41 citations as recorded by crossref.

1. Flood hazard assessment using design rainfall under climate change scenarios in the Kelantan River Basin, Malaysia T. Tam et al. https://doi.org/10.1108/IJDRBE-05-2022-0048
2. Subglacial hydrology from high-resolution ice-flow simulations of the Rhine Glacier during the Last Glacial Maximum: a proxy for glacial erosion D. Cohen et al. https://doi.org/10.5194/egqsj-72-189-2023
3. The role of land cover in the climate of glacial Europe P. Velasquez et al. https://doi.org/10.5194/cp-17-1161-2021
4. An integrated high-resolution WRF-BEPS framework for improving the meteorological forcings in hourly mountain vegetation GPP estimation T. Yang et al. https://doi.org/10.1016/j.agrformet.2026.111254
5. Bias corrections of ERA5 and ERA5-land temperature using automatic weather station data in the Higher Central Himalaya: implications for hydro-meteorological and glaciological research S. Satyapragyan et al. https://doi.org/10.1016/j.ejrh.2025.103079
6. Enhancing crop protection through smart autonomous pesticide spray bot in sustainable agriculture A. Meshram et al. https://doi.org/10.1088/2631-8695/ad9545
7. High-resolution LGM climate of Europe and the Alpine region using the regional climate model WRF E. Russo et al. https://doi.org/10.5194/cp-20-449-2024
8. Quantile mapping bias correction methods to IMDAA reanalysis for calibrating NCMRWF unified model operational forecasts K. Niranjan Kumar et al. https://doi.org/10.1080/02626667.2022.2049272
9. Projected mean and extreme precipitation based on bias-corrected simulation outputs of CORDEX Southeast Asia S. Ngai et al. https://doi.org/10.1016/j.wace.2022.100484
10. Atmosphere–cryosphere interactions during the last phase of the Last Glacial Maximum (21 ka) in the European Alps C. Del Gobbo et al. https://doi.org/10.5194/cp-19-1805-2023
11. A Method to Assess and Explain Changes in Sub‐Daily Precipitation Return Levels From Convection‐Permitting Simulations E. Dallan et al. https://doi.org/10.1029/2023WR035969
12. Evaluating the robustness of IMD gridded data of temperature and rainfall with/without statistical bias correction techniques A. Krishna et al. https://doi.org/10.1007/s12517-025-12303-4
13. Improved modelling of mountain snowpacks with spatially distributed precipitation bias correction derived from historical reanalysis M. von Kaenel & S. Margulis https://doi.org/10.5194/tc-19-3309-2025
14. A review of past changes in extratropical cyclones in the northern hemisphere and what can be learned for the future C. Raible et al. https://doi.org/10.1002/wcc.680
15. Correcting bias of satellite rainfall data using physical empirical model G. Ziarh et al. https://doi.org/10.1016/j.atmosres.2020.105430
16. Last Glacial Maximum glacier fluctuations on the northern Alpine foreland: Geomorphological and chronological reconstructions from the Rhine and Reuss glacier systems S. Kamleitner et al. https://doi.org/10.1016/j.geomorph.2022.108548
17. Bias correction of precipitation from convection-permitting models at the point scale: a case study in Switzerland T. Nguyen et al. https://doi.org/10.1007/s10584-025-04079-z
18. Contrasting impacts of two mesoscale cyclones on the South Shetland Islands' glaciers, northern Antarctic Peninsula C. Torres et al. https://doi.org/10.1002/qj.5052
19. Climate Projections for Precipitation and Temperature Indicators in the Douro Wine Region: The Importance of Bias Correction J. Martins et al. https://doi.org/10.3390/agronomy11050990
20. Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM) Z. Xu & A. Di Vittorio https://doi.org/10.1016/j.jhydrol.2021.126646
21. Investigation of model forecast biases and skilful prediction for Assam heavy rainfall 2022 V. Vishwakarma et al. https://doi.org/10.1016/j.wace.2024.100678
22. Sensitivity of precipitation and temperature over the Mount Kenya area to physics parameterization options in a high-resolution model simulation performed with WRFV3.8.1 M. Messmer et al. https://doi.org/10.5194/gmd-14-2691-2021
23. Speleothem growth and stable carbon isotopes as proxies of the presence and thermodynamical state of glaciers compared to modelled glacier evolution in the Alps V. Skiba et al. https://doi.org/10.1016/j.quascirev.2023.108403
24. How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation? E. Dallan et al. https://doi.org/10.5194/hess-27-1133-2023
25. Analysis of Linear Scaling Method in Downscaling Precipitation and Temperature A. Azman et al. https://doi.org/10.1007/s11269-021-03020-0
26. Integrating machine learning and zoning-based techniques for bias correction in gridded precipitation data to improve hydrological estimation in the data-scarce region T. Meema et al. https://doi.org/10.1016/j.jhydrol.2024.132356
27. Bias-corrected high-resolution precipitation datasets assessment over a tropical mountainous region in Colombia: A case of study in Upper Cauca River Basin C. Romero-Hernández et al. https://doi.org/10.1016/j.jsames.2024.104898
28. Augmenting precipitation datasets: A comparative study of topographic-based corrections and collocation techniques considering orographic effects M. Besharatifar et al. https://doi.org/10.1016/j.atmosres.2025.108317
29. Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3.8.1 S. González-Rojí et al. https://doi.org/10.5194/gmd-15-2859-2022
30. Multivariate adjustment of drizzle bias using machine learning in European climate projections G. Lazoglou et al. https://doi.org/10.5194/gmd-17-4689-2024
31. Coupled climate-glacier modelling of the last glaciation in the Alps G. Jouvet et al. https://doi.org/10.1017/jog.2023.74
32. Temporal disaggregation of hourly precipitation under changing climate over the Southeast United States B. Takhellambam et al. https://doi.org/10.1038/s41597-022-01304-7
33. Comparison of Bias Correction Methods for Summertime Daily Rainfall in South Korea Using Quantile Mapping and Machine Learning Model G. Seo & J. Ahn https://doi.org/10.3390/atmos14071057
34. How does bias correction impact simulated drought characteristics by Regional Climate Models? P. Nguyen-Ngoc-Bich et al. https://doi.org/10.1007/s10584-025-03901-y
35. The role of ice-sheet topography in the Alpine hydro-climate at glacial times P. Velasquez et al. https://doi.org/10.5194/cp-18-1579-2022
36. Evaluation of root zone soil moisture products over the Huai River basin E. Liu et al. https://doi.org/10.5194/hess-28-2375-2024
37. Seasonal Bias Correction of Daily Precipitation over France Using a Stitch Model Designed for Robust Representation of Extremes P. Ear et al. https://doi.org/10.3390/atmos16040480
38. Performance assessment of neural network models for seasonal weather forecast postprocessing in the Alpine region S. Uttarwar et al. https://doi.org/10.1016/j.advwatres.2025.105061
39. Implications of WRF model resolutions on resolving rainfall variability with topography over East Africa A. Mwanthi et al. https://doi.org/10.3389/fclim.2024.1311088
40. Performance assessment of six bias correction methods using observed and RCM data at upper Awash basin, Oromia, Ethiopia B. Tumsa https://doi.org/10.2166/wcc.2021.181
41. Vegetation, hydrology, and quantitative monsoon precipitation since the Last Glacial Maximum in Central China Z. Huang et al. https://doi.org/10.1016/j.gloplacha.2023.104298