EO·Atlas
Satellite precipitation retrieval
Integrates passive-microwave precipitation estimates with microwave-calibrated infrared observations and interpolation to produce near-global rainfall fields, exemplified by GPM IMERG.
Satellite precipitation retrieval is an analysis methodology: it does not rest on one sensor principle. IMERG-class products merge precipitation estimates from a constellation of passive-microwave sensors with microwave-calibrated geostationary infrared estimates, interpolation, and gauge adjustment to produce half-hourly global rainfall fields.[1][2] It is useful for rainfall exposure and vector-borne-disease risk modelling, but it remains indirect for disease outcomes and is weakest for shallow, orographic, frozen, and rapidly evolving precipitation where sensor sampling or retrieval physics under-resolve the event.
- FY-4B Advanced Geostationary Radiation Imager
via FY-4B
WMO lists precipitation intensity retrieval from AGRI TIR, SWIR, and MWIR channels with microwave-calibration caveats.
- FY-4A Advanced Geostationary Radiation Imager
via FY-4A
WMO lists precipitation intensity retrieval from AGRI TIR/SWIR/MWIR cloud microphysics with microwave-calibration caveats.
- MTVZA-GY Imaging/Sounding Microwave Radiometer
via Meteor-M N2-4
MTVZA-GY passive microwave channels (particularly high-frequency channels near 91 and 183 GHz) contribute to precipitation retrieval. WMO OSCAR lists precipitation measurement as a MTVZA-GY output variable.
- Advanced Microwave Scanning Radiometer for EOS (AMSR-E)
Passive-microwave input sensor class used by IMERG-era precipitation retrievals; full IMERG/GMI product row is open.
- Advanced Microwave Scanning Radiometer 2 (AMSR2)
Passive-microwave input sensor class used by IMERG-era precipitation retrievals; full IMERG/GMI product row is open.
- 2C Degrees Water-Risk Signals
- CARMA Climate Risk Platform
Combines optical reflectance and SAR backscatter to exploit complementary information; good for cloud-persistent monitoring, crop classification under cloud cover, and flood mapping in vegetated areas.
Reconstructs dense time-series by blending high-frequency coarse-resolution and low-frequency fine-resolution observations; good for crop phenology tracking and cloud-gap filling.
Merges measurements from active (radar or scatterometer) and passive (radiometer) sensors that observe the same geophysical variable, combining their complementary error and sampling characteristics into a single harmonised record. The basis of long-term blended soil moisture climate data records.
Adjusts observations from different instruments onto a common radiometric and geometric reference so they can be used interchangeably in one time-series, correcting for differences in band response, view geometry, and calibration. The basis of harmonised multi-mission surface-reflectance products.
- [1]IMERG: Integrated Multi-satellitE Retrievals for GPMagency doc2026-06-08
- [2]Integrated Multi-satellitE Retrievals for GPM (IMERG) Algorithm Theoretical Basis Documentagency doc2026-06-08
Edited from public sources by SpectraWorks editorial. See the data dictionary for field definitions.
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Plain text
Satellite precipitation retrieval. EO-Atlas, SpectraWorks B.V. https://eo-atlas.org/topics/methodologies/satellite-precipitation-retrieval (CC BY 4.0)
BibTeX
@misc{eoatlas:topics:methodologies:satellite-precipitation-retrieval,
title = {Satellite precipitation retrieval},
author = {{EO-Atlas}},
publisher = {SpectraWorks B.V.},
note = {CC BY 4.0},
url = {https://eo-atlas.org/topics/methodologies/satellite-precipitation-retrieval}
}