies.
For the calibration and validation of the method we use an eight month dataset of combined radar and AMSU-data obtained over the Baltic area. We campare results for the AMSU-B channels at 89 GHz and 150 GHz and find that the high frequency channel at 150 GHz allows for a much better discrimination of different types of precipitation than the 89 GHz channel. While precipitation-free areas as well as heavily precipitating areas (> 5mm/h) can be identified to a high accuracy, the intennediate classes are more ambiguous. This ambiguity stems from the ambiguity of the passive microwave observations as well as from the non-perfect matching of the different data sources and non-perfect radar adjustment. In addition to a statistical assessment of the method's accuracy, we present case studies to demonstrate its capabilities to classify different types of precipitation and to seemlessly work over highly structured, inhomogeneous surfaces.