184 citations as recorded by crossref.

1. Reducing uncertainty in local temperature projections S. Qasmi & A. Ribes 10.1126/sciadv.abo6872
2. The effectiveness of machine learning‐based multi‐model ensemble predictions of CMIP6 in Western Ghats of India S. Shetty et al. 10.1002/joc.8131
3. Impact of multi-scenario land-use changes on habitat quality evolution in the Yangtze River economic belt B. Dong et al. 10.3389/fenvs.2024.1516703
4. Future changes of socioeconomic exposure to potential landslide hazards over mainland China D. Li et al. 10.1016/j.wace.2024.100731
5. Evaluation of global teleconnections in CMIP6 climate projections using complex networks C. Dalelane et al. 10.5194/esd-14-17-2023
6. Climate-aware decision-making: lessons for electric grid infrastructure planning and operations A. Brockway et al. 10.1088/1748-9326/ac7815
7. Expert judgment in climate science: How it is used and how it can be justified M. Majszak & J. Jebeile 10.1016/j.shpsa.2023.05.005
8. Assessing the impact of global warming on windstorms in the northeastern United States using the pseudo-global-warming method J. Sethunadh et al. 10.1007/s11069-023-05968-1
9. Change of global land extreme temperature in the future X. Zhang et al. 10.1016/j.gloplacha.2024.104583
10. Constraining uncertainty in projected precipitation over land with causal discovery K. Debeire et al. 10.5194/esd-16-607-2025
11. 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
12. Common Error Patterns in the Regional Atmospheric Circulation Simulated by the CMIP Multi‐Model Ensemble S. Brands 10.1029/2022GL101446
13. The Mediterranean climate change hotspot in the CMIP5 and CMIP6 projections J. Cos et al. 10.5194/esd-13-321-2022
14. Sahel Rainfall Projections Constrained by Past Sensitivity to Global Warming J. Schewe & A. Levermann 10.1029/2022GL098286
15. Comparing CMIP6 Climate Model Simulations of Annual Global Mean Temperatures to a New Combined Data Product P. Craigmile & P. Guttorp 10.1029/2022EA002468
16. Development of a new hybrid ensemble method for accurate characterization of future drought using multiple global climate models M. Yousaf et al. 10.1007/s00477-023-02526-w
17. Indian Ocean dynamic sea level, its variability and projections in CMIP6 models C. Sajidh & A. Chatterjee 10.1007/s00382-023-06676-z
18. Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework P. Nguyen et al. 10.5194/gmd-17-7285-2024
19. 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
20. Indian summer monsoon simulations in successive generations of the NCAR Community Atmosphere Model R. Kumar et al. 10.1007/s00704-023-04514-0
21. Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on CMIP6‐GCMs K. Lu et al. 10.1002/joc.7673
22. CMIP6 Earth System Models Project Greater Acceleration of Climate Zone Change Due To Stronger Warming Rates A. Bayar et al. 10.1029/2022EF002972
23. Accounting for Pacific climate variability increases projected global warming Y. Liang et al. 10.1038/s41558-024-02017-y
24. Emergent Constraints on the Large-Scale Atmospheric Circulation and Regional Hydroclimate: Do They Still Work in CMIP6 and How Much Can They Actually Constrain the Future? I. Simpson et al. 10.1175/JCLI-D-21-0055.1
25. Application-specific optimal model weighting of global climate models: A red tide example A. Elshall et al. 10.1016/j.cliser.2022.100334
26. Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6 C. Tebaldi et al. 10.5194/esd-12-253-2021
27. Projected changes in mean annual cycle of temperature and precipitation over the Czech Republic: Comparison of CMIP5 and CMIP6 E. Holtanová et al. 10.3389/feart.2022.1018661
28. Probabilistic projections of El Niño Southern Oscillation properties accounting for model dependence and skill R. Olson et al. 10.1038/s41598-022-26513-3
29. Validation and Selection of a Representative Subset from the Ensemble of EURO-CORDEX EUR11 Regional Climate Model Outputs for the Czech Republic J. Meitner et al. 10.3390/atmos14091442
30. Differential Credibility of Climate Modes in CMIP6 J. Coburn & S. Pryor 10.1175/JCLI-D-21-0359.1
31. Climate Model Projections for Canada: A Comparison of CMIP5 and CMIP6 S. Sobie et al. 10.1080/07055900.2021.2011103
32. Temperature Sensitivity of Freshwater Denitrification and N2O Emission—A Meta‐Analysis M. Velthuis & A. Veraart 10.1029/2022GB007339
33. Improvement in the skill of CMIP6 decadal hindcasts for extreme rainfall events over the Indian summer monsoon region G. Konda et al. 10.1038/s41598-023-48268-1
34. Spatial Modeling and Future Projection of Extreme Precipitation Extents P. Zhong et al. 10.1080/01621459.2024.2408045
35. Fighting climate change: soil bacteria communities and topography play a role in plant colonization of desert areas X. Sun et al. 10.1111/1462-2920.15799
36. The role of crop simulation modeling in assessing potential climate change impacts D. Timlin et al. 10.1002/agg2.20453
37. Australian climate warming: observed change from 1850 and global temperature targets M. Grose et al. 10.1071/ES22018
38. Projections of fire emissions and the consequent impacts on air quality under 1.5 °C and 2 °C global warming C. Tian et al. 10.1016/j.envpol.2023.121311
39. Assessing Climate Change Effects on Winter Wheat Production in the 3H Plain: Insights from Bias-Corrected CMIP6 Projections Y. Xu et al. 10.3390/agriculture14030469
40. Selecting CMIP6 models to assess the impact of climate change on energy need for heating and cooling in Europe H. Filahi et al. 10.1007/s00704-024-05263-4
41. Performance-based sub-selection of CMIP6 models for impact assessments in Europe T. Palmer et al. 10.5194/esd-14-457-2023
42. Plant Phenomics: The Force Behind Tomorrow’s Crop Phenotyping Tools P. Kumari et al. 10.1007/s00344-024-11450-4
43. Dispersal abilities favor commensalism in animal-plant interactions under climate change P. Lemes et al. 10.1016/j.scitotenv.2022.155157
44. An updated assessment of past and future warming over France based on a regional observational constraint A. Ribes et al. 10.5194/esd-13-1397-2022
45. Bayesian estimates for changes of the Russian river runoff in the 21st century as based on the CMIP6 model ensemble simulations А. Medvedev et al. 10.31857/S0002351524020021
46. Selecting and weighting dynamical models using data-driven approaches P. Le Bras et al. 10.5194/npg-31-303-2024
47. Evolution of land surface feedbacks on extreme heat: Adapting existing coupling metrics to a changing climate P. Dirmeyer et al. 10.3389/fenvs.2022.949250
48. Screening CMIP6 models for Chile based on past performance and code genealogy F. Gateño et al. 10.1007/s10584-024-03742-1
49. The potential for structural errors in emergent constraints B. Sanderson et al. 10.5194/esd-12-899-2021
50. Evaluation of CMIP6 models toward dynamical downscaling over 14 CORDEX domains M. Zhang et al. 10.1007/s00382-022-06355-5
51. Drivers of Recent North Pacific Decadal Variability: The Role of Aerosol Forcing A. Dittus et al. 10.1029/2021EF002249
52. Correlation Between Sea‐Level Rise and Aspects of Future Tropical Cyclone Activity in CMIP6 Models J. Lockwood et al. 10.1029/2021EF002462
53. Concerning prognostic estimations on hazardous weather events: a road to nowhere or to home? Y. Kolokolov & A. Monovskaya 10.1088/1755-1315/1070/1/012019
54. Pantropical Indo-Atlantic temperature gradient modulates multi-decadal AMOC variability in models and observations B. Ferster et al. 10.1038/s41612-023-00489-x
55. Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence J. Zhao et al. 10.1007/s00376-023-2393-2
56. Dominant inflation of the Arctic Ocean’s Beaufort Gyre in a warming climate Q. Wang et al. 10.1038/s43247-025-02028-3
57. Surface air temperature variability over India in CMIP6 models during spring and early summer: after effect of El Niño S. Velivelli et al. 10.1007/s00382-025-07654-3
58. Model spread and progress in climate modelling J. Jebeile & A. Barberousse 10.1007/s13194-021-00387-0
59. Dynamic Response of Surface Water Temperature in Urban Lakes under Different Climate Scenarios—A Case Study in Dianchi Lake, China H. Duan et al. 10.3390/ijerph191912142
60. Scenarios of change in the realized climatic niche of mountain carnivores and ungulates C. Dragonetti et al. 10.1111/cobi.14035
61. Reducing Snow Amount Uncertainty in CMIP6 PanCanadian Climate Projections D. Matte et al. 10.1080/07055900.2025.2478835
62. How well have CMIP3, CMIP5 and CMIP6 future climate projections portrayed the recently observed warming D. Carvalho et al. 10.1038/s41598-022-16264-6
63. Climate response to off-equatorial stratospheric sulfur injections in three Earth system models – Part 1: Experimental protocols and surface changes D. Visioni et al. 10.5194/acp-23-663-2023
64. Observation-based selection of climate models projects Arctic ice-free summers around 2035 D. Docquier & T. Koenigk 10.1038/s43247-021-00214-7
65. 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
66. Learning from weather and climate science to prepare for a future pandemic S. Schemm et al. 10.1073/pnas.2209091120
67. Machine learning to optimize climate projection over China with multi-model ensemble simulations T. Li et al. 10.1088/1748-9326/ac1d0c
68. Opposite effects of climate and land‐use/cover change on Mediterranean herpetofauna: Insights from the southern Apennines D. Biancolini et al. 10.1111/acv.12999
69. Identifying climate models based on their daily output using machine learning L. Brunner & S. Sippel 10.1017/eds.2023.23
70. network-based constraint to evaluate climate sensitivity L. Ricard et al. 10.1038/s41467-024-50813-z
71. Projected Changes and Uncertainty of Cold Surges Over Northern China Using the Cmip6 Weighted Multi-Model Ensemble S. Song & X. Yan 10.2139/ssrn.4074639
72. Evaluating regional climate change during 2021–2080 for Iran and neighboring countries (a comparative analysis of projections and reanalysis data) H. Dehban et al. 10.1007/s00704-025-05381-7
73. Temperature and Precipitation Change over South China in CMIP5 and CMIP6 Models: Historical Simulation and Future Projection D. Peng et al. 10.1007/s00376-024-4375-4
74. Future temperature and salinity in Puget Sound, Washington State, under CMIP6 climate change scenarios S. Walker et al. 10.2166/wcc.2022.282
75. Assessing observational constraints on future European climate in an out-of-sample framework C. O’Reilly et al. 10.1038/s41612-024-00648-8
76. A CMIP6-based multi-model downscaling ensemble to underpin climate change services in Australia M. Grose et al. 10.1016/j.cliser.2023.100368
77. A non-stationary climate-informed weather generator for assessing future flood risks V. Nguyen et al. 10.5194/ascmo-10-195-2024
78. Why we need lower-performance climate models R. O’Loughlin 10.1007/s10584-023-03661-7
79. Bayesian Estimates of Changes in Russian River Runoff in the 21st Century Based on the CMIP6 Ensemble Model Simulations A. Medvedev et al. 10.1134/S000143382470018X
80. Optimizing climate model selection in regional studies using an adaptive weather type based framework: a case study for extreme heat in Belgium F. Serras et al. 10.1007/s00382-024-07432-7
81. Dynamical downscaling CMIP6 models over New Zealand: added value of climatology and extremes P. Gibson et al. 10.1007/s00382-024-07337-5
82. Uncertainties in projections of climate extremes indices in South America via Bayesian inference C. Gouveia et al. 10.1002/joc.7650
83. The Impact of Climate Change and Carbon Policy on Company Earnings M. Goldklang et al. 10.2139/ssrn.4477683
84. A global climate model ensemble for downscaled monthly climate normals over North America C. Mahony et al. 10.1002/joc.7566
85. Vulnerability to climate change of cultivated and wild cacao in Ecuador V. Ceccarelli et al. 10.1007/s10584-024-03756-9
86. Global warming increases risk from compound dry‐hot events to human and agricultural systems Y. Zhang et al. 10.1002/joc.8229
87. Cloud properties and their projected changes in CMIP models with low to high climate sensitivity L. Bock & A. Lauer 10.5194/acp-24-1587-2024
88. Representing natural climate variability in an event attribution context: Indo-Pakistani heatwave of 2022 S. Nath et al. 10.1016/j.wace.2024.100671
89. Projecting Global Mean Sea‐Level Change Using CMIP6 Models T. Hermans et al. 10.1029/2020GL092064
90. Validation of key Arctic energy and water budget components in CMIP6 S. Winkelbauer et al. 10.1007/s00382-024-07105-5
91. Present-day North Atlantic salinity constrains future warming of the Northern Hemisphere I. Park et al. 10.1038/s41558-023-01728-y
92. Projection of temperature and precipitation under climate change in Tabriz, Iran B. Ghazi & E. Jeihouni 10.1007/s12517-022-09848-z
93. Bayesian weighting of climate models based on climate sensitivity E. Massoud et al. 10.1038/s43247-023-01009-8
94. A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs) M. Meinshausen et al. 10.5194/gmd-17-4533-2024
95. Projected changes and uncertainty in cold surges over northern China using the CMIP6 weighted multi-model ensemble S. Shuaifeng & Y. Xiaodong 10.1016/j.atmosres.2022.106334
96. Climate Change Signal in Atlantic Tropical Cyclones Today and Near Future C. Lee et al. 10.1029/2023EF003539
97. Probabilistic projections of future warming and climate sensitivity trajectories P. Goodwin 10.1093/oxfclm/kgab007
98. Using large ensembles of climate change mitigation scenarios for robust insights C. Guivarch et al. 10.1038/s41558-022-01349-x
99. FaIRv2.0.0: a generalized impulse response model for climate uncertainty and future scenario exploration N. Leach et al. 10.5194/gmd-14-3007-2021
100. Combination of Decadal Predictions and Climate Projections in Time: Challenges and Potential Solutions D. Befort et al. 10.1029/2022GL098568
101. Increasing Fire Weather Potential Over Northeast China Linked to Declining Bering Sea Ice G. Liu et al. 10.1029/2023GL105931
102. On the role of moist and dry processes in atmospheric blocking biases in the Euro-Atlantic region in CMIP6 E. Dolores-Tesillos et al. 10.5194/wcd-6-471-2025
103. Future Projections and Uncertainty Assessment of Precipitation Extremes in the Korean Peninsula from the CMIP6 Ensemble with a Statistical Framework Y. Shin et al. 10.3390/atmos12010097
104. Effects of Climate Change on Streamflow in the Ayazma River Basin in the Marmara Region of Turkey K. Seddiqe et al. 10.3390/w15040763
105. Biogeochemical and Physical Assessment of CMIP5 and CMIP6 Ocean Components for the Southwest Pacific Ocean G. Rickard et al. 10.1029/2022JG007123
106. Filtering CMIP6 models in the Euro-Mediterranean based on a circulation patterns approach M. Olmo et al. 10.1016/j.wace.2025.100765
107. Large spread in the representation of compound long-duration dry and hot spells over Europe in CMIP5 C. Manning et al. 10.5194/wcd-4-309-2023
108. How fast is the frequency of precipitation extremes doubling in global land regions? G. Chagnaud et al. 10.1088/2515-7620/ad9f12
109. Assessing CMIP6 uncertainties at global warming levels G. Evin et al. 10.1007/s00382-024-07323-x
110. The need for carbon-emissions-driven climate projections in CMIP7 B. Sanderson et al. 10.5194/gmd-17-8141-2024
111. Future precipitation extremes over base Himalayan Uttarakhand region: analysis using the statistically downscaled, bias-corrected high-resolution NEX-GDDP datasets B. Vinodhkumar et al. 10.1007/s00704-022-04111-7
112. Constraining CMIP6 Projections of an Ice‐Free Arctic Using a Weighting Scheme J. Zhao et al. 10.1029/2022EF002708
113. Scenario choice impacts carbon allocation projection at global warming levels L. de Mora et al. 10.5194/esd-14-1295-2023
114. A simple framework for likely climate projections applied to tropical width D. Baldassare & T. Reichler 10.1007/s00382-024-07335-7
115. An Assessment of the Oceanic Physical and Biogeochemical Components of CMIP5 and CMIP6 Models for the Ross Sea Region G. Rickard et al. 10.1029/2022JC018880
116. Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates K. Chang et al. 10.1111/gcb.16755
117. Future sea-level projections with a coupled atmosphere-ocean-ice-sheet model J. Park et al. 10.1038/s41467-023-36051-9
118. Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case Study V. Shevchenko et al. 10.1109/ACCESS.2024.3358865
119. Using Neural Networks to Predict Hurricane Storm Surge and to Assess the Sensitivity of Surge to Storm Characteristics J. Lockwood et al. 10.1029/2022JD037617
120. Comparison of CMIP6 and CMIP5 models in simulating mean and extreme precipitation over East Africa B. Ayugi et al. 10.1002/joc.7207
121. Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over Australia S. Chapman et al. 10.1029/2023EF003548
122. Eddy activity in the Arctic Ocean projected to surge in a warming world X. Li et al. 10.1038/s41558-023-01908-w
123. Changes of extreme precipitation in the Philippines, projected from the CMIP6 multi-model ensemble J. Hong et al. 10.1016/j.wace.2022.100480
124. Use of meta-heuristic approach in the estimation of aquifer's response to climate change under shared socioeconomic pathways N. Zeydalinejad & R. Dehghani 10.1016/j.gsd.2022.100882
125. A chance to “cure” local climate systems and reconcile humanity with Nature Y. Kolokolov & A. Monovskaya 10.1088/1755-1315/1045/1/012154
126. Substantial changes in the probability of future annual temperature extremes R. Slater et al. 10.1002/asl.1061
127. Confronting Earth System Model trends with observations I. Simpson et al. 10.1126/sciadv.adt8035
128. 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
129. Opinion: Why all emergent constraints are wrong but some are useful – a machine learning perspective P. Nowack & D. Watson-Parris 10.5194/acp-25-2365-2025
130. Microplastics in global rivers: Sustainable practices Y. Guo et al. 10.1002/sd.3279
131. Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6 D. Lafferty & R. Sriver 10.1038/s41612-023-00486-0
132. Description of historical and future projection simulations by the global coupled E3SMv1.0 model as used in CMIP6 X. Zheng et al. 10.5194/gmd-15-3941-2022
133. Future Extreme Precipitation in Summer Will Become More Widespread in China Depending on Level of Warming R. Yu et al. 10.1029/2022EF003413
134. Evolution of the Internal Climate Modes under Future Warming J. Coburn & S. Pryor 10.1175/JCLI-D-22-0200.1
135. A Comparison of Regional Climate Projections With a Range of Climate Sensitivities C. Barnes et al. 10.1029/2023JD038917
136. Running to warmer-drier springs in the Greater Mekong Subregion as climate warms Z. Dong et al. 10.1016/j.atmosres.2024.107606
137. Imminent loss of climate space for permafrost peatlands in Europe and Western Siberia R. Fewster et al. 10.1038/s41558-022-01296-7
138. Simulations With the Marine Biogeochemistry Library (MARBL) M. Long et al. 10.1029/2021MS002647
139. Contribution of large-scale atmospheric circulation and anthropogenic aerosols to recent summer warming over western Europe H. Douville et al. 10.1007/s00382-025-07689-6
140. Historical footprints and future projections of global dust burden from bias-corrected CMIP6 models J. Liu et al. 10.1038/s41612-023-00550-9
141. Comparison of Climate Model Large Ensembles With Observations in the Arctic Using Simple Neural Networks Z. Labe & E. Barnes 10.1029/2022EA002348
142. Linking hydroclimate indices to projected warming temperature and increased precipitation under CMIP6 for a sub-arctic basin C. Nakigudde et al. 10.1016/j.ejrh.2024.102059
143. Assessment and Constraint of Mesozooplankton in CMIP6 Earth System Models C. Petrik et al. 10.1029/2022GB007367
144. Effects of multi-observations uncertainty and models similarity on climate change projections R. Pathak et al. 10.1038/s41612-023-00473-5
145. Future Projections and Uncertainty Assessment of Precipitation Extremes in Iran from the CMIP6 Ensemble J. Hong et al. 10.3390/atmos12081052
146. Projections of changes in ecosystem productivity under 1.5 °C and 2 °C global warming C. Tian et al. 10.1016/j.gloplacha.2021.103588
147. Estimating Regionalized Hydrological Impacts of Climate Change Over Europe by Performance-Based Weighting of CORDEX Projections F. Sperna Weiland et al. 10.3389/frwa.2021.713537
148. Evaluation of atmospheric circulations for dynamic downscaling in CMIP6 models over East Asia S. Song et al. 10.1007/s00382-022-06465-0
149. Change in Precipitation over the Tibetan Plateau Projected by Weighted CMIP6 Models Y. Zhao et al. 10.1007/s00376-022-1401-2
150. Natural variability is a large source of uncertainty in future projections of hypoxia in the Baltic Sea H. Markus Meier et al. 10.1038/s43247-021-00115-9
151. RECCAP2 Future Component: Consistency and Potential for Regional Assessment to Constrain Global Projections C. Jones et al. 10.1029/2023AV001024
152. Climate change may reduce suitable habitat for freshwater fish in a tropical watershed L. Peluso et al. 10.1007/s10584-023-03526-z
153. Rarest rainfall events will see the greatest relative increase in magnitude under future climate change G. Gründemann et al. 10.1038/s43247-022-00558-8
154. Assessing high-resolution precipitation extremes in Central Asia: evaluation and future projections S. Gummadi et al. 10.1007/s10584-025-03872-0
155. Impacts of marine heatwaves on tropical western and central Pacific Island nations and their communities N. Holbrook et al. 10.1016/j.gloplacha.2021.103680
156. 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
157. New Potential to Reduce Uncertainty in Regional Climate Projections by Combining Physical and Socio‐Economic Constraints F. Lehner et al. 10.1029/2023AV000887
158. The ExtremeX global climate model experiment: investigating thermodynamic and dynamic processes contributing to weather and climate extremes K. Wehrli et al. 10.5194/esd-13-1167-2022
159. Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections Z. Nicholls et al. 10.1029/2020EF001900
160. Temporal fragmentation of the energy demand in Europe: Impact of climate change on the maneuverability of energy system H. Filahi et al. 10.1016/j.cliser.2024.100469
161. Sign of Observed California Temperature Trends Depends on Data Set Homogenization: Implications for Weighting and Downscaling A. Charn et al. 10.1029/2022GL099186
162. Sustainable food systems and nutrition in the 21st century: a report from the 22nd annual Harvard Nutrition Obesity Symposium J. Fanzo et al. 10.1093/ajcn/nqab315
163. MESMER-M: an Earth system model emulator for spatially resolved monthly temperature S. Nath et al. 10.5194/esd-13-851-2022
164. Future Changes in Various Cold Surges over China in CMIP6 Projections L. Ma et al. 10.1007/s00376-023-3220-5
165. Assessment of Equilibrium Climate Sensitivity of the Community Earth System Model Version 2 Through Simulation of the Last Glacial Maximum J. Zhu et al. 10.1029/2020GL091220
166. Extreme climate changes over three major river basins in China as seen in CMIP5 and CMIP6 X. Zhu et al. 10.1007/s00382-021-05767-z
167. Predicting daily maximum temperature over Andhra Pradesh using machine learning techniques S. Velivelli et al. 10.1007/s00704-024-05146-8
168. Evaluating the phase evolution of CMIP GCMs for agricultural climate-change impact assessments in China L. Yao et al. 10.1016/j.agrformet.2024.110282
169. A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes S. Brands 10.5194/gmd-15-1375-2022
170. Dynamic simulation of land use change and habitat quality assessment under climate change scenarios in Nanchang, China Z. Chen et al. 10.1007/s11356-023-31304-y
171. Revealing the Impact of Global Heating on North Atlantic Circulation Using Transparent Machine Learning M. Sonnewald & R. Lguensat 10.1029/2021MS002496
172. From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: coupling of MAGICC (v7.5.1) and MESMER (v0.8.3) L. Beusch et al. 10.5194/gmd-15-2085-2022
173. Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis F. Lema et al. 10.5194/hess-29-1981-2025
174. Tropical and subtropical Asia's valued tree species under threat H. Gaisberger et al. 10.1111/cobi.13873
175. Future climate change implications in Bhutan from a downscaled and bias‐adjusted CMIP6 multimodel ensemble F. Lehner et al. 10.1002/joc.8623
176. Pitfalls in diagnosing temperature extremes L. Brunner & A. Voigt 10.1038/s41467-024-46349-x
177. Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6 F. Lehner et al. 10.5194/esd-11-491-2020
178. Observationally constrained projection of Afro-Asian monsoon precipitation Z. Chen et al. 10.1038/s41467-022-30106-z
179. Pacific variability reconciles observed and modelled global mean temperature increase since 1950 M. Stolpe et al. 10.1007/s00382-020-05493-y
180. Implications of exceeding the Paris Agreement for mammalian biodiversity V. Mendez Angarita et al. 10.1111/csp2.12889
181. Evaluation of CMIP6 GCMs Over the CONUS for Downscaling Studies M. Ashfaq et al. 10.1029/2022JD036659
182. Showcasing MESMER‐X: Spatially Resolved Emulation of Annual Maximum Temperatures of Earth System Models Y. Quilcaille et al. 10.1029/2022GL099012
183. Emergent Constrained Projections of Mean and Extreme Warming in China Z. Chen et al. 10.1029/2022GL102124
184. Toward Consistent Observational Constraints in Climate Predictions and Projections G. Hegerl et al. 10.3389/fclim.2021.678109