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Trends in surface air temperature (SAT) are a common metric for global warming. Using observations and observationally driven models, we show that a more comprehensive metric for global warming and weather extremes is the trend in surface equivalent potential temperature (Thetae_sfc) since it also accounts for the increase in atmospheric humidity and latent energy. From 1980 to 2019, while SAT increased by 0.79 ° C , Thetae_sfc increased by 1.48 ° C globally and as much as 4 ° C in the tropics. The increase in water vapor is responsible for the factor of 2 difference between SAT and Thetae_sfc trends. Thetae_sfc increased more uniformly (than SAT) between the midlatitudes of the southern hemisphere and the northern hemisphere, revealing the global nature of the heating added by greenhouse gases (GHGs). Trends in heat extremes and extreme precipitation are correlated strongly with the global/tropical trends in Thetae_sfc. The tropical amplification of Thetae_sfc is as large as the arctic amplification of SAT, accounting for the observed global positive trends in deep convection and a 20% increase in heat extremes. With unchecked GHG emissions, while SAT warming can reach 4.8 ° C by 2100, the global mean Thetae_sfc can increase by as much as 12 ° C , with corresponding increases of 12 ° C (median) to 24 ° C (5% of grid points) in land surface temperature extremes, a 14- to 30-fold increase in frequency of heat extremes, a 40% increase in the energy available for tropical deep convection, and an up to 60% increase in extreme precipitation. 

The double-ITCZ bias has puzzled the climate modeling community for more than two decades. Here we show that, over the northeastern Pacific Ocean, precipitation and sea surface temperature (SST) biases are seasonally dependent in the NCAR CESM1 and 37 CMIP5 models, with positive biases during boreal summer–autumn and negative biases during boreal winter–spring, although the easterly wind bias persists year round. This seasonally dependent bias is found to be caused by the model’s failure to reproduce the climatological seasonal wind reversal of the North American monsoon. During winter–spring, the observed easterly wind dominates, so the simulated stronger wind speed enhances surface evaporation and lowers SST. It is opposite when the observed wind turns to westerly during summer–autumn. An easterly wind bias, mainly evident in the lower troposphere, also occurs in the atmospheric model when the observed SST is prescribed, suggesting that it is of atmospheric origin. When the atmospheric model resolution is doubled in the CESM1, both SST and precipitation are improved in association with the reduced easterly wind bias. During boreal spring, when the double-ITCZ bias is most significant, the northern and southern ITCZ can be improved by 29.0% and 18.8%, respectively, by increasing the horizontal resolution in the CESM1. When dividing the 37 CMIP5 models into two groups on the basis of their horizontal resolutions, it is found that both the seasonally dependent biases over the northeastern Pacific and year-round biases over the southeastern Pacific are reduced substantially in the higher-resolution models, with improvement of ~30% in both regions during boreal spring. Close relationships between wind and precipitation biases over the northeastern and southeastern Pacific are also found among CMIP5 models.