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Abstract:

The question of how humans have influenced individual extreme weather events is both scientifically and socially important. However, deficiencies in climate models’ representations of key mechanisms within the process chains that drive weather reduce our confidence in estimates of the human influence on extreme events. We propose that using forecast models that successfully predicted the event in question could increase the robustness of such estimates. Using a successful forecast means we can be confident that the model is able to faithfully represent the characteristics of the specific extreme event. We use this forecast-based methodology to estimate the direct radiative impact of increased CO2 concentrations (one component, but not the entirety, of human influence) on the European heatwave of February 2019.

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.