2024
Evaluation of IMERG climate trends over land in the TRMM and GPM eras Journal Article
In: Environmental Research Letters, 2024.
How has the latest IMERG V07 improved the precipitation estimates and hydrologic utility over CONUS against IMERG V06? Journal Article
In: Journal of Hydrology, vol. 645, 2024.
2023
In: Remote Sensing, vol. 15, iss. 23, pp. 5622, 2023.
2022
In: Atmosphere, vol. 13, iss. 10, pp. 1666, 2022, (A comparison of precipitation products from satellite observation, WRF simulation, and insitu gauges over Andes ).

Disentangling error structures of precipitation datasets using decision trees Journal Article
In: Remote Sensing of Environment, vol. 280, pp. 113185, 2022, (Interpret decision tree structures to infer spatiotemporal errors on satellite precipitation products.).
A flood predictability study for Hurricane Harvey with the CREST-iMAP model using high-resolution quantitative precipitation forecasts and U-Net deep learning precipitation nowcasts Journal Article
In: Journal of Hydrology, vol. 612, pp. 128168, 2022, (Comparing different QPFs and their impact on flood inundation).

In: Zhang, Ke; Hong, Yang; AghaKouchak, Amir (Ed.): Remote Sensing of Water-related Hazards, Chapter 5, pp. 87-104, American Geophysical Union, 2022.
Evaluation of GPM IMERG and its constellations in extreme events over the conterminous United States Journal Article
In: Journal of Hydrology, vol. 606, pp. 127357, 2022, (Continental-scale evaluation of satellite precipitation utilities during extreme rainfall events).
2021

Two-decades of GPM IMERG early and final run products intercomparison: Similarity and difference in climatology, rates, and extremes. Journal Article
In: Journal of Hydrology, vol. 594, pp. 125975, 2021, (Global evaluation of satellite precipitation product utilities and its applicability in real time weather forecast).
2020
Ground Validation and Error Sources Identification for GPM IMERG Product over the Southeast Coastal Regions of China Journal Article
In: Remote Sensing, vol. 12, iss. 24, pp. 4154, 2020, (Satellite precipitation products error identification in coastal regions).
Advancing Satellite Precipitation Retrievals with Data Driven Approaches: Is black box model explainable? Journal Article
In: Earth and Space Science, vol. 8, pp. e2020EA001423, 2020, (One of the first machine learning interpretation used in satellite precipitation retrievals).
In: Remote Sensing, vol. 12, iss. 8, pp. 1258, 2020, (Investigate the uncertainties of precipitation products derived from three sources: satellite, weather radar, and in-situ gauges).