129 citations as recorded by crossref.

1. Fusion of Multiple Gridded Biomass Datasets for Generating a Global Forest Aboveground Biomass Map Y. Zhang & S. Liang 10.3390/rs12162559
2. Historical and future runoff changes in the Yangtze River Basin from CMIP6 models constrained by a weighting strategy J. Zhao et al. 10.1088/1748-9326/ac3f61
3. Characterization of long period return values of extreme daily temperature and precipitation in the CMIP6 models: Part 1, model evaluation M. Wehner et al. 10.1016/j.wace.2020.100283
4. Global terrestrial water storage and drought severity under climate change Y. Pokhrel et al. 10.1038/s41558-020-00972-w
5. Using indices of atmospheric circulation to refine southern Australian winter rainfall climate projections M. Grose et al. 10.1007/s00382-019-04880-4
6. Understanding the Distribution of Multimodel Ensembles B. Christiansen 10.1175/JCLI-D-20-0186.1
7. Precipitation projections over the Indus River Basin of Pakistan for the 21st century using a statistical downscaling framework M. Pomee & E. Hertig 10.1002/joc.7244
8. Bayesian Model Averaging of Climate Model Projections Constrained by Precipitation Observations over the Contiguous United States E. Massoud et al. 10.1175/JHM-D-19-0258.1
9. Optimal reliability ensemble averaging approach for robust climate projections over China Y. Gao et al. 10.1002/joc.8485
10. Asian water tower evinced in total column water vapor: a comparison among multiple satellite and reanalysis data sets Y. Zhao & T. Zhou 10.1007/s00382-019-04999-4
11. Assessment of uncertainty in multi‐model means of downscaled South Florida precipitation for projected (2019–2099) climate J. Infanti et al. 10.1002/joc.6365
12. Projection and Uncertainty Analysis of Future Temperature Change over the Yarlung Tsangpo-Brahmaputra River Basin Based on CMIP6 Z. Xu et al. 10.3390/w15203595
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14. Amplification of compound hot-dry extremes and associated population exposure over East Africa B. Ayugi et al. 10.1007/s10584-024-03802-6
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16. Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle L. Teckentrup et al. 10.5194/esd-14-549-2023
17. Spatiotemporal Reliability Ensemble Averaging of Multimodel Simulations G. Tegegne et al. 10.1029/2019GL083053
18. Taking climate model evaluation to the next level V. Eyring et al. 10.1038/s41558-018-0355-y
19. Establishing a Range of Extreme Precipitation Estimates in California for Planning in the Face of Climate Change D. Feldman et al. 10.1061/(ASCE)WR.1943-5452.0001410
20. RECCAP2 Future Component: Consistency and Potential for Regional Assessment to Constrain Global Projections C. Jones et al. 10.1029/2023AV001024
21. Constraining CMIP6 Projections of an Ice‐Free Arctic Using a Weighting Scheme J. Zhao et al. 10.1029/2022EF002708
22. The future of extreme meteorological fire danger under climate change scenarios for Iberia V. Bento et al. 10.1016/j.wace.2023.100623
23. Causal networks for climate model evaluation and constrained projections P. Nowack et al. 10.1038/s41467-020-15195-y
24. Exploring the Multiverse of Analytical Decisions in Scaling Educational Large-Scale Assessment Data: A Specification Curve Analysis for PISA 2018 Mathematics Data A. Robitzsch 10.3390/ejihpe12070054
25. Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa S. Kolusu et al. 10.1007/s10584-021-02991-8
26. Learning algorithms allow for improved reliability and accuracy of global mean surface temperature projections E. Strobach & G. Bel 10.1038/s41467-020-14342-9
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28. Biased estimates of the isotope ratios of steady‐state evaporation from the assumption of equilibrium between vapour and precipitation R. Fiorella et al. 10.1002/hyp.13531
29. The need for carbon-emissions-driven climate projections in CMIP7 B. Sanderson et al. 10.5194/gmd-17-8141-2024
30. Precipitation regime change in Western North America: The role of Atmospheric Rivers A. Gershunov et al. 10.1038/s41598-019-46169-w
31. Constraining Uncertainties in CMIP5 Projections of September Arctic Sea Ice Extent with Observations D. Senftleben et al. 10.1175/JCLI-D-19-0075.1
32. Water scarcity down to earth surface in a Mediterranean climate: The extreme future of soil moisture in Portugal P. Soares & D. Lima 10.1016/j.jhydrol.2022.128731
33. A Markov chain method for weighting climate model ensembles M. Kulinich et al. 10.5194/gmd-14-3539-2021
34. Influence of Environmental Factors on the Site Selection and Layout of Ancient Military Towns (Zhejiang Region) L. Tan et al. 10.3390/su14052572
35. Similarities within a multi-model ensemble: functional data analysis framework E. Holtanová et al. 10.5194/gmd-12-735-2019
36. Selecting and weighting dynamical models using data-driven approaches P. Le Bras et al. 10.5194/npg-31-303-2024
37. Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3 J. Lee et al. 10.5194/gmd-17-3919-2024
38. Weighting climate models for hydrological projections: effects on contrasting hydroclimatic regions M. Castaneda-Gonzalez et al. 10.1007/s10584-023-03643-9
39. Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications A. Merrifield et al. 10.5194/gmd-16-4715-2023
40. The Effect of Statistical Downscaling on the Weighting of Multi-Model Ensembles of Precipitation A. Wootten et al. 10.3390/cli8120138
41. Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence M. Amos et al. 10.5194/acp-20-9961-2020
42. Implications of climate model selection for projections of decision-relevant metrics: A case study of chill hours in California K. Jagannathan et al. 10.1016/j.cliser.2020.100154
43. Prospects and Caveats of Weighting Climate Models for Summer Maximum Temperature Projections Over North America R. Lorenz et al. 10.1029/2017JD027992
44. Ranking CMIP5 GCMs for Model Ensemble Selection on Regional Scale: Case Study of the Indochina Region R. Chhin & S. Yoden 10.1029/2017JD028026
45. Why we need lower-performance climate models R. O’Loughlin 10.1007/s10584-023-03661-7
46. Bringing it all together: science priorities for improved understanding of Earth system change and to support international climate policy C. Jones et al. 10.5194/esd-15-1319-2024
47. An Integrated Modeling Framework in Projections of Hydrological Extremes H. Meresa et al. 10.1007/s10712-022-09737-w
48. On the Choice of the Item Response Model for Scaling PISA Data: Model Selection Based on Information Criteria and Quantifying Model Uncertainty A. Robitzsch 10.3390/e24060760
49. Grappling with uncertainties in physical climate impact projections of water resources R. Dankers & Z. Kundzewicz 10.1007/s10584-020-02858-4
50. Impacts of climate change on the food-water nexus in central Arizona X. Guan & G. Mascaro 10.1016/j.agrformet.2023.109413
51. Global Climate Model Ensemble Approaches for Future Projections of Atmospheric Rivers E. Massoud et al. 10.1029/2019EF001249
52. Projected Changes to Hydroclimate Seasonality in the Continental United States K. Marvel et al. 10.1029/2021EF002019
53. Projected wave climate temporal variability due to climate change A. Loarca et al. 10.1007/s00477-020-01946-2
54. Emergent constraints on equilibrium climate sensitivity in CMIP5: do they hold for CMIP6? M. Schlund et al. 10.5194/esd-11-1233-2020
55. ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing G. Abramowitz et al. 10.5194/esd-10-91-2019
56. Assessing sensitivities of climate model weighting to multiple methods, variables, and domains in the south-central United States A. Wootten et al. 10.5194/esd-14-121-2023
57. Effective sample size for precipitation estimation in atmospheric general circulation model ensemble experiments: dependence on temporal and spatial averaging scales K. Hibino & I. Takayabu 10.1007/s10584-020-02886-0
58. Application-specific optimal model weighting of global climate models: A red tide example A. Elshall et al. 10.1016/j.cliser.2022.100334
59. Projecting Response of Ecological Vulnerability to Future Climate Change and Human Policies in the Yellow River Basin, China X. Zhang et al. 10.3390/rs16183410
60. 21st Century alpine climate change S. Kotlarski et al. 10.1007/s00382-022-06303-3
61. Fighting big data and ensemble fatigue in climate change impact studies: Can we turn the ensemble cascade upside down? E. Van Uytven et al. 10.1002/joc.6696
62. An Approach for Selecting Observationally-Constrained Global Climate Model Ensembles for Regional Climate Impacts and Adaptation Studies in Canada D. Jeong & A. Cannon 10.1080/07055900.2023.2239194
63. Future changes of socioeconomic exposure to potential landslide hazards over mainland China D. Li et al. 10.1016/j.wace.2024.100731
64. Business risk and the emergence of climate analytics T. Fiedler et al. 10.1038/s41558-020-00984-6
65. Toward Consistent Observational Constraints in Climate Predictions and Projections G. Hegerl et al. 10.3389/fclim.2021.678109
66. Distribution-based pooling for combination and multi-model bias correction of climate simulations M. Vrac et al. 10.5194/esd-15-735-2024
67. Reducing uncertainty in local temperature projections S. Qasmi & A. Ribes 10.1126/sciadv.abo6872
68. Hydrological benefits of restoring wildfire regimes in the Sierra Nevada persist in a warming climate E. Rakhmatulina et al. 10.1016/j.jhydrol.2020.125808
69. Development of a Hoisting Safety Risk Framework Based on the STAMP Theory and PLS-SEM Method Y. Junjia et al. 10.1109/ACCESS.2024.3453929
70. Does the weighting of climate simulations result in a better quantification of hydrological impacts? H. Wang et al. 10.5194/hess-23-4033-2019
71. Inferences of Groundwater Response to Projected Hydroclimatic Changes in North Florida F. Gordu & M. Nachabe 10.1061/JHYEFF.HEENG-5827
72. Comparing Methods to Constrain Future European Climate Projections Using a Consistent Framework L. Brunner et al. 10.1175/JCLI-D-19-0953.1
73. Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles M. Zumwald et al. 10.1002/wcc.654
74. Evaluating the sensitivity of robust water resource interventions to climate change scenarios R. Geressu et al. 10.1016/j.crm.2022.100442
75. A multi-variable constrained ensemble of regional climate projections under multi-scenarios for Portugal – Part I: An overview of impacts on means and extremes D. Lima et al. 10.1016/j.cliser.2023.100351
76. The role of crop simulation modeling in assessing potential climate change impacts D. Timlin et al. 10.1002/agg2.20453
77. Ranking of CMIP5-based global climate models using standard performance metrics for Telangana region in the southern part of India K. Sreelatha & P. Anand Raj 10.1080/09715010.2019.1634648
78. Past and future adverse response of terrestrial water storages to increased vegetation growth in drylands K. Liu et al. 10.1038/s41612-023-00437-9
79. Selecting a climate model subset to optimise key ensemble properties N. Herger et al. 10.5194/esd-9-135-2018
80. Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2°C with Consideration of Model Performance and Independence T. Li et al. 10.1007/s13351-021-0067-5
81. Developing Representative Impact Scenarios From Climate Projection Ensembles, With Application to UKCP18 and EURO‐CORDEX Precipitation S. Jewson et al. 10.1029/2022MS003038
82. Climate data uncertainty for agricultural impact assessments in West Africa P. Romanovska et al. 10.1007/s00704-023-04430-3
83. A temperature binning approach for multi-sector climate impact analysis M. Sarofim et al. 10.1007/s10584-021-03048-6
84. Emergent Constraints on CMIP6 Climate Warming Projections: Contrasting Cloud- and Surface Temperature–Based Constraints Y. Liang et al. 10.1175/JCLI-D-21-0468.1
85. Wetter California Projected by CMIP6 Models With Observational Constraints Under a High GHG Emission Scenario F. Li et al. 10.1029/2022EF002694
86. Assessing the stability of terrestrial water storage to drought based on CMIP6 forcing scenarios W. Wei et al. 10.1016/j.jhydrol.2024.132232
87. Reducing the Uncertainty in the Tropical Precipitation through a Multi‐Criteria Decision‐Making Approach A. Majhi et al. 10.1002/joc.8665
88. Ensemble optimisation, multiple constraints and overconfidence: a case study with future Australian precipitation change N. Herger et al. 10.1007/s00382-019-04690-8
89. Prescreening-Based Subset Selection for Improving Predictions of Earth System Models With Application to Regional Prediction of Red Tide A. Elshall et al. 10.3389/feart.2022.786223
90. Change in Precipitation over the Tibetan Plateau Projected by Weighted CMIP6 Models Y. Zhao et al. 10.1007/s00376-022-1401-2
91. Limited comparability of global and local estimates of environmental flow requirements to sustain river ecosystems M. Messager et al. 10.1088/1748-9326/ad1cb5
92. Projected urban flood risk assessment under climate change and urbanization based on an optimized multi-scale geographically weighted regression F. Han et al. 10.1016/j.scs.2024.105642
93. Effects of anthropogenic climate change on the compound drought and heat events in different agricultural regions of China J. Yang et al. 10.1016/j.ecolind.2024.112719
94. Quantifying uncertainty in European climate projections using combined performance-independence weighting L. Brunner et al. 10.1088/1748-9326/ab492f
95. A dependent multimodel approach to climate prediction with Gaussian processes M. Thompson et al. 10.1017/eds.2022.24
96. Beyond equilibrium climate sensitivity R. Knutti et al. 10.1038/ngeo3017
97. The potential for structural errors in emergent constraints B. Sanderson et al. 10.5194/esd-12-899-2021
98. Unrevealing past and future vegetation restoration on the Loess Plateau and its impact on terrestrial water storage K. Liu et al. 10.1016/j.jhydrol.2022.129021
99. Sensitivity of future climate change and uncertainty over India to performance-based model weighting R. Singh & K. AchutaRao 10.1007/s10584-019-02643-y
100. Future extreme hourly wet bulb temperatures using downscaled climate model projections of temperature and relative humidity M. Alessi & A. DeGaetano 10.1007/s00704-020-03368-0
101. Interdependency in Multimodel Climate Projections: Component Replication and Result Similarity J. Boé 10.1002/2017GL076829
102. Changes in temperature and precipitation in the instrumental period (1951–2018) and projections up to 2100 in Podgorica (Montenegro) D. Burić & M. Doderović 10.1002/joc.6671
103. Constraining Uncertainty in Projected Gross Primary Production With Machine Learning M. Schlund et al. 10.1029/2019JG005619
104. A SPATIOTEMPORAL-AWARE WEIGHTING SCHEME FOR IMPROVING CLIMATE MODEL ENSEMBLE PREDICTIONS M. Fan et al. 10.1615/JMachLearnModelComput.2022046715
105. Probabilistic projection of extreme precipitation changes over Iran by the CMIP6 multi-model ensemble S. Khansalari & A. Mohammadi 10.1007/s10584-024-03771-w
106. CH2018 – National climate scenarios for Switzerland: How to construct consistent multi-model projections from ensembles of opportunity S. Sørland et al. 10.1016/j.cliser.2020.100196
107. Calibrating Climate Model Ensembles for Assessing Extremes in a Changing Climate N. Herger et al. 10.1029/2018JD028549
108. The future of Iberian droughts: a deeper analysis based on multi-scenario and a multi-model ensemble approach P. Soares et al. 10.1007/s11069-023-05938-7
109. Demystifying global climate models for use in the life sciences D. Schoeman et al. 10.1016/j.tree.2023.04.005
110. Assessing and reducing the environmental impact of dairy production systems in the northern US in a changing climate K. Veltman et al. 10.1016/j.agsy.2021.103170
111. Running to warmer-drier springs in the Greater Mekong Subregion as climate warms Z. Dong et al. 10.1016/j.atmosres.2024.107606
112. Sign of Observed California Temperature Trends Depends on Data Set Homogenization: Implications for Weighting and Downscaling A. Charn et al. 10.1029/2022GL099186
113. Regional evaluation of global climate models for precipitation, maximum and minimum temperature over southern-part of India K. Sreelatha & P. AnandRaj 10.1080/09715010.2020.1779137
114. Exploration of diverse solutions for the calibration of imperfect climate models S. Peatier et al. 10.5194/esd-15-987-2024
115. A surrogate weighted mean ensemble method to reduce the uncertainty at a regional scale for the calculation of potential evapotranspiration B. Yoo et al. 10.1038/s41598-020-57466-0
116. Ensembles for Viticulture Climate Classifications of the Willamette Valley Wine Region B. Skahill et al. 10.3390/cli9090140
117. Quantifying the Value of Learning for Flexible Water Infrastructure Planning J. Skerker et al. 10.1029/2022WR034412
118. Informing Future Risks of Record‐Level Rainfall in the United States B. Sanderson et al. 10.1029/2019GL082362
119. Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections Z. Nicholls et al. 10.1029/2020EF001900
120. Evaluation of Satellite and Reanalysis Precipitable Water Vapor Data Sets Against Radiosonde Observations in Central Asia J. Jiang et al. 10.1029/2019EA000654
121. Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates G. Quetin et al. 10.1029/2019MS001889
122. Combining global climate models using graph cuts S. Thao et al. 10.1007/s00382-022-06213-4
123. Uncovering the shortcomings of a weather typing method E. Van Uytven et al. 10.5194/hess-24-2671-2020
124. Benchmarking Simulated Precipitation Variability Amplitude across Time Scales M. Ahn et al. 10.1175/JCLI-D-21-0542.1
125. Pareto‐Optimal Estimates of California Precipitation Change B. Langenbrunner & J. Neelin 10.1002/2017GL075226
126. Evaluation of CMIP6 GCMs Over the CONUS for Downscaling Studies M. Ashfaq et al. 10.1029/2022JD036659
127. Weighted multi-model ensemble projection of extreme precipitation in the Mediterranean region using statistical downscaling L. Keupp et al. 10.1007/s00704-019-02851-7
128. A Proposal to Evaluate Drought Characteristics Using Multiple Climate Models for Multiple Timescales N. Tien Thanh 10.3390/cli6040079
129. Bayesian weighting of climate models based on climate sensitivity E. Massoud et al. 10.1038/s43247-023-01009-8