11 papers in the archive.
Hybrid NWP-AI system spectrally nudges GEM toward GraphCast large scales, improving prediction skill and tropical cyclone tracks while keeping physically consistent fine scales.
Hybrid physics-ML & parameterizationEnvironment and Climate Change Canada (ECCC)
A physics-informed recurrent deep learning model super-resolves regional climate precipitation from 2.5 km to 250 m, producing realistic intense short-duration events over Montreal.
Downscaling & super-resolutionEnvironment and Climate Change Canada (ECCC)
GANs statistically downscale near-surface winds to convection-permitting WRF scales, with spectral analysis exposing spatial-structure biases and a partial frequency-separation loss.
Downscaling & super-resolutionEnvironment and Climate Change Canada (ECCC)
WMO prize challenge winners used AI to post-process ECMWF S2S forecasts, beating bias-corrected references for weeks 3-6 precipitation and temperature.
Sub-seasonal to seasonalColumbia University (LEAP, Lamont-Doherty)Environment and Climate Change Canada (ECCC)ECMWFMax Planck Institute for MeteorologySwiss Data Science Center (SDSC)
Machine learning regression on ten years of airport station data nowcasts visibility and ceiling height up to 1 h, with MAE of about 324 m and 167 m.
Local & station forecastingEnvironment and Climate Change Canada (ECCC)
ClimART offers over 10 million radiative transfer samples from climate conditions to benchmark neural emulators, showing shortcomings of prior datasets and architectures.
Benchmarks, datasets & evaluationEnvironment and Climate Change Canada (ECCC)code
Adversarial sub-pixel CNN super-resolves 2.5 km regional climate simulations of Montreal to 250 m, improving urban temperature errors and heat-stress indicators.
Downscaling & super-resolutionEnvironment and Climate Change Canada (ECCC)
Gradient-boosting and related ML models forecast Eurasian winter precipitation seasonally, outperforming linear regression and matching or beating dynamical models; Arctic autumn sea ice is a key predictor.
Sub-seasonal to seasonalEnvironment and Climate Change Canada (ECCC)
SVR and XGBoost seasonal winter surface air temperature forecasts over North America outperform two dynamical models in 2011–2017 real-time tests.
Sub-seasonal to seasonalEnvironment and Climate Change Canada (ECCC)
A neural network infers gridded marine surface visibility over the Indian Ocean from satellite optical thickness and reanalysis, with mean error under 8%.
Observations & remote sensingEnvironment and Climate Change Canada (ECCC)
An expanded Bernoulli-gamma neural density network downscales multisite daily precipitation from synoptic predictors, reproducing spatial covariances and generating realistic synthetic series in coastal British Columbia.
Downscaling & super-resolutionEnvironment and Climate Change Canada (ECCC)
