Climate dynamics

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:

Central stages in the evolution of rocky, potentially habitable planets may play out under atmospheric conditions with a large inventory of nondilute condensable components. Variations in condensate retention and accompanying changes in local lapse rate may substantially affect planetary climate and surface conditions, but there is currently no general theory to effectively describe such atmospheres. In this article, expanding on the work by Li et al., we generalize the single-component moist pseudoadiabat derivation in Pierrehumbert to allow for multiple condensing components of arbitrary diluteness and retained condensate fraction. The introduction of a freely tunable retained condensate fraction allows for a flexible, self-consistent treatment of atmospheres with nondilute condensable components. To test the pseudoadiabat's capabilities for simulating a diverse range of climates, we apply the formula to planetary atmospheres with compositions, surface pressures, and temperatures representing important stages with condensable-rich atmospheres in the evolution of terrestrial planets: a magma ocean planet in a runaway greenhouse state; a post-impact, late-veneer-analog planet with a complex atmospheric composition; and an Archean Earth-like planet near the outer edge of the classical circumstellar habitable zone. We find that variations in the retention of multiple nondilute condensable species can significantly affect the lapse rate and in turn outgoing radiation and the spectral signatures of planetary atmospheres. The presented formulation allows for a more comprehensive treatment of the climate evolution of rocky exoplanets and early Earth analogs.

Abstract:

Internal climate variability will play a major role in determining change on regional scales under global warming. In the extratropics, large-scale atmospheric circulation is responsible for much of observed regional climate variability, from seasonal to multidecadal timescales. However, the extratropical circulation variability on multidecadal timescales is systematically weaker in coupled climate models. Here we show that projections of future extratropical climate from coupled model simulations significantly underestimate the projected uncertainty range originating from large-scale atmospheric circulation variability. Using observational datasets and large ensembles of coupled climate models, we produce synthetic ensemble projections constrained to have variability consistent with the large-scale atmospheric circulation in observations. Compared to the raw model projections, the synthetic observationally-constrained projections exhibit an increased uncertainty in projected 21st century temperature and precipitation changes across much of the Northern extratropics. This increased uncertainty is also associated with an increase of the projected occurrence of future extreme seasons.