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Abstract:

Summer 2010 saw two simultaneous extremes linked by an atmospheric wave train: a record-breaking heatwave in Russia and severe floods in Pakistan. Here, we study this wave event using a large ensemble climate model experiment. First, we show that the circulation in 2010 reflected a recurrent wave train connecting the heatwave and flooding events. Second, we show that the occurrence of the wave train is favored by three drivers: (1) 2010 sea surface temperature anomalies increase the probability of this wave train by a factor 2-to-4 relative to the model’s climatology, (2) early-summer soil moisture deficit in Russia not only increases the probability of local heatwaves, but also enhances rainfall extremes over Pakistan by forcing an atmospheric wave response, and (3) high-latitude land warming favors wave-train occurrence and therefore rainfall and heat extremes. These findings highlight the complexity and synergistic interactions between different drivers, reconciling some seemingly contradictory results from previous studies.

Abstract:

We highlight some of the scientific benefits of the Aeolus Doppler Wind Lidar mission since its launch in August 2018. Its scientific objectives are to improve weather forecasts and to advance the understanding of atmospheric dynamics and its interaction with the atmospheric energy and water cycle. A number of meteorological and science institutes across the world are starting to demonstrate that the Aeolus mission objectives are being met. Its wind product is being operationally assimilated by four Numerical Weather Prediction (NWP) centres, thanks to demonstrated useful positive impact on NWP analyses and forecasts. Applications of its atmospheric optical properties product have been found, e.g., in the detection and tracking of smoke from the extreme Australian wildfires of 2020 and in atmospheric composition data assimilation. The winds are finding novel applications in atmospheric dynamics research, such as tropical phenomena (Quasi-Biennial Oscillation disruption events), detection of atmospheric gravity waves, and in the smoke generated vortex associated with the Australian wildfires. It has been applied in the assessment of other types of satellite derived wind information such as atmospheric motions vectors. Aeolus is already successful with hopefully more to come.

Abstract:

The quasi-biennial oscillation (QBO) of tropical stratospheric winds was disrupted during the 2019/20 Northern Hemisphere winter. We show that this latest disruption to the regular QBO cycling was similar in many respects to that seen in 2016, but initiated by horizontal momentum transport from the Southern Hemisphere. The predictable signal associated with the QBO's quasi-regular phase progression is lost during disruptions and the oscillation reemerges after a few months significantly shifted in phase from what would be expected if it had progressed uninterrupted. We infer from an increased wave-momentum flux into equatorial latitudes seen in climate model projections that disruptions to the QBO are likely to become more common in future. Consequently, it is possible that in the future, the QBO could be a less reliable source of predictability on lead times extending out to several years than it currently is.