4 citations · 8 across the 3 of their papers we have counts for
3 papers
physics.ao-ph2024★ 1 cited
Reconstructing the Tropical Pacific Upper Ocean using Online Data Assimilation with a Deep Learning model
Zilu Meng, Gregory J. Hakim
A deep learning (DL) model, based on a transformer architecture, is trained on a climate-model dataset and compared with a standard linear inverse model (LIM) in the tropical Pacif…
physics.ao-ph2024★ 3 cited
Predictability Limit of the 2021 Pacific Northwest Heatwave from Deep-Learning Sensitivity Analysis
P. Trent Vonich, Gregory J. Hakim
The traditional method for estimating weather forecast sensitivity to initial conditions uses adjoint models, which are limited to short lead times due to linearization around a co…
physics.ao-ph2023★ 4 cited
Dynamical Tests of a Deep-Learning Weather Prediction Model
Gregory J. Hakim, Sanjit Masanam
Global deep-learning weather prediction models have recently been shown to produce forecasts that rival those from physics-based models run at operational centers. It is unclear wh…