2 papers
physics.ao-ph2026
Estimation of temperature and precipitation uncertainties using quantile neural networks
Andrew Brettin, Laure Zanna
Extreme events pose significant risks and are challenging to predict. Assessing climate hazards requires placing quantitative constraints on geophysical fields under observable but…
physics.ao-ph2025
Uncertainty-permitting machine learning reveals sources of dynamic sea level predictability across daily-to-seasonal timescales
Andrew Brettin, Laure Zanna, Elizabeth A. Barnes
Reliable dynamic sea level forecasts are hindered by numerous sources of uncertainty on daily-to-seasonal timescales (1-180 days) due to atmospheric boundary conditions and interna…