Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets

Guoqiang Tang, Martyn Clark, Simon Michael Papalexiou, Ziqiang Ma, Yang Hong

Remote Sensing of Environment · 2020

Read source ↗ All evidence

Summary

This 2020 comparative analysis evaluated whether satellite precipitation products, particularly NASA's GPM IMERG, have improved in accuracy and utility over the preceding two decades relative to nine competing satellite and reanalysis datasets. The work assessed multiple performance metrics across diverse geographical contexts, providing systematic evidence on the trajectory of remote-sensing precipitation measurement. Such benchmarking is relevant to hydrological modelling, climate studies, and water resource management applications in agriculture and beyond.

UK applicability

The findings on satellite precipitation product accuracy are applicable to UK rainfall monitoring, flood forecasting, and hydrological modelling. Improved precipitation datasets support UK agricultural decision-making, irrigation management, and climate impact assessments, particularly as weather patterns become less predictable.

Key measures

Precipitation estimation accuracy (bias, root mean square error, correlation coefficients); temporal and spatial resolution; product coverage and availability across regions and time periods

Outcomes reported

The study compared the accuracy and evolution of the GPM IMERG satellite precipitation product against nine other satellite and reanalysis datasets over two decades. It assessed improvements in precipitation estimation quality across diverse geographical and climatic regions.

Theme
Measurement & metrics
Subject
Measurement methods & nutrient profiling
Study type
Research
Study design
Comparative analysis / benchmarking study
Source type
Peer-reviewed study
Status
Published
Geography
Global
System type
Other
DOI
10.1016/j.rse.2020.111697
Catalogue ID
BFmor3gf2d-nvprif

Topic tags

Pulse AI · ask about this record

Dig deeper with Pulse AI.

Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.