32 citations as recorded by crossref.

1. Development of a high-resolution near-surface meteorological forcing dataset for the Third Pole region Y. Jiang et al. 10.1007/s11430-024-1507-6
2. The Uncertainty of IMERG Over the Western Edge of the Eastern Pacific Fresh Pool: An Error Model Based on SPURS-2 Field Campaign Observations Z. Li et al. 10.1109/TGRS.2023.3306795
3. Hourly calibration algorithm for Fengyun-2G quantitative precipitation estimates using spatial random forest and improved temporal disaggregation scheme H. Wu et al. 10.1016/j.atmosres.2025.108061
4. Analysis of the IMERG-GPM Precipitation Product Analysis in Brazilian Midwestern Basins Considering Different Time and Spatial Scales L. Duarte et al. 10.3390/w14162472
5. Deep learning-based multi-source precipitation merging for the Tibetan Plateau T. Nan et al. 10.1007/s11430-022-1050-2
6. 第三极地区高分辨率近地面气象驱动数据研制 尧. 姜 et al. 10.1360/N072024-0170
7. Statistical blending of global-gridded climatological products: an approach to inverse hydrological model R. Mousavi et al. 10.2166/hydro.2023.141
8. A multiple-step scheme for the improvement of satellite precipitation products over the Tibetan Plateau from multisource information K. He et al. 10.1016/j.scitotenv.2023.162378
9. A new approach to ensemble precipitation Estimation: Coupling satellite hydrological products with backward water balance models in Large-Scale P. Dastjerdi et al. 10.1016/j.jhydrol.2023.130564
10. Mapping Australia’s precipitation: harnessing the synergies of multi-satellite remote sensing and gauge network data B. Hines et al. 10.1080/15481603.2022.2143807
11. A two-step merging strategy for incorporating multi-source precipitation products and gauge observations using machine learning classification and regression over China H. Lei et al. 10.5194/hess-26-2969-2022
12. Sequential Data Processing for IMERG Satellite Rainfall Comparison and Improvement Using LSTM and ADAM Optimizer S. Toh et al. 10.3390/app13127237
13. Improving spatio-temporal precipitation estimates in data scarce river basins: an application of machine learning-based multi-source data merging J. Mohammed et al. 10.1007/s00477-022-02346-4
14. Reconstructing high-resolution gridded precipitation data in the southwest China highland canyon area using an improved (MGWR) downscaling method L. Wang et al. 10.1016/j.scitotenv.2024.174866
15. Cross Validation of GOES-16 and NOAA Multi-Radar Multi-Sensor (MRMS) QPE over the Continental United States L. Sun et al. 10.3390/rs13204030
16. Comparison of Methods for Filling Daily and Monthly Rainfall Missing Data: Statistical Models or Imputation of Satellite Retrievals? L. Duarte et al. 10.3390/w14193144
17. Assessment and Data Fusion of Satellite-Based Precipitation Estimation Products over Ungauged Areas Based on Triple Collocation without In Situ Observations X. Wu et al. 10.3390/rs15174210
18. Assessment of Merged Satellite Precipitation Datasets in Monitoring Meteorological Drought over Pakistan K. Rahman et al. 10.3390/rs13091662
19. Assimilation of Multi-Source Precipitation Data over Southeast China Using a Nonparametric Framework Y. Zhou et al. 10.3390/rs13061057
20. SMPD: a soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation K. He et al. 10.5194/hess-27-169-2023
21. A framework for merging precipitation retrievals and gauge-based observations based on a novel concept namely virtual gauges Y. Dou et al. 10.1016/j.jhydrol.2023.129506
22. Blending high-resolution satellite rainfall estimates over urban catchment using Bayesian Model Averaging approach W. Asfaw et al. 10.1016/j.ejrh.2022.101287
23. SMPD-MERG: A Hybrid Downscaling Model for High-Resolution Daily Precipitation Estimation via Merging Surface Soil Moisture and Multisource Precipitation Data K. He et al. 10.1109/TGRS.2025.3561253
24. Assessment and Hydrological Validation of Merged Near-Real-Time Satellite Precipitation Estimates Based on the Gauge-Free Triple Collocation Approach D. Cao et al. 10.3390/rs14153835
25. Triple collocation-based error estimation and data fusion of global gridded precipitation products over the Yangtze River basin C. Chen et al. 10.1016/j.jhydrol.2021.127307
26. A Data- and Knowledge-Driven Method for Fusing Satellite-Derived and Ground-Based Precipitation Observations F. Chen et al. 10.1109/TGRS.2024.3385647
27. Quantifying the Reliability and Uncertainty of Satellite, Reanalysis, and Merged Precipitation Products in Hydrological Simulations over the Topographically Diverse Basin in Southwest China H. Lei et al. 10.3390/rs15010213
28. Effective multi-satellite precipitation fusion procedure conditioned by gauge background fields over the Chinese mainland W. Li et al. 10.1016/j.jhydrol.2022.127783
29. Spatial Downscaling of IMERG Considering Vegetation Index Based on Adaptive Lag Phase Z. Zeng et al. 10.1109/TGRS.2021.3070417
30. An Assimilating Model Using Broad Learning System for Incorporating Multi‐Source Precipitation Data With Environmental Factors Over Southeast China Y. Zhou et al. 10.1029/2021EA002043
31. 基于深度学习的青藏高原多源降水融合 天. 南 et al. 10.1360/SSTe-2022-0077
32. A Regional Blended Precipitation Dataset over Pakistan Based on Regional Selection of Blending Satellite Precipitation Datasets and the Dynamic Weighted Average Least Squares Algorithm K. Rahman & S. Shang 10.3390/rs12244009