4 citations · 6 across the 8 of their papers we have counts for
9 papers
Coupled multiscale paleoclimate reconstruction with four-dimensional variational data assimilation
Zilu Meng, Gregory J. Hakim, Julien Emile-Geay +2
Paleoclimate archives extend climate knowledge beyond the instrumental era, registering different seasons, variables, time averages, and memory lengths. A longstanding problem is t…
Gray Swan Factory: Making Extreme Events from Ordinary Cyclones
Gregory J. Hakim, Aishwarya Agrawal
Gray swans, plausible but unobserved extreme events, broaden our understanding of the range of hazards beyond those observed during the short observational record. They are useful…
Large-Ensemble Simulations Reveal Links Between Atmospheric Blocking Frequency and Sea Surface Temperature Variability
Zilu Meng, Gregory J. Hakim, Wenchang Yang +1
Atmospheric blocking events drive persistent weather extremes in midlatitudes, but isolating the influence of sea surface temperature (SST) from chaotic internal atmospheric variab…
Top-of-atmosphere radiation over the last millennium reconstructed from proxies
Dominik Stiller, Gregory J. Hakim
Earth's energy imbalance at the top of the atmosphere is a key climate system metric, but its natural variability is poorly constrained by the short observational record and large…
Deep Learning Atmospheric Models Reliably Simulate Out-of-Sample Land Heat and Cold Wave Frequencies
Zilu Meng, Gregory J. Hakim, Wenchang Yang +1
Deep learning (DL)-based general circulation models (GCMs) are emerging as fast simulators, yet their ability to replicate extreme events outside their training range remains unkno…
The Boussinesq equation on the half-line
Christophe Charlier
We study the initial-boundary value problem for the Boussinesq equation on the half-line. Assuming that the solution exists, we prove that it can be recovered from its initial-boun…
Coupled Seasonal Data Assimilation of Sea Ice, Ocean, and Atmospheric Dynamics over the Last Millennium
Zilu Meng, Gregory J. Hakim, Eric J. Steig
"Online" data assimilation (DA) is used to generate a seasonal-resolution reanalysis dataset over the last millennium by combining forecasts from an ocean--atmosphere--sea-ice coup…
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…
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…