67 citations as recorded by crossref.

1. Simulating hydrological extremes for different warming levels–combining large scale climate ensembles with local observation based machine learning models S. Hauswirth et al. 10.3389/frwa.2023.1108108
2. Comparison of ocean deoxygenation between CMIP models and an observational dataset in the North Pacific from 1958 to 2005 Y. Abe & S. Minobe 10.3389/fmars.2023.1161451
3. Model spread in multidecadal North Atlantic Oscillation variability connected to stratosphere–troposphere coupling R. Bonnet et al. 10.5194/wcd-5-913-2024
4. Continental United States climate projections based on thermodynamic modification of historical weather A. Jones et al. 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. 10.1002/joc.8197
6. 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. 10.5194/gmd-16-4853-2023
7. Interpretable polynomial neural ordinary differential equations C. Fronk & L. Petzold 10.1063/5.0130803
8. Rising risks of hydroclimatic swings: A large ensemble study of dry and wet spell transitions in North America W. Na & M. Najafi 10.1016/j.gloplacha.2024.104476
9. The SMHI Large Ensemble (SMHI-LENS) with EC-Earth3.3.1 K. Wyser et al. 10.5194/gmd-14-4781-2021
10. Dependence of strategic solar climate intervention on background scenario and model physics J. Fasullo & J. Richter 10.5194/acp-23-163-2023
11. Demystifying global climate models for use in the life sciences D. Schoeman et al. 10.1016/j.tree.2023.04.005
12. Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events M. Schirmer et al. 10.5194/tc-16-3469-2022
13. 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
14. Extreme and compound ocean events are key drivers of projected low pelagic fish biomass N. Le Grix et al. 10.1111/gcb.16968
15. 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
16. 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. 10.1016/j.jhydrol.2024.131679
17. Severe compound events of low wind and cold temperature for the British power system L. Lücke et al. 10.1002/met.2219
18. Effects of forcing differences and initial conditions on inter-model agreement in the VolMIP volc-pinatubo-full experiment D. Zanchettin et al. 10.5194/gmd-15-2265-2022
19. Exploring the contribution of low‐frequency internal variability modes to global mean sea surface temperature variability based on large ensembles L. Yang et al. 10.1002/joc.8515
20. Temperature emergence at decision-relevant scales L. Harrington 10.1088/1748-9326/ac19dc
21. The influence of variability on fire weather conditions in high latitude regions under present and future global warming M. Lund et al. 10.1088/2515-7620/acdfad
22. Effects of storms on fisheries and aquaculture: An Icelandic case study on climate change adaptation N. Sühring et al. 10.1080/15230430.2023.2269689
23. Applying global warming levels of emergence to highlight the increasing population exposure to temperature and precipitation extremes D. Gampe et al. 10.5194/esd-15-589-2024
24. Unsupervised detection of large-scale weather patterns in the northern hemisphere via Markov State Modelling: from blockings to teleconnections S. Springer et al. 10.1038/s41612-024-00659-5
25. A Deep Learning Approach for the Identification of Long-Duration Mixed Precipitation in Montréal (Canada) M. Mittermeier et al. 10.1080/07055900.2021.1992341
26. Quantifying the contribution of forcing and three prominent modes of variability to historical climate A. Schurer et al. 10.5194/cp-19-943-2023
27. Predicting Slowdowns in Decadal Climate Warming Trends With Explainable Neural Networks Z. Labe & E. Barnes 10.1029/2022GL098173
28. An overview of the E3SM version 2 large ensemble and comparison to other E3SM and CESM large ensembles J. Fasullo et al. 10.5194/esd-15-367-2024
29. Theoretical tools for understanding the climate crisis from Hasselmann’s programme and beyond V. Lucarini & M. Chekroun 10.1038/s42254-023-00650-8
30. Assessing Outcomes in Stratospheric Aerosol Injection Scenarios Shortly After Deployment D. Hueholt et al. 10.1029/2023EF003488
31. A deep learning based classification of atmospheric circulation types over Europe: projection of future changes in a CMIP6 large ensemble M. Mittermeier et al. 10.1088/1748-9326/ac8068
32. A 100-member ensemble simulations of global historical (1951–2010) wave heights M. Casas-Prat et al. 10.1038/s41597-023-02058-6
33. The Role of the North Atlantic Oscillation for Projections of Winter Mean Precipitation in Europe C. McKenna & A. Maycock 10.1029/2022GL099083
34. Reliability of simulating internal precipitation variability over multi‐timescales using multiple global climate model large ensembles in China J. Liu et al. 10.1002/joc.8210
35. Where are the coexisting parallel climates? Large ensemble climate projections from the point of view of chaos theory M. Herein et al. 10.1063/5.0136719
36. The Super-large Ensemble Experiments of CAS FGOALS-g3 P. Lin et al. 10.1007/s00376-022-1439-1
37. 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 10.1007/s00382-024-07213-2
38. An ensemble based approach for the effect of climate change on the dynamics of extremes M. Herein et al. 10.3389/feart.2023.1267473
39. The KNMI Large Ensemble Time Slice (KNMI–LENTIS) L. Muntjewerf et al. 10.5194/gmd-16-4581-2023
40. The Arctic has warmed nearly four times faster than the globe since 1979 M. Rantanen et al. 10.1038/s43247-022-00498-3
41. Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6 D. Lafferty & R. Sriver 10.1038/s41612-023-00486-0
42. 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. 10.5194/gmd-15-8221-2022
43. Diffusion model-based probabilistic downscaling for 180-year East Asian climate reconstruction F. Ling et al. 10.1038/s41612-024-00679-1
44. Attributing heavy rainfall event in Berchtesgadener Land to recent climate change – Further rainfall intensification projected for the future B. Poschlod 10.1016/j.wace.2022.100492
45. Role of mean and variability change in changes in European annual and seasonal extreme precipitation events R. Wood 10.5194/esd-14-797-2023
46. Quantifying the extremity of 2022 Chinese Yangtze River Valley daily hot extreme: fixed or moving baseline matters L. Li et al. 10.1088/1748-9326/ad4e49
47. Tropical cyclone-induced coastal sea level projection and the adaptation to a changing climate N. Mori & T. Shimura 10.1017/cft.2022.6
48. Effects of Internal Climate Variability on Historical Ocean Wave Height Trend Assessment M. Casas-Prat et al. 10.3389/fmars.2022.847017
49. Advancing research on compound weather and climate events via large ensemble model simulations E. Bevacqua et al. 10.1038/s41467-023-37847-5
50. Developing user-informed fire weather projections for Canada L. Van Vliet et al. 10.1016/j.cliser.2024.100505
51. Current and future risk of unprecedented hydrological droughts in Great Britain W. Chan et al. 10.1016/j.jhydrol.2023.130074
52. Time-Varying Evaluation of Compound Drought and Hot Extremes in Machine Learning–Predicted Ensemble CMIP5 Future Climate: A Multivariate Multi-Index Approach S. Swain et al. 10.1061/JHYEFF.HEENG-6026
53. Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates C. Tebaldi et al. 10.5194/esd-12-1427-2021
54. Improving statistical projections of ocean dynamic sea-level change using pattern recognition techniques V. Malagón-Santos et al. 10.5194/os-19-499-2023
55. Can limiting global temperature rise to below 2°C warming prevent the emergence of unprecedented drought? Y. Ji et al. 10.1016/j.agrformet.2024.110047
56. Contrasting changes in hydrological processes of the Volta River basin under global warming M. Dembélé et al. 10.5194/hess-26-1481-2022
57. Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble F. Willkofer et al. 10.5194/hess-28-2969-2024
58. Uncertainty Analysis in Multi‐Sector Systems: Considerations for Risk Analysis, Projection, and Planning for Complex Systems V. Srikrishnan et al. 10.1029/2021EF002644
59. Detection of Forced Change Within Combined Climate Fields Using Explainable Neural Networks J. Rader et al. 10.1029/2021MS002941
60. West Antarctic Surface Climate Changes Since the Mid‐20th Century Driven by Anthropogenic Forcing Q. Dalaiden et al. 10.1029/2022GL099543
61. Combined role of ENSO and IOD on compound drought and heatwaves in Australia using two CMIP6 large ensembles P. Reddy et al. 10.1016/j.wace.2022.100469
62. The application of applied category theory to quantify mission success R. Garrett et al. 10.1177/00375497221114861
63. 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. 10.5194/nhess-23-1287-2023
64. Storm surges and extreme sea levels: Review, establishment of model intercomparison and coordination of surge climate projection efforts (SurgeMIP). N. Bernier et al. 10.1016/j.wace.2024.100689
65. Increasing Risks of Future Compound Climate Extremes With Warming Over Global Land Masses H. Wu et al. 10.1029/2022EF003466
66. Simulation of hydropower at subcontinental to global scales: a state-of-the-art review S. Turner & N. Voisin 10.1088/1748-9326/ac4e38
67. Comparison of Climate Model Large Ensembles With Observations in the Arctic Using Simple Neural Networks Z. Labe & E. Barnes 10.1029/2022EA002348