143 citations as recorded by crossref.

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2. Comparison of ocean deoxygenation between CMIP models and an observational dataset in the North Pacific from 1958 to 2005 Y. Abe & S. Minobe https://doi.org/10.3389/fmars.2023.1161451
3. Attribution of the 2024 record-breaking precipitation event in Southern Denmark to human-induced climate change M. Newell et al. https://doi.org/10.1016/j.wace.2025.100848
4. Continental United States climate projections based on thermodynamic modification of historical weather A. Jones et al. https://doi.org/10.1038/s41597-023-02485-5
5. Increasing connections of the leading internal mode of the summertime Northwest Pacific subtropical anticyclone with preceding ENSO under greenhouse warming in FGOALS‐g3 super‐large ensemble J. Ma et al. https://doi.org/10.1002/joc.8197
6. Interpretable polynomial neural ordinary differential equations C. Fronk & L. Petzold https://doi.org/10.1063/5.0130803
7. Constructing extreme heatwave storylines with differentiable climate models T. Whittaker & A. Di Luca https://doi.org/10.5194/wcd-7-393-2026
8. Connecting climate science and society: reflections from early and mid-career researchers at the World Climate Research Programme Open Science Conference 2023 L. Díaz et al. https://doi.org/10.3389/fclim.2024.1501216
9. Influence of age, soil volume, and climate change on water availability at urban tree sites L. Rosenberger et al. https://doi.org/10.1016/j.scs.2024.105680
10. Variability in flood frequency in sub-Saharan Africa: The role of large-scale climate modes of variability and their future impacts J. Ekolu et al. https://doi.org/10.1016/j.jhydrol.2024.131679
11. Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature S. Schöngart et al. https://doi.org/10.5194/gmd-17-8283-2024
12. European compound flood-heat-flood events associated with Omega patterns cannot be easily reproduced by a fully coupled model Y. Guo et al. https://doi.org/10.1038/s43247-025-02481-0
13. Effects of forcing differences and initial conditions on inter-model agreement in the VolMIP volc-pinatubo-full experiment D. Zanchettin et al. https://doi.org/10.5194/gmd-15-2265-2022
14. Overview of the advances in understanding chaos in low-dimensional dynamical systems subjected to parameter drift D. Jánosi & T. Tél https://doi.org/10.1016/j.physrep.2024.09.003
15. Impacts of Climate Change on Tropical Cyclones and associated Rainfall over South Korea: Storyline and Risk-based approaches Y. Hiraga et al. https://doi.org/10.1016/j.atmosres.2025.108685
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17. Opinion: The importance and future development of perturbed parameter ensembles in climate and atmospheric science K. Carslaw et al. https://doi.org/10.5194/acp-26-4651-2026
18. The Unprecedented Late-Summer 2023 Heatwave in Southeastern South America: Attribution and future projection of similar events W. Kim et al. https://doi.org/10.1016/j.wace.2025.100772
19. Large ensemble simulations indicate increases in spatial compounding of droughts and hot extremes across multiple croplands in China B. Lv et al. https://doi.org/10.1016/j.gloplacha.2024.104670
20. Unsupervised detection of large-scale weather patterns in the northern hemisphere via Markov State Modelling: from blockings to teleconnections S. Springer et al. https://doi.org/10.1038/s41612-024-00659-5
21. Precipitation variability in CMIP6 climate models across the North Atlantic–European region and their Links to Atmospheric Circulation E. Plavcová et al. https://doi.org/10.1007/s00382-024-07556-w
22. Quantifying the contribution of forcing and three prominent modes of variability to historical climate A. Schurer et al. https://doi.org/10.5194/cp-19-943-2023
23. Predicting Slowdowns in Decadal Climate Warming Trends With Explainable Neural Networks Z. Labe & E. Barnes https://doi.org/10.1029/2022GL098173
24. An overview of the E3SM version 2 large ensemble and comparison to other E3SM and CESM large ensembles J. Fasullo et al. https://doi.org/10.5194/esd-15-367-2024
25. Theoretical tools for understanding the climate crisis from Hasselmann’s programme and beyond V. Lucarini & M. Chekroun https://doi.org/10.1038/s42254-023-00650-8
26. Assessing Outcomes in Stratospheric Aerosol Injection Scenarios Shortly After Deployment D. Hueholt et al. https://doi.org/10.1029/2023EF003488
27. A deep learning based classification of atmospheric circulation types over Europe: projection of future changes in a CMIP6 large ensemble M. Mittermeier et al. https://doi.org/10.1088/1748-9326/ac8068
28. A 100-member ensemble simulations of global historical (1951–2010) wave heights M. Casas-Prat et al. https://doi.org/10.1038/s41597-023-02058-6
29. Adapting analogue forecasting to compare ENSO remote influences across different models and regions J. Jeffree et al. https://doi.org/10.1007/s00382-026-08258-1
30. Reliability of simulating internal precipitation variability over multi‐timescales using multiple global climate model large ensembles in China J. Liu et al. https://doi.org/10.1002/joc.8210
31. Observation-Constrained Intercomparison of CMIP6 GCMs Precipitation Projections around Japan D. Kim & N. Shirakawa https://doi.org/10.1007/s13143-025-00423-6
32. Extreme Precipitation and Flood Estimation Using Large Ensemble Climate Model Outputs: A Review T. Tanaka et al. https://doi.org/10.1061/JHYEFF.HEENG-6665
33. Disentangling the contributions of anthropogenic climate change, greenhouse gases, and aerosols to heat-related mortality in Great Britain: a climate change impact attribution study K. Wan et al. https://doi.org/10.1016/S2542-5196(25)00050-6
34. How to stop being surprised by unprecedented weather T. Kelder et al. https://doi.org/10.1038/s41467-025-57450-0
35. Are Simulated Ocean Deoxygenation Rates Consistent with the Observational Reconstructions? T. Ito et al. https://doi.org/10.1146/annurev-earth-032524-123111
36. Advances in aggregation methods for multi-model ensembles in climate science: A comprehensive review M. Shiru et al. https://doi.org/10.1016/j.pce.2026.104391
37. Global record-shattering breadbasket droughts emerge from moderately extreme regional events J. Li et al. https://doi.org/10.1038/s41467-026-70700-z
38. A substantial reduction of total and group-specific population risk to compound heat and drought events in China through achieving carbon neutrality J. Chen et al. https://doi.org/10.1016/j.jclepro.2025.144694
39. Latent Diffusion and Spatiotemporal Transformers Generate Large Ensemble Climate Simulations J. Meuer et al. https://doi.org/10.1109/TAI.2025.3621121
40. On the Reliability of Estimated Return Periods for Climate Extremes E. Ragno & A. AghaKouchak https://doi.org/10.1007/s13753-026-00764-4
41. The updated Multi-Model Large Ensemble Archive and the Climate Variability Diagnostics Package: new tools for the study of climate variability and change N. Maher et al. https://doi.org/10.5194/gmd-18-6341-2025
42. Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6 D. Lafferty & R. Sriver https://doi.org/10.1038/s41612-023-00486-0
43. Reduction of the uncertainty of flood projection under a future climate by focusing on similarities among multiple SSP-RCP scenarios Y. Kimura et al. https://doi.org/10.1038/s41598-025-16327-4
44. Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI): protocol and initial results from the first simulations J. Richter et al. https://doi.org/10.5194/gmd-15-8221-2022
45. Diffusion model-based probabilistic downscaling for 180-year East Asian climate reconstruction F. Ling et al. https://doi.org/10.1038/s41612-024-00679-1
46. Attributing heavy rainfall event in Berchtesgadener Land to recent climate change – Further rainfall intensification projected for the future B. Poschlod https://doi.org/10.1016/j.wace.2022.100492
47. Bringing it all together: science priorities for improved understanding of Earth system change and to support international climate policy C. Jones et al. https://doi.org/10.5194/esd-15-1319-2024
48. Is reliable climate change information ‘predictably uncertain’? M. Ackermann https://doi.org/10.1007/s13194-026-00757-6
49. Tropical cyclone-induced coastal sea level projection and the adaptation to a changing climate N. Mori & T. Shimura https://doi.org/10.1017/cft.2022.6
50. Threat posed by rising lake levels on the Tibetan Plateau: take Qinghai Lake for example H. Yu et al. https://doi.org/10.1016/j.ecolind.2025.113716
51. Multi-year droughts in CMIP6 large ensemble models J. van Mourik et al. https://doi.org/10.1088/2515-7620/ae6d87
52. Developing Guidelines for working with Multi-Model Ensembles in CMIP A. Katzenberger et al. https://doi.org/10.5194/esd-17-495-2026
53. Increasing risk of 2022-like droughts in Europe under climate change: evidence from Large Ensembles using flow analogs B. Bulut et al. https://doi.org/10.1007/s10584-026-04235-z
54. Frequent land-ocean transboundary migration of tropical heatwaves under climate change X. Gu et al. https://doi.org/10.1038/s41467-025-58586-9
55. Climate change projections of probable maximum precipitation over large areas through depth-area-duration analysis: A case study in Brazil J. Brêda et al. https://doi.org/10.1016/j.jhydrol.2026.136296
56. Attributing the recent weakening of the South Asian subtropical westerlies P. Upadhyaya et al. https://doi.org/10.1038/s41612-024-00777-0
57. Improving statistical projections of ocean dynamic sea-level change using pattern recognition techniques V. Malagón-Santos et al. https://doi.org/10.5194/os-19-499-2023
58. Can limiting global temperature rise to below 2°C warming prevent the emergence of unprecedented drought? Y. Ji et al. https://doi.org/10.1016/j.agrformet.2024.110047
59. Contrasting changes in hydrological processes of the Volta River basin under global warming M. Dembélé et al. https://doi.org/10.5194/hess-26-1481-2022
60. Uncertainty Analysis in Multi‐Sector Systems: Considerations for Risk Analysis, Projection, and Planning for Complex Systems V. Srikrishnan et al. https://doi.org/10.1029/2021EF002644
61. Detection of Forced Change Within Combined Climate Fields Using Explainable Neural Networks J. Rader et al. https://doi.org/10.1029/2021MS002941
62. Exploring the role of building codes in protecting occupants from overheating—A Canadian perspective C. Siu et al. https://doi.org/10.1016/j.enbuild.2025.115673
63. Observation-inferred resilience loss of the Amazon rainforest possibly due to internal climate variability R. Grodofzig et al. https://doi.org/10.5194/esd-15-913-2024
64. West Antarctic Surface Climate Changes Since the Mid‐20th Century Driven by Anthropogenic Forcing Q. Dalaiden et al. https://doi.org/10.1029/2022GL099543
65. Disentangling Internal Variability and Forced Response in Global Land Monsoon Projection Uncertainty: Insights from Multi-Model Large Ensembles L. Wang et al. https://doi.org/10.1007/s00376-025-5151-9
66. Storm surges and extreme sea levels: Review, establishment of model intercomparison and coordination of surge climate projection efforts (SurgeMIP). N. Bernier et al. https://doi.org/10.1016/j.wace.2024.100689
67. Swiss glacier mass loss during the 2022 drought: persistent streamflow contributions amid declining melt water volumes M. van Tiel et al. https://doi.org/10.5194/hess-30-23-2026
68. The birth of a field through a marriage of scales: urban meteorological modeling meets regional climate modeling M. Georgescu https://doi.org/10.1088/1748-9326/ae8285
69. Simulation of hydropower at subcontinental to global scales: a state-of-the-art review S. Turner & N. Voisin https://doi.org/10.1088/1748-9326/ac4e38
70. Comparison of Climate Model Large Ensembles With Observations in the Arctic Using Simple Neural Networks Z. Labe & E. Barnes https://doi.org/10.1029/2022EA002348
71. Model spread in multidecadal North Atlantic Oscillation variability connected to stratosphere–troposphere coupling R. Bonnet et al. https://doi.org/10.5194/wcd-5-913-2024
72. Multi criteria evaluation of downscaled CMIP6 models in predicting precipitation extremes R. Gupta et al. https://doi.org/10.1016/j.atmosres.2025.107921
73. Global assessment of historical changes in extreme fire weather: Insight from CMIP6 ensembles and implications for probabilistic attribution to global warming Z. Liu et al. https://doi.org/10.1016/j.gloplacha.2025.104822
74. Confronting Earth System Model trends with observations I. Simpson et al. https://doi.org/10.1126/sciadv.adt8035
75. ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009) R. Hand et al. https://doi.org/10.5194/gmd-16-4853-2023
76. Reconstructing and Projecting 2012-like Drought in Serbia Using the Max Planck Institute Grand Ensemble M. Tošić et al. https://doi.org/10.3390/atmos16060668
77. Rising risks of hydroclimatic swings: A large ensemble study of dry and wet spell transitions in North America W. Na & M. Najafi https://doi.org/10.1016/j.gloplacha.2024.104476
78. The SMHI Large Ensemble (SMHI-LENS) with EC-Earth3.3.1 K. Wyser et al. https://doi.org/10.5194/gmd-14-4781-2021
79. Role of the Warm Arctic Cold Eurasian-like pattern on the near future warming rate of East Asian surface temperature S. Oh et al. https://doi.org/10.1088/1748-9326/ad90f6
80. Dependence of strategic solar climate intervention on background scenario and model physics J. Fasullo & J. Richter https://doi.org/10.5194/acp-23-163-2023
81. Demystifying global climate models for use in the life sciences D. Schoeman et al. https://doi.org/10.1016/j.tree.2023.04.005
82. Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events M. Schirmer et al. https://doi.org/10.5194/tc-16-3469-2022
83. Rarest rainfall events will see the greatest relative increase in magnitude under future climate change G. Gründemann et al. https://doi.org/10.1038/s43247-022-00558-8
84. Underestimation of meteorological drought intensity due to lengthening of the drought season with climate change J. Dullaart & K. van der Wiel https://doi.org/10.1088/2752-5295/ad8d01
85. Extreme and compound ocean events are key drivers of projected low pelagic fish biomass N. Le Grix et al. https://doi.org/10.1111/gcb.16968
86. Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications A. Merrifield et al. https://doi.org/10.5194/gmd-16-4715-2023
87. Anthropogenic global warming increases the risk of record-breaking extreme precipitation events in low-income countries L. Nguyen et al. https://doi.org/10.1038/s43247-026-03649-y
88. Severe compound events of low wind and cold temperature for the British power system L. Lücke et al. https://doi.org/10.1002/met.2219
89. Exploring the contribution of low‐frequency internal variability modes to global mean sea surface temperature variability based on large ensembles L. Yang et al. https://doi.org/10.1002/joc.8515
90. The variability fingerprint of a warming world informing climate risk and solutions Y. Wang & C. Turvey https://doi.org/10.1038/s41598-026-54733-4
91. The influence of variability on fire weather conditions in high latitude regions under present and future global warming M. Lund et al. https://doi.org/10.1088/2515-7620/acdfad
92. Changing windstorm characteristics over the US Northeast in a single model large ensemble J. Coburn et al. https://doi.org/10.1088/1748-9326/ad801b
93. Effects of storms on fisheries and aquaculture: An Icelandic case study on climate change adaptation N. Sühring et al. https://doi.org/10.1080/15230430.2023.2269689
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96. Excess water availability in northern mid-high latitudes contiguously migrated from ocean under climate change Y. Guan et al. https://doi.org/10.1126/sciadv.adv0282
97. Applying global warming levels of emergence to highlight the increasing population exposure to temperature and precipitation extremes D. Gampe et al. https://doi.org/10.5194/esd-15-589-2024
98. Climate Change Impacts Pair‐Bond Dynamics in a Long‐Lived Monogamous Species R. Sun et al. https://doi.org/10.1111/ele.14555
99. Subpolar North Atlantic decadal cooling may have aggravated recent Eastern Siberian wildfires Y. Zeng et al. https://doi.org/10.1038/s41467-025-66520-2
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104. Coupled Cellular automata – Snowmelt Runoff Model: A Novel Framework for Assessing Climate Change Impacts on Streamflow J. Hidalgo-Hidalgo et al. https://doi.org/10.1007/s41748-025-00975-7
105. Where are the coexisting parallel climates? Large ensemble climate projections from the point of view of chaos theory M. Herein et al. https://doi.org/10.1063/5.0136719
106. Global climate change below 2 °C avoids large end century increases in burned area in Canada S. Curasi et al. https://doi.org/10.1038/s41612-024-00781-4
107. GARD-LENS: A downscaled large ensemble dataset for understanding future climate and its uncertainties S. Hartke et al. https://doi.org/10.1038/s41597-024-04205-z
108. Chaotic oceanic excitation of low-frequency polar motion variability L. Börger et al. https://doi.org/10.5194/esd-16-75-2025
109. Triangulating habitat suitability for the locally extirpated California grizzly bear A. McInturff et al. https://doi.org/10.1016/j.biocon.2025.110989
110. The Super-large Ensemble Experiments of CAS FGOALS-g3 P. Lin et al. https://doi.org/10.1007/s00376-022-1439-1
111. Assessment of long-term historical trends in winter precipitation in Japan using large-ensemble climate simulations: Changes in the impact of southern coastal cyclones M. Ohba & H. Kawase https://doi.org/10.1007/s00382-024-07213-2
112. Natural Disasters, Principled Humanitarianism, and the Prospects for a New Solidarism in International Solidarity I. Ruacan https://doi.org/10.1177/03043754251319943
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114. Climate change effects on river droughts in Bavaria using a hydrological large ensemble B. Poschlod et al. https://doi.org/10.5194/hess-30-1165-2026
115. The KNMI Large Ensemble Time Slice (KNMI–LENTIS) L. Muntjewerf et al. https://doi.org/10.5194/gmd-16-4581-2023
116. The Arctic has warmed nearly four times faster than the globe since 1979 M. Rantanen et al. https://doi.org/10.1038/s43247-022-00498-3
117. Impact of bias adjustment strategy on ensemble projections of hydrological extremes P. Astagneau et al. https://doi.org/10.5194/hess-29-5695-2025
118. Role of mean and variability change in changes in European annual and seasonal extreme precipitation events R. Wood https://doi.org/10.5194/esd-14-797-2023
119. Future thermal environment in Japan using large ensemble climate dataset d4PDF—Can we hold outdoor activities at global 4 °C warming? K. Nakajima et al. https://doi.org/10.1088/2752-5295/ae583b
120. Drivers of summer extreme temperature trends in Europe: insight from three major heat waves using flow analogues L. Famooss Paolini et al. https://doi.org/10.1007/s00382-026-08171-7
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122. Meteorological drivers of co-occurring renewable energy droughts in Europe B. van Duinen et al. https://doi.org/10.1016/j.rser.2025.115993
123. Increasing central and northern European summer heatwave intensity due to forced changes in internal variability G. Beobide-Arsuaga et al. https://doi.org/10.1038/s41467-025-65392-w
124. Extreme Precipitation and High-Temperature Impacts on Terrestrial Gross Primary Productivity across China, 1981 to 2100 Z. Su et al. https://doi.org/10.34133/ehs.0462
125. Effects of Internal Climate Variability on Historical Ocean Wave Height Trend Assessment M. Casas-Prat et al. https://doi.org/10.3389/fmars.2022.847017
126. Advancing research on compound weather and climate events via large ensemble model simulations E. Bevacqua et al. https://doi.org/10.1038/s41467-023-37847-5
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128. Current and future risk of unprecedented hydrological droughts in Great Britain W. Chan et al. https://doi.org/10.1016/j.jhydrol.2023.130074
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131. Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates C. Tebaldi et al. https://doi.org/10.5194/esd-12-1427-2021
132. Humans have already endangered their shared cultural heritage by amplifying extreme weather events S. Zhao et al. https://doi.org/10.1016/j.culher.2026.02.017
133. Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble F. Willkofer et al. https://doi.org/10.5194/hess-28-2969-2024
134. Climate change impact on hydrological droughts: Differences between two ensembles of regional climate projections across Great Britain R. Lane et al. https://doi.org/10.1016/j.ejrh.2026.103417
135. Concurrent modes of climate variability linked to spatially compounding wind and precipitation extremes in the Northern Hemisphere B. François et al. https://doi.org/10.5194/esd-16-1029-2025
136. Combined role of ENSO and IOD on compound drought and heatwaves in Australia using two CMIP6 large ensembles P. Reddy et al. https://doi.org/10.1016/j.wace.2022.100469
137. Large Ensemble Simulations of Climate Models for Climate Change Research: A Review P. Lin et al. https://doi.org/10.1007/s00376-024-4012-2
138. Downscaling with AI reveals the large role of internal variability in fine-scale projections of climate extremes N. Rampal et al. https://doi.org/10.1007/s00382-026-08269-y
139. The application of applied category theory to quantify mission success R. Garrett et al. https://doi.org/10.1177/00375497221114861
140. A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe – Part 2: Historical context and relation to climate change P. Ludwig et al. https://doi.org/10.5194/nhess-23-1287-2023
141. Modulation of Northern Europe near-term anthropogenic warming and wettening assessed through internal variability storylines A. Liné et al. https://doi.org/10.1038/s41612-024-00759-2
142. A simulation-supported thought experiment for measuring low-dimensional chaotic systems subjected to parameter drift M. Herein et al. https://doi.org/10.1063/5.0230984
143. Increasing Risks of Future Compound Climate Extremes With Warming Over Global Land Masses H. Wu et al. https://doi.org/10.1029/2022EF003466