48 citations as recorded by crossref.

1. Exploring stochastic climate uncertainty in space and time using a gridded hourly weather generator N. Peleg et al. https://doi.org/10.1016/j.jhydrol.2019.02.010
2. Continuous rainfall generation for a warmer climate using observed temperature sensitivities C. Wasko & A. Sharma https://doi.org/10.1016/j.jhydrol.2016.12.002
3. Regionalization of rainfall for broad‐scale modeling: An inverse approach J. Pinault & D. Allier https://doi.org/10.1029/2006WR005642
4. RainSim: A spatial–temporal stochastic rainfall modelling system A. Burton et al. https://doi.org/10.1016/j.envsoft.2008.04.003
5. Short‐term flood inundation prediction using hydrologic‐hydraulic models forced with downscaled rainfall from global NWP D. Nam et al. https://doi.org/10.1002/hyp.10084
6. Wet and dry spell analysis of Global Climate Model-generated precipitation using power laws and wavelet transforms A. Mishra et al. https://doi.org/10.1007/s00477-010-0419-7
7. A weather-type approach to analysing water resource drought in the Yorkshire region from 1881 to 1998 H. Fowler & C. Kilsby https://doi.org/10.1016/S0022-1694(02)00034-3
8. A transient stochastic weather generator incorporating climate model uncertainty V. Glenis et al. https://doi.org/10.1016/j.advwatres.2015.08.002
9. A nonparametric nonhomogeneous hidden Markov model for downscaling of multisite daily rainfall occurrences R. Mehrotra & A. Sharma https://doi.org/10.1029/2004JD005677
10. Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin A. Murawski et al. https://doi.org/10.5194/hess-20-4283-2016
11. NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process J. Diez-Sierra et al. https://doi.org/10.5194/gmd-16-5035-2023
12. Stochastic Simulation of Nonstationary Rainfall Fields, Accounting for Seasonality and Atmospheric Circulation Pattern Evolution G. Sapriza Azuri et al. https://doi.org/10.1007/s11004-013-9467-0
13. Simulation of Stochastic Processes Exhibiting Any‐Range Dependence and Arbitrary Marginal Distributions I. Tsoukalas et al. https://doi.org/10.1029/2017WR022462
14. Weather types, runoff and sediment yield in a Mediterranean mountain landscape E. Nadal‐Romero et al. https://doi.org/10.1002/esp.3451
15. Current Awareness https://doi.org/10.1002/hyp.469
16. Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes A. Murawski et al. https://doi.org/10.1002/2017JD026654
17. Enhanced efficiency of pluvial flood risk estimation in urban areas using spatial–temporal rainfall simulations J. Blanc et al. https://doi.org/10.1111/j.1753-318X.2012.01135.x
18. Evaluation of machine learning tools as a statistical downscaling tool: temperatures projections for multi-stations for Thames River Basin, Canada M. Goyal et al. https://doi.org/10.1007/s00704-011-0546-1
19. Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user D. Maraun et al. https://doi.org/10.1029/2009RG000314
20. Projections of future streamflow for Australia informed by CMIP6 and previous generations of global climate models H. Zheng et al. https://doi.org/10.1016/j.jhydrol.2024.131286
21. Downscaling GCMs using the Smooth Support Vector Machine method to predict daily precipitation in the Hanjiang Basin H. Chen et al. https://doi.org/10.1007/s00376-009-8071-1
22. Statistical downscaling of precipitation using a stochastic rainfall model conditioned on circulation patterns – an evaluation of assumptions U. Haberlandt et al. https://doi.org/10.1002/joc.3989
23. A stochastic approach to simulate realistic continuous snow depth time series J. Park & D. Kim https://doi.org/10.1016/j.jhydrol.2022.128980
24. Analyzing rainfall patterns and pricing rainfall insurance using copula C. Choi et al. https://doi.org/10.7465/jkdi.2013.24.3.603
25. Precipitation downscaling using the artificial neural network BatNN and development of future rainfall intensity-duration-frequency curves S. Kueh & K. Kuok https://doi.org/10.3354/cr01383
26. Regionalization of precipitation characteristics in the Canadian Prairie Provinces using large-scale atmospheric covariates and geophysical attributes Z. Asong et al. https://doi.org/10.1007/s00477-014-0918-z
27. An advanced stochastic weather generator for simulating 2‐D high‐resolution climate variables N. Peleg et al. https://doi.org/10.1002/2016MS000854
28. Nearest Neighbor–Genetic Algorithm for Downscaling of Climate Change Data from GCMs S. Kim et al. https://doi.org/10.1175/JAMC-D-15-0100.1
29. Pyraingen: A python package for constrained continuous rainfall generation C. Dykman et al. https://doi.org/10.1016/j.envsoft.2024.105984
30. Modeling the impacts of climatic change and variability on the reliability, resilience, and vulnerability of a water resource system H. Fowler et al. https://doi.org/10.1029/2002WR001778
31. Evaluation of the coordinated development of regional water resource systems based on a dynamic coupling coordination model K. Cheng et al. https://doi.org/10.2166/ws.2018.102
32. Retrieval of Hourly Records of Surface Hydrometeorological Variables Using Satellite Remote Sensing Data S. Moghim et al. https://doi.org/10.1175/JHM-D-13-0127.1
33. Stochastic Modeling to Evaluate Effects of Changing Climate on Water Supply Systems Z. Gao et al. https://doi.org/10.1061/JWRMD5.WRENG-7132
34. Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations E. Mockler et al. https://doi.org/10.1016/j.advwatres.2016.10.008
35. Modelling monthly precipitation with circulation weather types for a dense network of stations over Iberia N. Cortesi et al. https://doi.org/10.5194/hess-17-665-2013
36. Ensemble estimation of future rainfall extremes with temperature dependent censored simulation D. Cross et al. https://doi.org/10.1016/j.advwatres.2019.103479
37. Simulation of future climate scenarios with a weather generator S. Fatichi et al. https://doi.org/10.1016/j.advwatres.2010.12.013
38. Spatial-temporal rainfall modelling for flood risk estimation H. Wheater et al. https://doi.org/10.1007/s00477-005-0011-8
39. Reconstruction of hydrometeorological time series and its uncertainties for the Kaidu River Basin using multiple data sources X. Li et al. https://doi.org/10.1007/s00704-012-0771-2
40. A weather-type conditioned multi-site stochastic rainfall model for the generation of scenarios of climatic variability and change H. Fowler et al. https://doi.org/10.1016/j.jhydrol.2004.10.021
41. Downscaling transient climate change using a Neyman–Scott Rectangular Pulses stochastic rainfall model A. Burton et al. https://doi.org/10.1016/j.jhydrol.2009.10.031
42. Impact of climate change on extreme rainfall events and flood risk in India P. GUHATHAKURTA et al. https://doi.org/10.1007/s12040-011-0082-5
43. Comprehensive evaluation of an improved large‐scale multi‐site weather generator for Germany V. Nguyen et al. https://doi.org/10.1002/joc.7107
44. Evaluation of Rule and Decision Tree Induction Algorithms for Generating Climate Change Scenarios for Temperature and Pan Evaporation on a Lake Basin M. Goyal & C. Ojha https://doi.org/10.1061/(ASCE)HE.1943-5584.0000795
45. Precipitation and the North Atlantic Oscillation: a study of climatic variability in northern England H. Fowler & C. Kilsby https://doi.org/10.1002/joc.765
46. Progress in and prospects for fluvial flood modelling D. Cox et al. https://doi.org/10.1098/rsta.2002.1007
47. Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling H. Fowler et al. https://doi.org/10.1002/joc.1556
48. Different Hydroclimate Modelling Approaches Can Lead to a Large Range of Streamflow Projections under Climate Change: Implications for Water Resources Management F. Chiew et al. https://doi.org/10.3390/w14172730