65 citations as recorded by crossref.

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4. Evaluation of Operational National Weather Service Gridded Flash Flood Guidance over the Arkansas Red River Basin D. Seo et al. https://doi.org/10.1111/jawr.12087
5. Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results E. Sharifi et al. https://doi.org/10.3390/rs8020135
6. Evaluation of satellite-based rainfall estimates in the upper Blue Nile basin T. Gado et al. https://doi.org/10.1007/s12040-023-02235-6
7. A comprehensive evaluation of the satellite precipitation products across Iran A. Dehaghani et al. https://doi.org/10.1016/j.ejrh.2023.101360
8. A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield J. Ringard et al. https://doi.org/10.3390/s17061413
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10. Evaluation of PERSIANN family remote sensing precipitation products for snowmelt runoff estimation in a mountainous basin G. Uysal & A. Şorman https://doi.org/10.1080/02626667.2021.1954651
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19. Assessment of two techniques to merge ground-based and TRMM rainfall measurements: a case study about Brazilian Amazon Rainforest P. Mateus et al. https://doi.org/10.1080/15481603.2016.1228161
20. Performance evaluation and correction of precipitation data using the 20-year IMERG and TMPA precipitation products in diverse subregions of China Q. Ma et al. https://doi.org/10.1016/j.atmosres.2020.105304
21. A Comparison of Precipitation Occurrence from the NCEP Stage IV QPE Product and the CloudSat Cloud Profiling Radar M. Smalley et al. https://doi.org/10.1175/JHM-D-13-048.1
22. Evaluation of Satellite-Based Precipitation Products from IMERG V04A and V03D, CMORPH and TMPA with Gauged Rainfall in Three Climatologic Zones in China G. Wei et al. https://doi.org/10.3390/rs10010030
23. Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal N. Krakauer et al. https://doi.org/10.3390/rs5084107
24. Precision of raw and bias-adjusted satellite precipitation estimations (TRMM, IMERG, CMORPH, and PERSIANN) over extreme flood events: case study in Langat river basin, Malaysia E. Soo et al. https://doi.org/10.2166/wcc.2020.180
25. ST-CORAbico: A Spatiotemporal Object-Based Bias Correction Method for Storm Prediction Detected by Satellite M. Laverde-Barajas et al. https://doi.org/10.3390/rs12213538
26. Assessment of Satellite-based Precipitation Products Performance over the Hyper-arid Climate of Kuwait B. AlMutairi https://doi.org/10.1175/JHM-D-20-0300.1
27. The Combined Power of Double Mass Curves and Bias Correction for the Maximisation of the Accuracy of an Ensemble Satellite-Based Precipitation Estimate Product N. Sriwongsitanon et al. https://doi.org/10.3390/hydrology10070154
28. Climatology-Focused Evaluation of CMORPH and TMPA Satellite Rainfall Products over the Nile Basin E. Habib et al. https://doi.org/10.1175/JAMC-D-11-0252.1
29. Retrieval of Rainfall by Combining Rain Gauge, Ground-Based Radar and Satellite Measurements over Phimai, Thailand P. Wetchayont et al. https://doi.org/10.2151/sola.2013-037
30. Bias Adjustment of Four Satellite-Based Rainfall Products Using Ground-Based Measurements over Sudan M. Siddig et al. https://doi.org/10.3390/w14091475
31. A comprehensive evaluation of the accuracy of satellite-based precipitation estimates over Thailand C. Kaprom et al. https://doi.org/10.1016/j.ejrh.2025.102380
32. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data H. Bhatti et al. https://doi.org/10.3390/s16060884
33. Comparing the use of past and forecast weather data for estimating reference evapotranspiration D. Vanella et al. https://doi.org/10.1016/j.agrformet.2020.108196
34. Identification of the Optimum Rain Gauge Network Density for Hydrological Modelling Based on Radar Rainfall Analysis Y. Gyasi-Agyei https://doi.org/10.3390/w12071906
35. Assessment and correction of three satellite rainfall estimate products for improving flood prevention in French Guiana A. Beaufort et al. https://doi.org/10.1080/01431161.2018.1511934
36. Comparative study of rainfall measurement by optical disdrometer, tipping-bucket rain gauge, and weighing precipitation gauge Y. Ro et al. https://doi.org/10.1007/s11069-023-06308-z
37. Assessment and Implications of NCEP Stage IV Quantitative Precipitation Estimates for Product Intercomparisons B. Nelson et al. https://doi.org/10.1175/WAF-D-14-00112.1
38. A multi-source precipitation estimation approach to fill gaps over a radar precipitation field: a case study in the Colorado River Basin K. Tesfagiorgis & S. Mahani https://doi.org/10.1002/hyp.10103
39. A comparative analysis of the precipitation extremes obtained from tropical rainfall‐measuring mission satellite and rain gauges datasets over a semiarid region M. Mahbod et al. https://doi.org/10.1002/joc.5824
40. Enhancement of Satellite Precipitation Estimations with Bias Correction and Data-Merging Schemes for Flood Forecasting E. Soo et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002190
41. River runoff estimation with satellite rainfall in Morocco Y. Tramblay et al. https://doi.org/10.1080/02626667.2023.2171295
42. Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model A. Rahman et al. https://doi.org/10.3389/frwa.2021.789352
43. Evaluation of Tropical Rainfall Measuring Mission, Integrated Multi‐satellite Retrievals for GPM, Climate Hazards Centre InfraRed Precipitation with Station data, and European Centre for Medium‐Range Weather Forecasts Reanalysis v5 data in estimating precipitation and capturing meteorological droughts over Iran M. Keikhosravi‐Kiany et al. https://doi.org/10.1002/joc.7351
44. Bias correction of GPM IMERG Early Run daily precipitation product using near real-time CPC global measurements L. Wei et al. https://doi.org/10.1016/j.atmosres.2022.106403
45. Evaluation of bias-adjusted satellite precipitation estimations for extreme flood events in Langat river basin, Malaysia E. Soo et al. https://doi.org/10.2166/nh.2019.071
46. How Frequent is Precipitation over the Contiguous United States? Perspectives from Ground-Based and Spaceborne Radars M. Smalley et al. https://doi.org/10.1175/JHM-D-16-0242.1
47. Performance evaluation of ERA5 precipitation estimates across Iran A. Malayeri et al. https://doi.org/10.1007/s12517-021-09079-8
48. Bias adjustment of satellite-based precipitation estimation using artificial neural networks-cloud classification system over Saudi Arabia R. Alharbi et al. https://doi.org/10.1007/s12517-018-3860-4
49. Bias adjustment of satellite‐based precipitation estimation using gauge observations: A case study in Chile Z. Yang et al. https://doi.org/10.1002/2015JD024540
50. Improving the accuracy of multimodel short-to-medium-range precipitation and streamflow forecasts over the Upper Bhima river basin, India S. Nandi & M. Janga Reddy https://doi.org/10.1080/02626667.2023.2243257
51. Enhancing Precipitation Estimates Through the Fusion of Weather Radar, Satellite Retrievals, and Surface Parameters Y. Wehbe et al. https://doi.org/10.3390/rs12081342
52. Assessment of satellite precipitation products at different time scales over a cyclone prone coastal river basin in India S. Setti et al. https://doi.org/10.2166/wcc.2022.166
53. Assessment of Satellite-Based Precipitation Estimates over Egypt T. Gado et al. https://doi.org/10.1061/JHYEFF.HEENG-6051
54. Interpreting Satellite Rainfall Bias Correction Through a Rainfall–Runoff Framework in a Monsoon-Influenced River Basin: The Phetchaburi River Basin, Thailand J. Vongphet et al. https://doi.org/10.3390/w18080964
55. In the aftermath of the October 2015 Alexandria Flood Challenges of an Arab city to deal with extreme rainfall storms C. Zevenbergen et al. https://doi.org/10.1007/s11069-016-2724-z
56. Analysis of the IMERG-GPM Precipitation Product Analysis in Brazilian Midwestern Basins Considering Different Time and Spatial Scales L. Duarte et al. https://doi.org/10.3390/w14162472
57. A framework for developing a spatial high-resolution daily precipitation dataset over a data-sparse region F. Yazdandoost et al. https://doi.org/10.1016/j.heliyon.2020.e05091
58. A Pixel-by-Pixel Error Correction Framework of Satellite Products Against Pixel-Scale Ground “Truth” From Sparse Observation Networks: A Case Study of MCD43A3 v061 Across the Globe X. Wu et al. https://doi.org/10.1109/TGRS.2025.3568188
59. Evaluating the Performance of Merged Multi-Satellite Precipitation Products Over a Complex Terrain S. Golian et al. https://doi.org/10.1007/s11269-015-1096-6
60. Comparative Evaluation of Radar–Gauge Fusion and Rain Gauge Rainfall Inputs for Flood Simulation in a Small Pumped-Storage Hydropower Catchment Z. Lin et al. https://doi.org/10.3390/w18151818
61. What does CloudSat reveal about global land precipitation detection by other spaceborne sensors? A. Behrangi et al. https://doi.org/10.1002/2013WR014566
62. An Innovative Correction–Fusion Approach for Multi-Satellite Precipitation Products Conditioned by Gauge Background Fields over the Lancang River Basin L. Nan et al. https://doi.org/10.3390/rs16111824
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64. Evaluating the performance of bias-corrected IMERG satellite rainfall estimates for hydrological simulation over the Upper Bhima River basin, India S. Nandi & M. Janga Reddy https://doi.org/10.1080/10106049.2022.2101695
65. Comparison and Bias-Correction of Satellite-Derived Precipitation Datasets at Local Level in Northern Kenya I. Vigna et al. https://doi.org/10.3390/su12072896