Equilibrium climate sensitivity‐the equilibrium warming per CO2 doubling‐increases with CO2 concentration for 13 of 14 coupled general circulation models for 0.5–8 times the preindustrial concentration. In particular, the abrupt 4 × CO2 equilibrium warming is more than twice the 2 × CO2 warming. We identify three potential causes: nonlogarithmic forcing, feedback CO2 dependence, and feedback temperature dependence. Feedback temperature dependence explains at least half of the sensitivity increase, while feedback CO2 dependence explains a smaller share, and nonlogarithmic forcing decreases sensitivity in as many models as it increases it. Feedback temperature dependence is positive for 10 out of 14 models, primarily due to the longwave clear‐sky feedback, while cloud feedbacks drive particularly large sensitivity increases. Feedback temperature dependence increases the risk of extreme or runaway warming, and is estimated to cause six models to warm at least an additional 3K under 8 × CO2.

To analyze a pollution process in Sichuan from 12 December 2017 to 2 January 2018, hourly pollutant data from 90 environmental monitors with surface data and sounding data from 21 meteorological stations were used to determine the sources of pollutants and the correlation between pollution levels and meteorological conditions. The results show that the whole process could be divided into two parts: (1) from 20 December 2017 to 30 December 2017, when, driven by a static stable atmosphere, the Sichuan basin experienced a long-lasting haze episode with an air quality index (AQI) that exceeded 150; and (2) after 30 December 2017, when a Mongolian cyclone developed and brought a large amount of cold air to Sichuan that improved the horizontal and vertical turbulence exchange and removed most of the pollutants. However, the northern part of Sichuan, affected by the cold air that carried dust from Shanxi and Qinghai, suffered an abrupt change in the extent of PM10 that led to an aggravation of this pollution process.

Abstract. Responses of El Niño–Southern Oscillation (ENSO) to global warming remain uncertain, which challenges ENSO forecasts in a warming climate. We investigate changes in ENSO characteristics and predictability in idealized simulations with quadrupled CO2 forcing from seven general circulation models. Comparing the warmer climate to control simulations, ENSO variability weakens, with the neutral state lasting longer, while active ENSO states last shorter and skew to favor the La Niña state. The 6-month persistence-assessed ENSO predictability slightly reduces in five models and increases in two models under the warming condition. While the overall changes in ENSO predictability are insignificant, we find significant relationships between changes in predictability and intensity, duration, and skewness of the three individual ENSO states. The maximal contribution to changes in the predictability of El Niño, La Niña and neutral states stems from changes in skewness and events' duration. Our findings show that a robust and significant decrease in ENSO characteristics does not imply a similar change in ENSO predictability in a warmer climate. This could be due to model deficiencies in ENSO dynamics and limitations in the persistence model when predicting ENSO.