Abstract 2023 was the warmest year on record, influenced by multiple warm ocean basins.
This has prompted speculation of an acceleration in surface warming, or a stronger than …

We present a lightweight, easy-to-train, low-resolution, fully data-driven climate emulator,
LUCIE, that can be trained on as low as $2 $ years of $6 $-hourly ERA5 data. Unlike most …

Recent studies indicate that virtually all global climate models (GCMs) have had difficulty
simulating sea surface temperature (SST) trend patterns over the past four decades. GCMs …

Predicting forced, long‐term radiative feedbacks from internal climate variability has been a
decades‐long quest in climate science. We train a convolutional neural network (CNN) to …

Projections of future tropical cyclone frequency are uncertain, ranging from a slight increase
to a considerable decrease according to climate models. Estimation of how much the Earth's …

Investigation of the major factors determining tropical upper-level cloud radiative effect
(TUCRE) is crucial for understanding cloud feedback mechanisms. We examined the …

Near‐term projections of drought in the southwestern United States (SWUS) are uncertain.
The observed decrease in SWUS precipitation since the 1980s and heightened drought …

Climate models exhibit an approximately invariant surface warming pattern in typical end-of-
century projections. This observation has been used extensively in climate impact …

The global surface temperature climate feedback parameter λ varies significantly across
climate models, and its real-world value remains uncertain. Studies have found that the sea …

In 2023, the world experienced its highest ever global mean surface temperature (GMST).
Our study underscores the pivotal significance of El Niño and sea surface temperature (SST) …