Articles | Volume 17, issue 11
https://doi.org/10.5194/hess-17-4481-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-4481-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
13 Nov 2013
Research article |
| 13 Nov 2013
Development and comparative evaluation of a stochastic analog method to downscale daily GCM precipitation
S. Hwang
Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, USA
Water Institute, University of Florida, Gainesville, FL, USA
W. D. Graham
Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, USA
Water Institute, University of Florida, Gainesville, FL, USA
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- Assessing the resilience of stormwater ponds under climate change: A case study on Grace Lake, Florida, unveiling flood control and water quality implications R. Davtalab et al. https://doi.org/10.1016/j.jhydrol.2024.130987
- Conditional stochastic simulation model for spatial downscaling for assessing the effects of climate change on hydro-meteorological variables T. Lee & T. Ouarda https://doi.org/10.1007/s10584-018-2276-1
- Potential changes in climate indices in Alberta under projected global warming of 1.5–5 °C H. Eum et al. https://doi.org/10.1016/j.ejrh.2023.101390
- Evaluation of impacts of future climate change and water use scenarios on regional hydrology S. Chang et al. https://doi.org/10.5194/hess-22-4793-2018
- Regional Climate Review: CMIP6 GCM Precipitation Patterns in Northeast India A. Paul & S. Maji https://doi.org/10.1007/s40030-025-00943-4
- Assessment of Climate Change Impacts on Extreme Precipitation Events: Applications of CMIP5 Climate Projections Statistically Downscaled over South Korea J. Sung et al. https://doi.org/10.1155/2018/4720523
- Gaussian Copula Method for Bias Correction of Daily Precipitation Generated by a Dynamical Model M. Kim et al. https://doi.org/10.1175/JAMC-D-18-0089.1
- An intercomparison of multiple statistical downscaling methods for daily precipitation and temperature over China: present climate evaluations Y. Yang et al. https://doi.org/10.1007/s00382-019-04809-x
- The Florida Water and Climate Alliance (FloridaWCA): Developing a Stakeholder–Scientist Partnership to Create Actionable Science in Climate Adaptation and Water Resource Management V. Misra et al. https://doi.org/10.1175/BAMS-D-19-0302.1
- Enhanced performance of CMIP6 climate models in simulating historical precipitation in the Florida Peninsula H. Wang & T. Asefa https://doi.org/10.1002/joc.8479
- Sensitivity of future continental United States water deficit projections to general circulation models, the evapotranspiration estimation method, and the greenhouse gas emission scenario S. Chang et al. https://doi.org/10.5194/hess-20-3245-2016
- Incorporating the logistic regression into a decision-centric assessment of climate change impacts on a complex river system D. Kim et al. https://doi.org/10.5194/hess-23-1145-2019
- Probability Distributions for a Quantile Mapping Technique for a Bias Correction of Precipitation Data: A Case Study to Precipitation Data Under Climate Change J. Heo et al. https://doi.org/10.3390/w11071475
- A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations J. Nahar et al. https://doi.org/10.1016/j.jhydrol.2017.05.045
- Evaluating the aptitude of global climate models fromCMIP5andCMIP6in capturing the historical observations of monsoon rainfall over Sudan from 1946 to 2005 M. Hamadalnel et al. https://doi.org/10.1002/joc.7387
- 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. https://doi.org/10.1109/TGRS.2025.3561253
- Keeping Us Honest: Examining Climate States and Transition Probabilities of Precipitation Projections in General Circulation Models T. Panaou et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000910
- Projected Heat Waves in Ecuador under Climate Change: Insights from HadGEM-RegCM4 Coupled Model D. Portalanza et al. https://doi.org/10.3390/earth5010005
- Comparative evaluation of different satellite rainfall estimation products and bias correction in the Upper Blue Nile (UBN) basin W. Abera et al. https://doi.org/10.1016/j.atmosres.2016.04.017
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- Data processing system and spatial-temporal reproducibility assessment of GloSea5 model https://doi.org/10.3741/JKWRA.2016.49.9.761
- Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies E. Maurer et al. https://doi.org/10.5194/hess-20-685-2016
- Hydrological impacts of climate change on rice cultivated riparian wetlands in the Upper Meghna River Basin (Bangladesh and India) M. Rahman et al. https://doi.org/10.1080/02626667.2019.1676427
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- How to Choose the Most Proper Representative Climate Model Over a Study Region? a Case Study of Precipitation Simulations in Ireland with NEX-GDDP-CMIP6 Data S. Moradian et al. https://doi.org/10.1007/s11269-023-03665-z
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- Bias correction of surface air temperature and precipitation in CORDEX East Asia simulation: What should we do when applying bias correction? J. Chen et al. https://doi.org/10.1016/j.atmosres.2022.106439
- Statistical Downscaling Multimodel Forecasts for Seasonal Precipitation and Surface Temperature over the Southeastern United States D. Tian et al. https://doi.org/10.1175/JCLI-D-13-00481.1
- Development of a climate‐informed analog downscaling method for Asian regions S. Kim et al. https://doi.org/10.1002/joc.7582
- Embedding spatial variability in rainfall field reconstruction L. Duffaut Espinosa et al. https://doi.org/10.1080/01431161.2018.1433894
- GCM‐related uncertainty in forecasting irrigation and design water requirement for paddy rice fields S. Lee et al. https://doi.org/10.1002/joc.5244
- Evaluating the impact of climate change on precipitation in the future period using CMIP6 models (case study: Siminehrood River Basin, Iran) F. Sharifan et al. https://doi.org/10.1007/s11600-025-01612-7
- Assessing climate change impacts on streamflow under uncertainty: multi-metric ensemble GCM selection using TOPSIS and social choice M. Ghasemi & A. Dariane https://doi.org/10.1016/j.rineng.2026.109347
- Alteration of hydrologic indicators for Korean catchments under CMIP5 climate projections M. Shin et al. https://doi.org/10.1002/hyp.10948
- Coupling forecast calibration and data‐driven downscaling for generating reliable, high‐resolution, multivariate seasonal climate forecast ensembles at multiple sites A. Schepen et al. https://doi.org/10.1002/joc.6346
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