The driving of North American climate extremes by North Pacific stationary-transient wave interference.

Wave interference between transient waves and climatological stationary waves is a useful framework for diagnosing the magnitude of stationary waves. Here, we find that the wave interference over the North Pacific Ocean is an important driver of North American wintertime cold and heavy precipitation extremes in the present climate, but that this relationship is projected to weaken under increasing greenhouse gas emissions. When daily circulation anomalies are in-phase with the climatological mean state, the anomalous transport of heat and moisture causes the enhanced occurrence of cold extremes across the continental U.

A weakened AMOC may prolong greenhouse gas-induced Mediterranean drying even with significant and rapid climate change mitigation.

The Mediterranean region has been identified as a climate hot spot, with models projecting a robust warming and rainfall decline in response to increasing greenhouse gases. The projected rainfall decline would have impacts on agriculture and water resources. Can such changes be reversed with significant reductions in greenhouse gases? To explore this, we examine large ensembles of a high-resolution climate model with various future radiative forcing scenarios, including a scenario with substantial reductions in greenhouse gas concentrations beginning in the mid-21st century.

Increasing risk of another Cape Town "Day Zero" drought in the 21st century.

Three consecutive dry winters (2015-2017) in southwestern South Africa (SSA) resulted in the Cape Town "Day Zero" drought in early 2018. The contribution of anthropogenic global warming to this prolonged rainfall deficit has previously been evaluated through observations and climate models. However, model adequacy and insufficient horizontal resolution make it difficult to precisely quantify the changing likelihood of extreme droughts, given the small regional scale.

North Atlantic climate far more predictable than models imply.

Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain. This leads to low confidence in regional projections, especially for precipitation, over the coming decades.

Detected climatic change in global distribution of tropical cyclones.

Owing to the limited length of observed tropical cyclone data and the effects of multidecadal internal variability, it has been a challenge to detect trends in tropical cyclone activity on a global scale. However, there is a distinct spatial pattern of the trends in tropical cyclone frequency of occurrence on a global scale since 1980, with substantial decreases in the southern Indian Ocean and western North Pacific and increases in the North Atlantic and central Pacific. Here, using a suite of high-resolution dynamical model experiments, we show that the observed spatial pattern of trends is very unlikely to be explained entirely by underlying multidecadal internal variability; rather, external forcing such as greenhouse gases, aerosols, and volcanic eruptions likely played an important role.