ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

doi:doi:10.57702/wladiipl

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

ClimSim is a large multi-scale dataset for hybrid physics-ML climate emulation. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator’s macro-scale physical state.

BibTex:

@dataset{Sungduk_Yu_and_Walter_M_Hannah_and_Liran_Peng_and_Jerry_Lin_and_Mohamed_Aziz_Bhouri_and_Ritwik_Gupta_and_Björn_Lütjens_and_Justus_C_Will_and_Gunnar_Behrens_and_Julius_J_M_Busecke_and_Nora_Loose_and_Charles_Stern_and_Tom_Beucler_and_Bryce_E_Harrop_and_Benjamin_R_Hillman_and_Andrea_M_Jenney_and_Savannah_L_Ferretti_and_Nana_Liu_and_Anima_Anandkumar_and_Noah_D_Brenowitz_and_Veronika_Eyring_and_Nicholas_Geneva_and_Pierre_Gentine_and_Stephan_Mandt_and_Jaideep_Pathak_and_Akshay_Subramaniam_and_Carl_Vondrick_and_Rose_Yu_and_Laure_Zanna_and_Tian_Zheng_and_Ryan_P_Abernathey_and_Fiaz_Ahmed_and_David_C_Bader_and_Pierre_Baldi_and_Elizabeth_A_Barnes_and_Christopher_S_Bretherton_and_Peter_M_Caldwell_and_Wayne_Chuang_and_Yilun_Han_and_Yu_Huang_and_Fernando_Iglesias-Suarez_and_Sanket_Jantre_and_Karthik_Kashinath_and_Marat_Khairoutdinov_and_Thorsten_Kurth_and_Nicholas_J_Lutsko_and_Po-Lun_Ma_and_Griffin_Mooers_and_J_David_Neelin_and_David_A_Randall_and_Sara_Shamekh_and_Mark_A_Taylor_and_Nathan_M_Urban_and_Janni_Yuval_and_Guang_J_Zhang_and_Michael_S_Pritchard_2024,
    abstract = {ClimSim is a large multi-scale dataset for hybrid physics-ML climate emulation. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator’s macro-scale physical state.},
    author = {Sungduk Yu and Walter M. Hannah and Liran Peng and Jerry Lin and Mohamed Aziz Bhouri and Ritwik Gupta and Björn Lütjens and Justus C. Will and Gunnar Behrens and Julius J. M. Busecke and Nora Loose and Charles Stern and Tom Beucler and Bryce E. Harrop and Benjamin R. Hillman and Andrea M. Jenney and Savannah L. Ferretti and Nana Liu and Anima Anandkumar and Noah D. Brenowitz and Veronika Eyring and Nicholas Geneva and Pierre Gentine and Stephan Mandt and Jaideep Pathak and Akshay Subramaniam and Carl Vondrick and Rose Yu and Laure Zanna and Tian Zheng and Ryan P. Abernathey and Fiaz Ahmed and David C. Bader and Pierre Baldi and Elizabeth A. Barnes and Christopher S. Bretherton and Peter M. Caldwell and Wayne Chuang and Yilun Han and Yu Huang and Fernando Iglesias-Suarez and Sanket Jantre and Karthik Kashinath and Marat Khairoutdinov and Thorsten Kurth and Nicholas J. Lutsko and Po-Lun Ma and Griffin Mooers and J. David Neelin and David A. Randall and Sara Shamekh and Mark A. Taylor and Nathan M. Urban and Janni Yuval and Guang J. Zhang and Michael S. Pritchard},
    doi = {10.57702/wladiipl},
    institution = {No Organization},
    keyword = {'climate emulation', 'climate modeling', 'hybrid physics-ML', 'machine learning'},
    month = {dec},
    publisher = {TIB},
    title = {ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation},
    url = {https://service.tib.eu/ldmservice/dataset/climsim--a-large-multi-scale-dataset-for-hybrid-physics-ml-climate-emulation},
    year = {2024}
}