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Australian wildfire smoke in the stratosphere: the decay phase in 2020/2021 and impact on ozone depletion

We present and discuss 2 years of long-term lidar observations of the largest stratospheric perturbation by wildfire smoke ever observed. The smoke originated from the record-breaking Australian fires in 2019–2020 and affects climate conditions and even the ozone layer in the Southern Hemisphere. The obvious link between dense smoke occurrence in the stratosphere and strong ozone depletion found in the Arctic and in the Antarctic in 2020 can be regarded as a new aspect of climate change.

New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra

Drizzle (small rain droplets) is an important component of warm clouds; however, its existence is poorly understood. In this study, we capitalized on a machine-learning algorithm to develop a drizzle detection method. We applied this algorithm to investigate drizzle occurrence and found out that drizzle is far more ubiquitous than previously thought. This study demonstrates the ubiquitous nature of drizzle in clouds and will improve understanding of the associated microphysical process.

Glacial runoff buffers droughts through the 21st century

Global climate models suggest that droughts could worsen over the coming century. In mountain basins with glaciers, glacial runoff can ease droughts, but glaciers are retreating worldwide. We analysed how one measure of drought conditions changes when accounting for glacial runoff that changes over time. Surprisingly, we found that glacial runoff can continue to buffer drought throughout the 21st century in most cases, even as the total amount of runoff declines.

Downscaling of climate change scenarios for a high-resolution, site-specific assessment of drought stress risk for two viticultural regions with heterogeneous landscapes

We modelled water budget developments of viticultural growing regions on the spatial scale of individual vineyard plots with respect to landscape features like the available water capacity of the soils, slope, and aspect of the sites. We used an ensemble of climate simulations and focused on the occurrence of drought stress. The results show a high bandwidth of projected changes where the risk of potential drought stress becomes more apparent in steep-slope regions.

Multi-century dynamics of the climate and carbon cycle under both high and net negative emissions scenarios

We explore the long-term dynamics of Earth’s climate and carbon cycles under a pair of contrasting scenarios to the year 2300 using six models that include both climate and carbon cycle dynamics. One scenario assumes very high emissions, while the second assumes a peak in emissions, followed by rapid declines to net negative emissions. We show that the models generally agree that warming is roughly proportional to carbon emissions but that many other aspects of the model projections differ.

Gaps in network infrastructure limit our understanding of biogenic methane emissions for the United States

To understand the CH4 flux potential of natural ecosystems and agricultural lands in the United States of America, a multi-scale CH4 observation network focused on CH4 flux rates, processes, and scaling methods is required. This can be achieved with a network of ground-based observations that are distributed based on climatic regions and land cover.

Currents generated by the sea breeze in the southern Caspian Sea

The smaller thermal heat capacity of land relative to the sea results in land–sea thermal gradients with a daily cycle, called sea breeze systems, with the same daily periodicity. Since tides in the Caspian, as the largest enclosed basin with a persistent sea breeze system through the year, are very weak we found that most of the higher-frequency variations in coastal currents are a response to the sea breeze system.

Training a supermodel with noisy and sparse observations: a case study with CPT and the synch rule on SPEEDO – v.1

In this study, we present a novel formulation to build a dynamical combination of models, the so-called supermodel, which needs to be trained based on data. Previously, we assumed complete and noise-free observations. Here, we move towards a realistic scenario and develop adaptations to the training methods in order to cope with sparse and noisy observations. The results are very promising and shed light on how to apply the method with state of the art general circulation models.

Lévy noise versus Gaussian-noise-induced transitions in the Ghil–Sellers energy balance model

In most of the investigations on metastable systems, the stochastic forcing is modulated by Gaussian noise. Lévy noise laws, which describe jump processes, have recently received a lot of attention, but much less is known. We study stochastic versions of the Ghil–Sellers energy balance model, and we highlight the fundamental difference between how transitions are performed between the competing warm and snowball states, depending on whether Gaussian or Lévy noise acts as forcing.

Assessing the consequences of including aerosol absorption in potential stratospheric aerosol injection climate intervention strategies

Simulations are presented investigating the influence of moderately absorbing aerosol in the stratosphere to combat the impacts of climate change. A number of detrimental impacts are noted compared to sulfate aerosol, including (i) reduced cooling efficiency, (ii) increased deficits in global precipitation, (iii) delays in the recovery of the stratospheric ozone hole, and (iv) disruption of the stratospheric circulation and the wintertime storm tracks that impact European precipitation.

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