Windows of opportunity for predicting seasonal climate extremes highlighted by the Pakistan floods of 2022.

Skilful predictions of near-term climate extremes are key to a resilient society. However, standard methods of analysing seasonal forecasts are not optimised to identify the rarer and most impactful extremes. For example, standard tercile probability maps, used in real-time regional climate outlooks, failed to convey the extreme magnitude of summer 2022 Pakistan rainfall that was, in fact, widely predicted by seasonal forecasts.

Publisher Correction: Critical Southern Ocean climate model biases traced to atmospheric model cloud errors.

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Critical Southern Ocean climate model biases traced to atmospheric model cloud errors.

The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate models, with significant biases in upper-ocean temperatures, clouds and winds. Combining Atmospheric and Coupled Model Inter-comparison Project (AMIP5/CMIP5) simulations, with observations and equilibrium heat budget theory, we show that across the CMIP5 ensemble variations in sea surface temperature biases in the 40-60°S Southern Ocean are primarily caused by AMIP5 atmospheric model net surface flux bias variations, linked to cloud-related short-wave errors. Equilibration of the biases involves local coupled sea surface temperature bias feedbacks onto the surface heat flux components.

No Robust Evidence of Future Changes in Major Stratospheric Sudden Warmings: A Multi-model Assessment from CCMI.

Major stratospheric sudden warmings (SSWs) are the largest instance of wintertime variability in the Arctic stratosphere. Due to their relevance for the troposphere-stratosphere system, several previous studies have focused on their potential response to anthropogenic forcings. However, a wide range of results have been reported, from a future increase in the frequency of SSWs to a decrease.

Deriving Global OH Abundance and Atmospheric Lifetimes for Long-Lived Gases: A Search for CHCCl Alternatives.

An accurate estimate of global hydroxyl radical (OH) abundance is important for projections of air quality, climate, and stratospheric ozone recovery. As the atmospheric mixing ratios of methyl chloroform (CHCCl) (MCF), the commonly used OH reference gas, approaches zero, it is important to find alternative approaches to infer atmospheric OH abundance and variability. The lack of global bottom-up emission inventories is the primary obstacle in choosing a MCF alternative.