Omranian, E., et al. (2018). “How Well Can Global Precipitation Measurement (GPM) Capture Hurricanes? Case Study: Hurricane Harvey.” Remote Sensing 10(7).

Author described the severity of Harvey, highest record of rainfall accumulated in this region ever, contributing to more than $125 billion Texas infrastructure loss and multiple faltalities. The author compared GPM-IMERG satellite data and NCEP stage IV QPE (4km) ground radar data as reference. The results indicated that IMERG is capable of detecting spatial variability of the storm and 62% accuracy in reconstructing rainfall field. But under-represented in coastal areas and over-representated in high-intensity regions. The IMERG data degrades along the core.

Prakash, S., et al. (2016). “From TRMM to GPM: How well can heavy rainfall be detected from space?” Advances in Water Resources 88: 1-7.

Author showed an improvement if IMERG data compared to TMPA data in detecting extreme rainfall events in India. Even though the TMPA data showed a larger probability of detection of heavy rainfall events most parts of the country, it showed a large false alarm ratio and a relatively small critical success index.

Mazzoglio, P., et al. (2019). “Improving an Extreme Rainfall Detection System with GPM IMERG data.” Remote Sensing 11(6).

Author here proposed a way to quantify the accuracy of IMERG data in extreme events for varying temporal aggregations. The results showed that, when aggregation time exceeds 12 hours, then IMERG can guarantee a good result.