With the rapid development of artificial intelligence, machine learning is gradually becoming
popular for predictions in all walks of life. In meteorology, it is gradually competing with …

While seasonal outlooks have been operational for many years, until recently the extended‐
range timescale referred to as subseasonal‐to‐seasonal (S2S) has received little attention …

Climate-related financial risks (CRFR) are now recognised by central banks and supervisors
as material to their financial stability mandates. But while CRFR are considered to have …

This study evaluates global climate models participating in the Coupled Model
Intercomparison Project phase 6 (CMIP6) for their performance in simulating the climate …

The double‐intertropical convergence zone (ITCZ) bias is one of the most outstanding errors
in all previous generations of climate models. Here, the annual double‐ITCZ bias and the …

Government policies currently commit us to surface warming of three to four degrees Celsius
above pre-industrial levels by 2100, which will lead to enhanced ice-sheet melt. Ice-sheet …

Patterns of future climate and expected extreme conditions are pushing design limits as
recognition of climate change and its implication for the built environment increases. There …

Climate models have continued to be developed and improved since the AR4, and many
models have been extended into Earth System models by including the representation of …

The frequency of climate extremes will change in response to shifts in both mean climate
and climate variability. These individual contributions, and thus the fundamental …

This paper evaluates sea surface temperature (SST) biases of coupled models participating
in Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. Overall, CMIP6 …