Research graph
References from CMIP6 model ranking and machine learning–assisted ensemble evaluation using a multi-variable integrated MCDM–GDM framework. Local targets link to admitted publications; unresolved targets remain external evidence.
On the projected decline in droughts over south Asia in CMIP6 multimodel ensemble
10.1029/2020jd033587 · 2020 · External reference
The impact of climate indices on precipitation variability in Baluchistan, Pakistan
10.1080/16000870.2020.1833584 · 2020 · External reference
Precipitation modeling of Gwadar Port Baluchistan for environmental sustainability using multilinear regression analysis technique
2022 · External reference
Performance of the general circulation models in simulating temperature and precipitation over Iran
10.1007/s00704-018-2456-y · 2019 · External reference
ESD reviews: model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing
10.5194/esd-10-91-2019 · 2019 · External reference
Development of an artificial neural network based multi-model ensemble to estimate the northeast monsoon rainfall over south peninsular India: an application of extreme learning machine
10.1007/s00382-013-1942-2 · 2014 · External reference
Exploring alternate coupling inputs of a data-driven model for optimum daily streamflow prediction in calibrated SWAT-BiLSTM rainfall-runoff modeling
10.3389/frwa.2025.1558218 · 2025 · External reference
Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics
10.5194/hess-23-4803-2019 · 2019 · External reference
Multi-model ensemble predictions of precipitation and temperature using machine learning algorithms
10.1016/j.atmosres.2019.104806 · 2020 · External reference
Projections of precipitation and temperature over the south Asian countries in CMIP6
10.1007/s41748-020-00157-7 · 2020 · External reference
Evaluation and comparison of the performances of the CMIP5 and CMIP6 models in reproducing extreme rainfall in the Upper Blue Nile Basin of Ethiopia
10.1007/s00704-024-05187-z · 2024 · External reference
Unresolved reference
2008 · External reference
10.59327/ipcc/ar6-9789291691647
10.59327/ipcc/ar6-9789291691647 · External reference
Bias correction of GCM precipitation by quantile mapping: how well do methods preserve changes in quantiles and extremes?
10.1175/jcli-d-14-00754.1 · 2015 · External reference
Climate change impacts on water resources and reservoir management: uncertainty and adaptation for a mountain catchment in Northeast Portugal
10.1007/s11269-017-1672-z · 2017 · External reference
Exploring climate-change impacts on streamflow and hydropower potential: insights from CMIP6 multi-GCM analysis
10.2166/wcc.2024.150 · 2024 · External reference
Impacts of weighting climate models for hydro-meteorological climate change studies
10.1016/j.jhydrol.2017.04.025 · 2017 · External reference
Comparative study of GCMs, RCMs, downscaling and hydrological models: a review toward future climate change impact estimation
10.1007/s42452-019-1764-x · 2019 · External reference
Developing climate model ensembles: a comparative case study
10.1016/j.jhydrol.2018.10.054 · 2019 · External reference
Performance assessment of general circulation models: application of compromise programming method and global performance indicator technique
10.1007/s00477-021-02124-8 · 2022 · External reference
Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization
10.5194/gmd-9-1937-2016 · 2016 · External reference
Climate change quadruples flood-causing extreme monsoon rainfall events in Bangladesh and northeast India
10.1002/qj.4645 · 2024 · External reference
Assessing responses of hydrological processes to climate change over the southeastern Tibetan Plateau based on resampling of future climate scenarios
10.1016/j.scitotenv.2019.02.013 · 2019 · External reference
Status of automatic calibration for hydrologic models: comparison with multilevel expert calibration
10.1061/(asce)1084-0699(1999)4:2(135) · 1999 · External reference
Assessing climate change impacts on future precipitation using random forest statistical downscaling of CMIP6 HadGEM3 projections in the Büyük Menderes Basin
10.3390/w18020277 · 2026 · External reference
Added value of CMIP6 over CMIP5 models in simulating Indian summer monsoon rainfall
10.1016/j.atmosres.2019.104680 · 2020 · External reference
Tropical anvil clouds and climate sensitivity
10.1073/pnas.1610455113 · 2016 · External reference
Selecting a climate model subset to optimise key ensemble properties
10.5194/esd-9-135-2018 · 2018 · External reference
A methodology for selecting climate models considering precipitation and temperature for modeling runoff
10.1007/s11269-025-04387-0 · 2026 · External reference
Unresolved reference
1992 · External reference
Changes of storm properties in the United States: observations and multimodel ensemble projections
10.1016/j.gloplacha.2016.05.001 · 2016 · External reference
Measurement of GCM skill in predicting variables relevant for hydroclimatological assessments
10.1175/2009jcli2681.1 · 2009 · External reference
Improving multiple model ensemble predictions of daily precipitation and temperature through machine learning techniques
10.1038/s41598-022-08786-w · 2022 · External reference
Performance assessment of general circulation model in simulating daily precipitation and temperature using multiple gridded datasets
10.3390/w10121793 · 2018 · External reference
Evaluation of the CMIP6 multi-model ensemble for climate extreme indices
10.1016/j.wace.2020.100269 · 2020 · External reference
A new class of climate hazard metrics and its demonstration: revealing a ten-fold increase of extreme heat over Europe
10.1016/j.wace.2026.100855 · 2026 · External reference
Challenges in combining projections from multiple climate models
10.1175/2009jcli3361.1 · 2010 · External reference
How the performance of hydrological models relates to credibility of projections under climate change
10.1080/02626667.2018.1446214 · 2018 · External reference
Multi-criteria decision-making and machine learning-based CMIP6 general circulation model ensemble for climate projections in a tropical river basin in India
10.1007/s11600-025-01623-4 · 2025 · External reference
Developing a multimodel ensemble framework for improved streamflow simulation in the Amudarya River Basin
10.1175/jhm-d-25-0055.1 · 2025 · External reference
Development of multi-model ensemble of CMIP6 GCMs using MCDM techniques for future climate projections in Mahanadi River Basin
10.1007/s00704-026-06098-x · 2026 · External reference
Ranking the AR4 climate models over the Murray-Darling Basin using simulated maximum temperature, minimum temperature and precipitation
10.1002/joc.1612 · 2008 · External reference
Selecting CMIP5 GCMs for downscaling over multiple regions
10.1007/s00382-014-2418-8 · 2015 · External reference
Model evaluation guidelines for systematic quantification of accuracy in watershed simulations
10.13031/2013.23153 · 2007 · External reference
Development of a new high spatial resolution (0.25° × 0.25°) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region
10.54302/mausam.v65i1.851 · 2014 · External reference
Identification of best CMIP6 global climate model for rainfall by ensemble implementation of MCDM methods and statistical inference
10.1007/s11269-023-03599-6 · 2023 · External reference
Evaluation of optimal normalization techniques in multi-criteria decision-making to rank CMIP6 climate models
10.1007/s00704-025-05617-6 · 2025 · External reference
A comparative approach to understand the performance of CMIP6 models for maximum temperature near tropic of cancer using multiple machine learning ensembles
10.1007/s11269-025-04137-2 · External reference
Evaluation of optimal normalization techniques in multi-criteria decision-making to rank CMIP6 climate models
10.1007/s00704-025-05617-6 · External reference
VII. Note on regression and inheritance in the case of two parents
10.1098/rspl.1895.0041 · 1895 · External reference
Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions
10.1175/jcli4253.1 · 2007 · External reference
Evaluation and ranking of NEX-GDDP-CMIP6 models based on monthly precipitation climatology over Indonesia
10.3389/fclim.2026.1748663 · 2026 · External reference
Extreme precipitation indices over India using CMIP6: a special emphasis on the SSP585 scenario
10.1007/s11356-023-25649-7 · 2023 · External reference
Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs
10.1016/j.jhydrol.2017.02.016 · 2018 · External reference
Evaluation of CMIP5 20th century climate simulations for the Pacific Northwest USA
2013 · External reference
Statistical downscaling of precipitation using machine learning techniques
10.1016/j.atmosres.2018.05.022 · 2018 · External reference
A representative democracy to reduce interdependency in a multimodel ensemble
10.1175/jcli-d-14-00362.1 · 2015 · External reference
Evaluation of coupled model intercomparison project phase 6 models in simulating precipitation and its possible relationship with sea surface temperature over Myanmar
10.3389/fenvs.2022.993802 · 2022 · External reference
Sustainable supplier selection of E-commerce industry in Bangladesh: an integrated TOPSIS-AHP approach
10.1002/eng2.70636 · 2026 · External reference
The effectiveness of machine learning-based multi-model ensemble predictions of CMIP6 in Western Ghats of India
10.1002/joc.8131 · 2023 · External reference
Projected intensification of precipitation extremes in the Kosi Basin using CMIP6 models
10.1038/s41598-026-43723-1 · 2026 · External reference
Refining rainfall projections for the Murray Darling Basin of South-East Australia – the effect of sampling model results based on performance
10.1007/s10584-009-9757-1 · 2010 · External reference
Uncertainty in science and its role in climate policy
10.1098/rsta.2011.0149 · 2011 · External reference
Ranking of CMIP5-based global climate models using standard performance metrics for Telangana region in the southern part of India
10.1080/09715010.2019.1634648 · 2021 · External reference
Ranking of CMIP5-based global climate models for India using compromise programming
10.1007/s00704-015-1721-6 · 2017 · External reference
Statistical downscaling of CMIP5 multi-model ensemble for projected changes of climate in the Indus River Basin
10.1016/j.atmosres.2016.03.023 · 2016 · External reference
Summarizing multiple aspects of model performance in a single diagram
10.1029/2000jd900719 · 2001 · External reference
Bias correction of regional climate model simulations for hydrological climate-change impact studies: review and evaluation of different methods
10.1016/j.jhydrol.2012.05.052 · 2012 · External reference
NASA global daily downscaled projections, CMIP6
10.1038/s41597-022-01393-4 · 2022 · External reference
Intercomparison of statistical and dynamical downscaling models under the EURO- and MED-CORDEX initiative framework: present climate evaluations
10.1007/s00382-015-2647-5 · 2016 · External reference
Ranking of CMIP 6 climate models in simulating precipitation over India
10.1007/s11600-024-01313-7 · 2024 · External reference
Large-scale atmospheric teleconnections and spatiotemporal variability of extreme rainfall indices across India
10.1016/j.jhydrol.2023.130584 · 2024 · External reference
Global climate model performance over Alaska and Greenland
10.1175/2008jcli2163.1 · 2008 · External reference
Risks of model weighting in multimodel climate projections
10.1175/2010jcli3594.1 · 2010 · External reference
Connections and causes of inter-model spread in boreal summer precipitation across monsoon regions in AMIP6 simulations
10.1038/s41598-025-29928-w · 2025 · External reference
A framework for assessing uncertainties in climate change impacts: low-flow scenarios for the River Thames, UK
10.1029/2005wr004065 · 2006 · External reference
Statistical downscaling of general circulation model output: a comparison of methods
10.1029/98wr02577 · 1998 · External reference
Recent cloud controlling factor analyses indicate higher climate sensitivity
10.1029/2025gl118366 · 2026 · External reference
Evaluation and projection of CMIP6 simulations of climate variables for the Rift Valley Lakes Basin, Ethiopia
10.1007/s00704-025-05356-8 · 2025 · External reference
Quantification of precipitation and temperature uncertainties simulated by CMIP3 and CMIP5 models
10.1002/2015jd023719 · 2016 · External reference
Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs
10.1023/b:clim.0000013685.99609.9e · 2004 · External reference
The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6
10.5194/gmd-12-1573-2019 · 2019 · External reference
A CMIP6-ensemble-based evaluation of precipitation and temperature projections
10.1007/s00704-024-05066-7 · 2024 · External reference
Climate change projections through optimized machine learning and deep learning models: a comprehensive analysis
10.58491/2735-4202.3334 · 2025 · External reference
Responses of the hydrological regime to variations in meteorological factors under climate change of the Tibetan plateau
10.1016/j.atmosres.2018.08.008 · 2018 · External reference
