Search

Small shallow cumulus clouds (<1 km) over the tropical oceans appear to possess the ability to self‐organize into mesoscale (10–100 km) patterns. To better understand the processes leading to such self‐organized convection, we present Cloud Botany, an ensemble of 103 large‐eddy simulations on domains of 150 km, produced by the Dutch Atmospheric Large Eddy Simulation model on supercomputer Fugaku. Each simulation is run in an idealized, fixed, larger‐scale environment, controlled by six free parameters. We vary these over characteristic ranges for the winter trades, including parameter combinations observed during the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) field campaign. In contrast to simulation setups striving for maximum realism, Cloud Botany provides a platform for studying idealized, and therefore more clearly interpretable causal relationships between conditions in the larger‐scale environment and patterns in mesoscale, self‐organized shallow convection. We find that any simulation that supports cumulus clouds eventually develops mesoscale patterns in their cloud fields. We also find a rich variety in these patterns as our control parameters change, including cold pools lined by cloudy arcs, bands of cross‐wind clouds and aggregated patches, sometimes topped by thin anvils. Many of these features are similar to cloud patterns found in nature. The published data set consists of raw simulation output on full 3D grids and 2D cross‐sections, as well as post‐processed quantities aggregated over the vertical (2D), horizontal (1D) and all spatial dimensions (time‐series). The data set is directly accessible from Python through the use of the EUREC4A intake catalog. Plain Language Summary: The organization of shallow cumulus clouds over the tropical ocean has recently received a lot of attention. This type of organization is potentially important for how the clouds are affected by a changing climate and also for how they modulate further warming. We present a collection of 103 detailed simulations of shallow cumulus clouds in idealized atmospheric environments. These environments are described by six parameters, and our collection is formed by systematically simulating different parameter combinations. This way an ensemble is created that spans up a multidimensional phase space of environmental conditions typical for the wintertime subtropical Atlantic Ocean. This approach allows us to form a picture of how the environmental conditions relate to the cloud organization that develops in the simulations. At a glance, most simulations evolve similarly: They quickly form small cumulus clouds, which then grow in size and organize into patterns. Often this leads to rainfall, which then causes further heterogeneity and pattern formation. The data is openly available online, and will serve future studies of cumulus clouds, their organization, and how they interact with the climate. Key Points: We present Cloud Botany, an ensemble of idealized large‐eddy simulations of the winter trade wind regions, controlled by six varied parametersThe parameter ranges are chosen to match the climatology of the trade wind regionThe simulations show a variety of cloud organization patterns: small cumulus, stripes, cold pools, cloud arcs, and anvils [ABSTRACT FROM AUTHOR]

In 1827, an Indian juggler named Mooty Madua Samme converted to Christianity in Stockholm, Sweden. This historical event got much attention in the press at the time – as did his succeeding marriage to a Swedish woman named Erica – and was celebrated as a victory for the Evangelical Lutheran faith. Later, in the 1840s, a narrative depicting the event spread via a travelogue by Xavier Marmier, which was translated and mediated through the Swedish press, and reacted to by Samme's priest; in the 1850s, Samme's name surfaced again – now in context of the contemporary freedom of religion debates in Sweden. In this article, we explore Samme's baptism (and interrelatedly, his marriage) by looking at newspaper mediations of the event and the related narratives. Seen from a microhistorical perspective, we show how Samme's conversion and religious otherness was utilised in contemporary religious and political discussions, and we argue that the event and narratives surrounding the baptism can augment our understanding of the Swedish nineteenth century religio‐cultural landscape in which he was situated. [ABSTRACT FROM AUTHOR]

A new generation of operational atmospheric models operating at horizontal resolutions in the range 200 m ∼ 2 km is becoming increasingly popular for operational use in numerical weather prediction and climate applications. Such grid spacings are becoming sufficiently fine to resolve a fraction of the turbulent transports. Here we analyze Large‐eddy simulation results of a convective boundary layer obtained by coarsening horizontal grid spacings up to 800 m. The aim is to explore the dependency of the mean state and turbulent fluxes on the grid resolution. Both isotropic and anisotropic eddy diffusion approaches are evaluated, where in the latter case the horizontal and vertical eddy diffusivities differ in accord with their horizontal and vertical grid spacings. For coarsening horizontal grid sizes entrainment at the top of the boundary layer tends to get slightly enhanced for isotropic diffusion, whereas for the anisotropic diffusion approach the vertically well‐mixed boundary‐layer structure becomes severely degraded. An analysis of the energy spectrum shows that anisotropic diffusion causes relatively more dissipation of variance at smaller length scales. This leads, in turn, to a shift of spectral energy toward larger length scales that also becomes apparent from a rather different kind of spatial organization of convection. The present study therefore suggests that details with regards to the representation of processes at small scales might impact the organization at length scales much larger than the smallest scales that can be resolved by the model. Plain Language Summary: A new generation of operational atmospheric models operating at horizontal resolutions in the range 200 m ∼ 2 km is becoming increasingly popular for operational use in numerical weather prediction and climate applications. Owing to ever increasing computational power their grid spacings are nowadays becoming sufficiently fine to allow for resolving a fraction of the turbulent transports. However, these types of models are operated with grid spacings that are much larger in the horizontal directions than in the vertical direction. In the present study we explore the extent to which the spatial organization of turbulence structures is affected by the size of the horizontal grid spacing. This question is addressed by means of large‐eddy simulation, which is an established modeling technique that has been designed specifically to resolve the dominant turbulent eddies at a high spatial resolution. It is found that differences in the way how turbulence at scales smaller than the grid spacing is calculated can have an effect on the organization of turbulent structures at much larger spatial scales. Key Points: A grid anisotropy factor is introduced to efficiently switch from an isotropic to an anisotropic eddy diffusion approach for large‐eddy simulation modelsThe organization of clear boundary‐layer convection depends on the horizontal grid spacings, most notably for the anisotropic eddy diffusion approachReduced variances at the smallest length scales may be compensated by opposite increases at larger length scales [ABSTRACT FROM AUTHOR]

In atmospheric modeling, superparameterization (SP) has gained popularity as a technique to improve cloud and convection representations in large‐scale models by coupling them locally to cloud‐resolving models. We show how the different representations of cloud water in the local and the global models in SP lead to a suppression of cloud advection and ultimately to a systematic underrepresentation of the cloud amount in the large‐scale model. We demonstrate this phenomenon in a regional SP experiment with the global model OpenIFS coupled to the local model Dutch Atmospheric Large Eddy Simulation, as well as in an idealized setup, where the large‐scale model is replaced by a simple advection scheme. As a starting point for mitigating the problem of suppressed cloud advection, we propose a scheme where the spatial variability of the local model's total water content is enhanced in order to match the global model's cloud condensate amount. The proposed scheme enhances the cloud condensate amount in the test cases, however a large discrepancy remains, caused by rapid dissipation of the clouds added by the proposed scheme. Plain Language Summary: In this article, we investigate a technique called superparameterization (SP) for improving how global weather and climate models represent clouds and convection. In current operational global weather and climate models, the resolution is limited to 10–100 km by computational resources. This is not sufficient to resolve cloud and convective processes. The effect of these processes must then be approximated by so‐called parameterizations. SP uses another, local atmospheric model with a higher resolution, nested inside the columns of the global model, to evaluate the effects of clouds and convection. By analyzing results from a superparameterized simulation, we show that SP as it is generally implemented suppresses advection of existing clouds from one grid column to another in the global model, leading to a severe underestimation of the amount of shallow clouds. The suppression occurs because the global and local models represent clouds in different ways, and the commonly used SP scheme does not communicate the full cloud information from the global model to the local one. Adding such a coupling of the cloud information to the SP scheme partially improves the advection of clouds. The remaining discrepancies indicate that there are still missing processes in the superparameterized representation of boundary layer clouds. Key Points: Superparameterization (SP) in weather and climate models is used to improve the representation of cloudsWe show that SP suppresses the transport of cloudsA scheme for controlling the humidity variation partially improves cloud representation in superparameterized models [ABSTRACT FROM AUTHOR]

The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations. Plain Language Summary: This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The data set of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We do not find a conclusive result for how cloud clustering changes as the climate warms. Key Points: Temperature, humidity, and clouds in radiative‐convective equilibrium vary substantially across modelsModels agree that self‐aggregation dries the atmosphere and reduces high cloudinessThere is no consistency in how self‐aggregation depends on warming [ABSTRACT FROM AUTHOR]

As a computationally attractive alternative for global large eddy simulations (LESs), we investigate the possibility of using comprehensive three‐dimensional LESs as a superparameterization that can replace all traditional parameterizations of atmospheric processes that are currently used in global models. We present the technical design for a replacement of the parameterization for clouds, convection, and turbulence of the global atmospheric model of the European Centre for Medium‐Range Weather Forecasts by the Dutch Atmospheric Large Eddy Simulation model. The model coupling consists of bidirectional data exchange between the global model and the high‐resolution LES models embedded within the columns of the global model. Our setup allows for selective superparameterization, that is, for applying superparameterization in local regions selected by the user, while keeping the standard parameterization of the global model intact outside this region. Computationally, this setup can result in major geographic load imbalance, because of the large difference in computational load between superparameterized and nonsuperparameterized model columns. To resolve this issue, we use a modular design where the local and global models are kept as distinct model codes and organize the model coupling such that all the local models run in parallel, separate from the global model. First simulation results, employing this design, demonstrate the potential of our approach. Key Points: We present an efficient implementation of a large eddy simulation (LES)‐based superparameterization in a global circulation modelSuperparameterization can be enabled for grid points in a selected areaThe initial results of an LES‐based superparameterized simulation are evaluated and found promising [ABSTRACT FROM AUTHOR]

Summary: Morphometrics, the assignment of quantities to biological shapes, is a powerful tool to address taxonomic, evolutionary, functional and developmental questions. We propose a novel method for shape quantification of complex modular architecture in thalloid plants, whose extremely reduced morphologies, combined with the lack of a formal framework for thallus description, have long rendered taxonomic and evolutionary studies extremely challenging. Using graph theory, thalli are described as hierarchical series of nodes and edges, allowing for accurate, homologous and repeatable measurements of widths, lengths and angles. The computer program MorphoSnake was developed to extract the skeleton and contours of a thallus and automatically acquire, at each level of organization, width, length, angle and sinuosity measurements. Through the quantification of leaf architecture in Hymenophyllum ferns (Polypodiopsida) and a fully worked example of integrative taxonomy in the taxonomically challenging thalloid liverwort genus Riccardia, we show that MorphoSnake is applicable to all ramified plants. This new possibility of acquiring large numbers of quantitative traits in plants with complex modular architectures opens new perspectives of applications, from the development of rapid species identification tools to evolutionary analyses of adaptive plasticity. [ABSTRACT FROM AUTHOR]

What determines countries' successful transition to democracy? This article explores the impact of granting civil rights in authoritarian regimes and especially the gendered aspect of this process. It argues that both men's and women's liberal rights are essential conditions for democratisation to take place: providing both women and men rights reduces an inequality that affects half of the population, thus increasing the costs of repression and enabling the formation of women's organising - historically important to spark protests in initial phases of democratisation. This argument is tested empirically using data that cover 173 countries over the years 1900-2012 and contain more nuanced measures than commonly used. Through novel sequence analysis methods, the results suggest that in order to gain electoral democracy a country first needs to furnish civil liberties to both women and men. [ABSTRACT FROM AUTHOR]

The paper investigates temporary layoffs in the Swedish labour market. Previous reports of few temporary layoffs are rejected. About 45 percent of unemployed people who found a job returned to a previous employer. As a stock measure, 10 percent of the unemployed are on temporary layoff. Using new job and recall as distinct exits in a competing risks model, one cannot reject a horizontal duration dependence for new jobs, while the recall hazard shows a strong, negative duration dependence. Clearer predictions of the effect of education on job probabilities are also found. Further, the results probably have implications for the interpretation of several policy parameters, including labour market programme outcomes. [ABSTRACT FROM AUTHOR]