collaborators

7 papers

physics.ao-ph2026

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…

physics.ao-ph2026

Atmospheric Predictability Beyond 30 Days with Machine Learning

P. Trent Vonich, Gregory J. Hakim

Atmospheric predictability research has long held that rapid error growth at small spatial scales imposes an intrinsic limit of roughly two weeks on deterministic weather forecast…

physics.ao-ph2026

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…

physics.ao-ph2026

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…

physics.ao-ph2026

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…

physics.ao-ph2025

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…