Paleoclimate reconstruction relies on estimates of spatiotemporal relationships among
climate quantities to interpolate between proxy data. This work quantifies how structural …

We use online data assimilation to combine information from a linear inverse model of
coupled atmosphere‐ocean dynamics with proxy records to create a new annual‐resolution …

Abstract We evaluate Linear Inverse Models (LIMs) trained on last millennium model data to
predict Arctic sea‐ice concentration, thickness, and other atmospheric and oceanic variables …

Paleoclimate data assimilation (DA) is a tool for reconstructing past climates that directly
integrates proxy records with climate model output. Despite the potential for DA to expand …

Hydroclimate variability of the southwest United States (SWUS) is influenced by the tropical
Pacific Ocean, particularly through the teleconnection to El Niño/Southern Oscillation …

Abstract El Niño‐Southern Oscillation (ENSO) variability affects year‐to‐year changes in
North American hydroclimate. Extra‐tropical teleconnections are not always consistent …

Cyclostationary linear inverse models (CS-LIMs), generalized versions of the classical
(stationary) LIM, are advanced data-driven techniques for extracting the first-order time …

Winter extratropical cyclones (ETCs) are dominant features of winter weather on the east
coast of North America. These storms are characterized by high winds and heavy …

Proxy records that document the last 2000 years of climate provide evidence for the wide
range of the natural climate variability from inter‐annual to secular timescales not captured …

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 …