GPROF-IR is a CNN-based retrieval that uses temporal context in geostationary IR observations to produce precipitation estimates with lower error than prior IR methods and climatological consistency with PMW retrievals for integration into IMERG V08.
Gprof-nn: a neural-network-based implementation of the goddard profiling algorithm,
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Cellular base station signals can be repurposed as distributed opportunistic radars to retrieve standard weather-radar moments for rainfall at few-meter spatial and tens-of-seconds temporal resolution in urban areas.
citing papers explorer
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GPROF-IR: An Improved Single-Channel Infrared Precipitation Retrieval for Merged Satellite Precipitation Products
GPROF-IR is a CNN-based retrieval that uses temporal context in geostationary IR observations to produce precipitation estimates with lower error than prior IR methods and climatological consistency with PMW retrievals for integration into IMERG V08.
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Mobile Radio Networks and Weather Radars Dualism: Rainfall Measurement Revolution in Densely Populated Areas
Cellular base station signals can be repurposed as distributed opportunistic radars to retrieve standard weather-radar moments for rainfall at few-meter spatial and tens-of-seconds temporal resolution in urban areas.