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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2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
physics.ao-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A fused PMW retrieval trained on complementary CloudSat and GPM radar references improves high-latitude precipitation detection by 26% and reduces underestimation by over 50% versus precipitation-radar-only training.
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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Bridging the Sensitivity Gap in Precipitation Estimates from Spaceborne Radars using Passive Microwave Observations
A fused PMW retrieval trained on complementary CloudSat and GPM radar references improves high-latitude precipitation detection by 26% and reduces underestimation by over 50% versus precipitation-radar-only training.