15 papers in the archive.
Unsupervised learning finds three propagation modes of Indo-Pacific rainfall extremes linked to Pacific SST, with early warning skill up to four weeks ahead.
Climate analysis & attributionTechnical University of Munich (TUM)Potsdam Institute for Climate Impact Research (PIK)
Physically constrained cGANs correct CMIP6-class Earth system model precipitation biases in both local distributions and spatial patterns, outperforming existing methods on extremes' spatial intermittency.
Post-processing & calibrationPotsdam Institute for Climate Impact Research (PIK)Technical University of Munich (TUM)
Argues that making Earth system models automatically differentiable enables objective calibration and hybrid ML components, targeting climate sensitivity, spatial biases and abrupt transitions.
Hybrid physics-ML & parameterizationPotsdam Institute for Climate Impact Research (PIK)Technical University of Munich (TUM)
A physically constrained GAN corrects Earth system model precipitation, fixing local distributions and the double-peaked ITCZ while preserving global precipitation sums under future scenarios.
Downscaling & super-resolutionPotsdam Institute for Climate Impact Research (PIK)Technical University of Munich (TUM)
Echo state network trained on low-frequency ENSO indices skilfully predicts El Niño up to 21 months ahead, with correlation above 0.5.
Sub-seasonal to seasonalTechnical University of Munich (TUM)Potsdam Institute for Climate Impact Research (PIK)
Random forests with explainable AI on ERA5 identify drivers of subseasonal high summer temperatures in Europe, with useful skill for warm anomalies at 15-day lead.
Sub-seasonal to seasonalKNMI (Royal Netherlands Meteorological Institute)Potsdam Institute for Climate Impact Research (PIK)
Deep networks trained on an NWP ensemble with a frequency-weighted loss correct rainfall, improving extreme-event forecast skill by factors of two to above six.
Post-processing & calibrationPotsdam Institute for Climate Impact Research (PIK)Technical University of Munich (TUM)
Perspective proposing Neural Earth System Modelling, which fuses deep networks and Earth system models into interpretable hybrids that might eventually replace them.
Hybrid physics-ML & parameterizationColorado State University (incl. CIRA)NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)Potsdam Institute for Climate Impact Research (PIK)Princeton UniversityUniversity of Washington
Machine learning models explain up to 65% of historical crop yield anomalies in 17 European countries, linking 2018 extreme temperature and rainfall to losses.
Applications & impactsPotsdam Institute for Climate Impact Research (PIK)
Three-stage random forest and XGBoost ensemble estimates hourly 1 km air temperature over Israel from geostationary satellite skin temperature and station data.
Observations & remote sensingPotsdam Institute for Climate Impact Research (PIK)
Two-stage random forest hybrid estimates gridded 1 km intra-daily near-surface air temperature over Israel from satellite skin temperature, with out-of-sample R2 of 0.96 for air temperature.
Observations & remote sensingPotsdam Institute for Climate Impact Research (PIK)
Nonlinear causal discovery method estimates interdependency networks from large generic time series datasets.
Climate analysis & attributionThe Alan Turing InstitutePotsdam Institute for Climate Impact Research (PIK)University of Oxford
Uses machine learning on sub-national yield data to show climate extremes explain 18-43% of yield-anomaly variance, with temperature extremes dominating global crop losses.
Applications & impactsETH ZurichPotsdam Institute for Climate Impact Research (PIK)
Opinion article arguing machine learning should be adopted for S2S forecasting, showing statistical methods beat dynamical models on a polar vortex case.
Sub-seasonal to seasonalMicrosoft Research (AI for Science)Massachusetts Institute of Technology (MIT)Potsdam Institute for Climate Impact Research (PIK)Stanford University
Causal effect networks identify Barents and Kara sea ice and Eurasian snow cover as drivers of winter Arctic Oscillation and midlatitude circulation.
Climate analysis & attributionPotsdam Institute for Climate Impact Research (PIK)
