Covariability of trade-wind cloudiness and environmental conditions in large-eddy simulations and observations

2021 ◽  
Author(s):  
Hauke Schulz ◽  
Ryan Eastman ◽  
Bjorn Stevens
Keyword(s):  
Environmental Conditions ◽  
Large Eddy Simulations ◽  
Trade Wind ◽  
Shallow Convection ◽  
First Case ◽  
Large Eddy ◽  
Cloud Radiative Effects ◽  
Weak Winds ◽  
Cloud Patterns ◽  
Lifting Condensation Level

<p>Shallow convection in the downwind trades occurs in form of different cloud patterns with characteristic cloud arrangements at the meso-scale. The four most dominant patterns were previously named Sugar, Gravel, Flowers and Fish and have been identified to be associated with different net cloud radiative effects.</p><p>By using long-term observations, we reveal that these differences can be mainly attributed to the stratiform cloud component that varies in extent across the patterns as opposed to the cloudiness at the lifting condensation level that is fairly constant independent of the patterns.</p><p>The observations reveal further, that each pattern is associated with a different environmental condition whose characteristics originate not soley from within the trades. Sugar air-masses are characterized by weak winds and of tropical origin, while Fish are driven by convergence lines originating from synoptical disturbances. Gravel and Flowers are most native to the trades, but distinguish themselves with slightly stronger winds and stronger subsidence in the first case and greater stability in the latter.</p><p>How well this covariability of cloudiness and environmental conditions is represented in simulations is important to project the occurrence of the patterns in a warmer climate and evaluated by realistic large-eddy simulations of the recent EUREC4A field campaign.</p>

Aerosol effects on shallow cumulus cloud fields in idealised and realistic simulations

2020 ◽  
Author(s):  
George Spill ◽  
Philip Stier ◽  
Paul Field ◽  
Guy Dagan
Keyword(s):  
Large Scale ◽  
Trade Wind ◽  
Quasi Equilibrium ◽  
Cumulus Cloud ◽  
Shallow Convection ◽  
Shallow Cumulus ◽  
Synoptic Conditions ◽  
Large Eddy ◽  
Transient Forcing ◽  
Periodic Domains

<p>Shallow cumulus clouds interact with their environment in myriad significant ways, and yet their behavour is still poorly understood, and is responsible for much uncertainty in climate models. Improving our understanding of these clouds is therefore an important part of improving our understanding of the climate system as a whole.</p><p>Modelling studies of shallow convection have traditionally made use of highly idealised simulations using large-eddy models, which allow for high resolution, detailed simulations. However, this idealised nature, with periodic boundaries and constant forcing, and the quasi-equilibrium cloud fields produced, means that they do not capture the effect of transient forcing and conditions found in the real atmosphere, which contains shallow cumulus cloud fields unlikely to be in equilibrium.<span> </span></p><p>Simulations with more realistic nested domains and forcings have previously been shown to have significant persistent responses differently to aerosol perturbations, in contrast to many large eddy simulations in which perturbed runs tend to reach a similar quasi-equilibrium.<span> </span></p><p>Here, we further this investigation by using a single model to present a comparison of familiar idealised simulations of trade wind cumuli in periodic domains, and simulations with a nested domain, whose boundary conditions are provided by a global driving model, able to simulate transient synoptic conditions.<span> </span></p><p>The simulations are carried out using the Met Office Unified Model (UM), and are based on a case study from the Rain In Cumulus over the Ocean (RICO) field campaign. Large domains of 500km are chosen in order to capture large scale cloud field behaviour. A double-moment interactive microphysics scheme is used, along with prescribed aerosol profiles based on RICO observations, which are then perturbed.</p><p>We find that the choice between realistic nested domains with transient forcing and idealised periodic domains with constant forcing does indeed affect the nature of the response to aerosol perturbations, with the realistic simulations displaying much larger persistent changes in domain mean fields such as liquid water path and precipitation rate.<span> </span></p>

scholarly journals Large-eddy simulation of organized precipitating trade wind cumulus clouds

2013 ◽  
Vol 13 (1) ◽  
pp. 1855-1889 ◽  
Author(s):  
A. Seifert ◽  
T. Heus
Keyword(s):  
Large Eddy Simulation ◽  
Trade Wind ◽  
Shallow Convection ◽  
Cumulus Clouds ◽  
Eddy Simulation ◽  
Cold Pools ◽  
Cloud Clusters ◽  
Large Eddy ◽  
Sensitivity Studies ◽  
The Individual

Abstract. Trade wind cumulus clouds often organize in along-wind cloud streets and across-wind mesoscale arcs. We present a benchmark large-eddy simulation which resolves the individual clouds as well as the mesoscale organization on scales of O(10 km). Different methods to quantify organization of cloud fields are applied and discussed. Using perturbed physics large-eddy simulations experiments the processes leading to the formation of cloud clusters and the mesoscale arcs are revealed. We find that both cold pools as well as the sub-cloud layer moisture field are crucial to understand the organization of precipitating shallow convection. Further sensitivity studies show that microphysical assumptions can have a pronounced impact on the onset of cloud organization.

Dependence of mesoscale patterns of Trade-wind clouds on environmental conditions: an investigation using satellite and in-situ observations

2020 ◽  
Author(s):  
Sandrine Bony ◽  
Hauke Schulz ◽  
Jessica Vial ◽  
Bjorn Stevens ◽  
Keyword(s):  
Meteorological Data ◽  
Surface Wind ◽  
Cloud Amount ◽  
Surface Wind Speed ◽  
Trade Wind ◽  
Shallow Convection ◽  
Western Atlantic ◽  
Near Surface ◽  
Cloud Patterns

<p>Trade-wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as Flowers, Fish, Gravel and Sugar. By using 19 years of satellite and meteorological data, we show that these four patterns can be identified objectively from satellite observations, and that on daily and interannual timescales, the near-surface wind speed and the strength of the lower-tropospheric stability discriminate the occurrence of the different organization patterns. Moreover, we point out a tight relationship between cloud patterns, low-level cloud amount and cloud-radiative effects. The EUREC4A field study taking place upwind of Barbados in Jan-Feb 2020 offers an opportunity to investigate these relationships from an in-situ and process-oriented perspective. Preliminary results will be discussed.</p>

Evolution of Organized Shallow Convection

2020 ◽  
Author(s):  
Hauke Schulz ◽  
Ryan Eastman ◽  
Bjorn Stevens
Keyword(s):  
Large Fraction ◽  
Satellite Image ◽  
Atmospheric Environment ◽  
Trade Wind ◽  
Shallow Convection ◽  
Cumulus Clouds ◽  
Back Trajectories ◽  
Wind Region ◽  
Future Warming ◽  
Cloud Patterns

<p>Uncertainty in the response of clouds to warming is the leading source of uncertainty in projections of future warming. To a large fraction the frequently occurring shallow cumulus clouds in the trade wind region contribute to this uncertainty. In symbiosis with thin clouds of stratiform extent they often create various cloud patterns.<br><br>We introduce a neural network that is able to detect the mesoscale organization from GOES16 and MODIS satellite imagery in order to put eight years of ground-based measurements of the Barbados Cloud Observatory into the context of mesoscale organization. With this combination of long-term ground-based measurements from the trade-wind region and satellite image classifications, we overcome the common resolution limitations of satellite derived cloud products of shallow cumuli and are able to present the characteristics of shallow convection depending on the mesoscale organization with great detail.<br><br>By using back-trajectories and EUREC4A field campaign data, we show that differences in the atmospheric environment are not only present at the time of pronounced mesoscale organization, but are already distinguishable days ahead in LTS, wind speed and SST.</p>

scholarly journals Large-eddy simulation of organized precipitating trade wind cumulus clouds

2013 ◽  
Vol 13 (11) ◽  
pp. 5631-5645 ◽  
Author(s):  
A. Seifert ◽  
T. Heus
Keyword(s):  
Large Eddy Simulation ◽  
Trade Wind ◽  
Shallow Convection ◽  
Cumulus Clouds ◽  
Eddy Simulation ◽  
Cold Pools ◽  
Cloud Clusters ◽  
Large Eddy ◽  
Sensitivity Studies ◽  
The Individual

Abstract. Trade wind cumulus clouds often organize in along-wind cloud streets and across-wind mesoscale arcs. We present a benchmark large-eddy simulation which resolves the individual clouds as well as the mesoscale organization on scales of O(10 km). Different methods to quantify organization of cloud fields are applied and discussed. Using perturbed physics large-eddy simulation experiments, the processes leading to the formation of cloud clusters and the mesoscale arcs are revealed. We find that both cold pools as well as the sub-cloud layer moisture field are crucial to understand the organization of precipitating shallow convection. Further sensitivity studies show that microphysical assumptions can have a pronounced impact on the onset of cloud organization.

scholarly journals Large-Eddy Simulations of Trade Wind Cumuli Using Particle-Based Microphysics with Monte Carlo Coalescence

2013 ◽  
Vol 70 (9) ◽  
pp. 2768-2777 ◽  
Author(s):  
Sylwester Arabas ◽  
Shin-ichiro Shima
Keyword(s):  
Monte Carlo ◽  
Droplet Size ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Large Eddy Simulations ◽  
Trade Wind ◽  
Type Model ◽  
Size Spectrum ◽  
Large Eddy ◽  
Condensational Growth

Abstract A series of simulations employing the superdroplet method (SDM) for representing aerosol, cloud, and rain microphysics in large-eddy simulations (LES) is discussed. The particle-based formulation treats all particles in the same way, subjecting them to condensational growth and evaporation, transport of the particles by the flow, gravitational settling, and collisional growth. SDM features a Monte Carlo–type numerical scheme for representing the collision and coalescence process. All processes combined cover representation of cloud condensation nuclei (CCN) activation, drizzle formation by autoconversion, accretion of cloud droplets, self-collection of raindrops, and precipitation, including aerosol wet deposition. The model setup used in the study is based on observations from the Rain in Cumulus over the Ocean (RICO) field project. Cloud and rain droplet size spectra obtained in the simulations are discussed in context of previously published analyses of aircraft observations carried out during RICO. The analysis covers height-resolved statistics of simulated cloud microphysical parameters such as droplet number concentration, effective radius, and parameters describing the width of the cloud droplet size spectrum. A reasonable agreement with measurements is found for several of the discussed parameters. The sensitivity of the results to the grid resolution of the LES, as well as to the sampling density of the probabilistic Monte Carlo–type model, is explored.

scholarly journals Turbulence effects on warm-rain formation in precipitating shallow convection revisited

2016 ◽  
Vol 16 (18) ◽  
pp. 12127-12141 ◽  
Author(s):  
Axel Seifert ◽  
Ryo Onishi
Keyword(s):  
Isotropic Turbulence ◽  
Large Eddy Simulations ◽  
Small Scale ◽  
Shallow Convection ◽  
Surface Precipitation ◽  
Considerable Uncertainty ◽  
Warm Rain ◽  
Large Eddy ◽  
Turbulence Effects ◽  
Rain Formation

Abstract. Two different collection kernels which include turbulence effects on the collision rate of liquid droplets are used as a basis to develop a parameterization of the warm-rain processes autoconversion, accretion, and self-collection. The new parameterization is tested and validated with the help of a 1-D bin microphysics model. Large-eddy simulations of the rain formation in shallow cumulus clouds confirm previous results that turbulence effects can significantly enhance the development of rainwater in clouds and the occurrence and amount of surface precipitation. The detailed behavior differs significantly for the two turbulence models, revealing a considerable uncertainty in our understanding of such effects. In addition, the large-eddy simulations show a pronounced sensitivity to grid resolution, which suggests that besides the effect of sub-grid small-scale isotropic turbulence which is parameterized as part of the collection kernel also the larger turbulent eddies play an important role for the formation of rain in shallow clouds.

scholarly journals Extracting Microphysical Impacts in Large-Eddy Simulations of Shallow Convection

2014 ◽  
Vol 71 (12) ◽  
pp. 4493-4499 ◽  
Author(s):  
Wojciech W. Grabowski
Keyword(s):  
Traditional Approach ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Natural Variability ◽  
Large Eddy Simulations ◽  
Shallow Convection ◽  
Liquid Water Path ◽  
Large Eddy ◽  
The Mean ◽  
The Impact

Abstract A simple methodology is proposed to extract impacts of cloud microphysics on macrophysical cloud-field properties in large-eddy simulations of shallow convection. These impacts are typically difficult to assess because of natural variability of the simulated cloud field. The idea is to use two sets of thermodynamic variables driven by different microphysical schemes or by a single scheme with different parameters as applied here. The first set is coupled to the dynamics as in the standard model, and the second set is applied diagnostically—that is, driven by the flow but without the feedback on the flow dynamics. Having the two schemes operating in the same flow pattern allows for extracting the impact with high confidence. For illustration, the method is applied to simulations of precipitating shallow convection applying a simple bulk representation of warm-rain processes. Because of natural variability, the traditional approach provides an uncertain estimate of the impact of cloud droplet concentration on the mean cloud-field rainfall even with an ensemble of simulations. In contrast, the impact is well constrained while applying the new methodology. The method can even detect minuscule changes of the mean cloud cover and liquid water path despite their large temporal fluctuations and different evolutions within the ensemble.

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