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 (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.

scholarly journals A climatology of trade-wind cumulus cold pools and their link to mesoscale cloud organization

2021 ◽  
Vol 21 (21) ◽  
pp. 16609-16630
Author(s):  
Raphaela Vogel ◽  
Heike Konow ◽  
Hauke Schulz ◽  
Paquita Zuidema
Keyword(s):  
Cloud Cover ◽  
Large Fraction ◽  
Remote Sensing Data ◽  
Occurrence Frequency ◽  
Diel Cycle ◽  
Trade Wind ◽  
Cold Pool ◽  
Shallow Convection ◽  
Cold Pools ◽  
Early Afternoon

Abstract. We present a climatology of trade cumulus cold pools and their associated changes in surface weather, vertical velocity and cloudiness based on more than 10 years of in situ and remote sensing data from the Barbados Cloud Observatory. Cold pools are identified by abrupt drops in surface temperature, and the mesoscale organization pattern is classified by a neural network algorithm based on Geostationary Operational Environmental Satellite 16 (GOES-16) Advanced Baseline Imager (ABI) infrared images. We find cold pools to be ubiquitous in the winter trades – they are present about 7.8 % of the time and occur on 73 % of days. Cold pools with stronger temperature drops (ΔT) are associated with deeper clouds, stronger precipitation, downdrafts and humidity drops, stronger wind gusts and updrafts at the onset of their front, and larger cloud cover compared to weaker cold pools, which agrees well with the conceptual picture of cold pools. The rain duration in the front is the best predictor of ΔT and explains 36 % of its variability. The mesoscale organization pattern has a strong influence on the occurrence frequency of cold pools. Fish has the largest cold-pool fraction (12.8 % of the time), followed by Flowers and Gravel (9.9 % and 7.2 %) and lastly Sugar (1.6 %). Fish cold pools are also significantly stronger and longer-lasting compared to the other patterns, while Gravel cold pools are associated with significantly stronger updrafts and deeper cloud-top height maxima. The diel cycle of the occurrence frequency of Gravel, Flowers, and Fish can explain a large fraction of the diel cycle in the cold-pool occurrence as well as the pronounced extension of the diel cycle of shallow convection into the early afternoon by cold pools. Overall, we find cold-pool periods to be ∼ 90 % cloudier relative to the average winter trades. Also, the wake of cold pools is characterized by above-average cloudiness, suggesting that mesoscale arcs enclosing broad clear-sky areas are an exception. A better understanding of how cold pools interact with and shape their environment could therefore be valuable to understand cloud cover variability in the trades.

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>

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>

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 A climatology of trade-wind cumulus cold pools and their link to mesoscale cloud organization

2021 ◽  
Author(s):  
Raphaela Vogel ◽  
Heike Konow ◽  
Hauke Schulz ◽  
Paquita Zuidema
Keyword(s):  
Cloud Cover ◽  
Large Fraction ◽  
Remote Sensing Data ◽  
Occurrence Frequency ◽  
Trade Wind ◽  
Cold Pool ◽  
Shallow Convection ◽  
Daily Cycle ◽  
Cold Pools ◽  
Early Afternoon

Abstract. We present a climatology of trade cumulus cold pools and their associated meteorological perturbations based on more than ten years of in-situ and remote sensing data from the Barbados Cloud Observatory. Cold pools are identified by abrupt drops in surface temperature, and the mesoscale organization pattern is classified by a neural network algorithm based on GOES-16 ABI infrared images. We find cold pools to be ubiquitous in the winter trades – they are present about 7.8 % of the time and occur on 73 % of days. Cold pools with stronger temperature drops (∆T) are associated with deeper clouds, stronger precipitation, downdrafts and humidity drops, stronger wind gusts and updrafts at the onset of the front, and larger cloud cover compared to weaker cold pools. The downdraft strength together with the cold-pool front duration explains 50 % of the variability in ∆T. The mesoscale organization pattern has a strong influence on the occurrence frequency of cold pools. Fish has the largest cold-pool fraction (12.8 % of time), followed by Flowers and Gravel (9.9 % and 7.2 %), and lastly Sugar (1.6 %). Fish cold pools are also significantly stronger and longer-lasting compared to the other patterns, while Gravel cold pools are associated with significantly stronger updrafts and deeper cloud-top height maxima. The daily cycle of the occurrence frequency of Gravel, Flowers, and Fish can explain a large fraction of the daily cycle in the cold-pool occurrence, as well as the pronounced extension of the daily cycle of shallow convection into the early afternoon by cold pools. Overall, we find cold-pool periods to be ~90 % cloudier relative to the average winter trades. Also the wake of cold pools is characterized by above-average cloudiness, suggesting that mesoscale arcs enclosing broad clear-sky areas are an exception. A better understanding of how cold pools interact with and shape their environment could therefore be valuable to understand cloud cover variability in the trades.

scholarly journals Differences between Nonprecipitating Tropical and Trade Wind Marine Shallow Cumuli

2016 ◽  
Vol 144 (2) ◽  
pp. 681-701 ◽  
Author(s):  
Virendra P. Ghate ◽  
Mark A. Miller ◽  
Ping Zhu
Keyword(s):  
Surface Fluxes ◽  
Cloud Base ◽  
Trade Wind ◽  
Cumulus Clouds ◽  
Wind Speeds ◽  
Lower Cloud ◽  
Observational Site ◽  
Velocity Scale ◽  
Atmospheric Radiation Measurement ◽  
The Mean

Abstract Marine nonprecipitating cumulus topped boundary layers (CTBLs) observed in a tropical and in a trade wind region are contrasted based on their cloud macrophysical, dynamical, and radiative structures. Data from the Atmospheric Radiation Measurement (ARM) observational site previously operating at Manus Island, Papua New Guinea, and data collected during the deployment of ARM Mobile Facility at the island of Graciosa, in the Azores, were used in this study. The tropical marine CTBLs were deeper, had higher surface fluxes and boundary layer radiative cooling, but lower wind speeds compared to their trade wind counterparts. The radiative velocity scale was 50%–70% of the surface convective velocity scale at both locations, highlighting the prominent role played by radiation in maintaining turbulence in marine CTBLs. Despite greater thicknesses, the chord lengths of tropical cumuli were on average lower than those of trade wind cumuli, and as a result of lower cloud cover, the hourly averaged (cloudy and clear) liquid water paths of tropical cumuli were lower than the trade wind cumuli. At both locations ~70% of the cloudy profiles were updrafts, while the average amount of updrafts near cloud base stronger than 1 m s−1 was ~22% in tropical cumuli and ~12% in the trade wind cumuli. The mean in-cloud radar reflectivity within updrafts and mean updraft velocity was higher in tropical cumuli than the trade wind cumuli. Despite stronger vertical velocities and a higher number of strong updrafts, due to lower cloud fraction, the updraft mass flux was lower in the tropical cumuli compared to the trade wind cumuli. The observations suggest that the tropical and trade wind marine cumulus clouds differ significantly in their macrophysical and dynamical structures.

scholarly journals The Role of Shallow Convection over the Tibetan Plateau

2017 ◽  
Vol 30 (15) ◽  
pp. 5791-5803 ◽  
Author(s):  
Yunying Li ◽  
Minghua Zhang
Keyword(s):  
Tibetan Plateau ◽  
Large Scale ◽  
Diabatic Heating ◽  
Middle Atmosphere ◽  
Atmospheric Environment ◽  
Monsoon Circulation ◽  
The Tibetan Plateau ◽  
Shallow Convection ◽  
Sensitivity Experiment ◽  
Stratiform Clouds

Cumulus (Cu) from shallow convection is one of the dominant cloud types over the Tibetan Plateau (TP) in the summer according to CloudSat– CALIPSO observations. Its thermodynamic effects on the atmospheric environment and impacts on the large-scale atmospheric circulation are studied in this paper using the Community Atmospheric Model, version 5.3 (CAM5.3). It is found that the model can reasonably simulate the unique distribution of diabatic heating and Cu over the TP. Shallow convection provides the dominant diabatic heating and drying to the lower and middle atmosphere over the TP. A sensitivity experiment indicates that without Cu over the TP, large-scale condensation and stratiform clouds would increase dramatically, which induces enhanced low-level wind and moisture convergence toward the TP, resulting in significantly enhanced monsoon circulation with remote impact on the areas far beyond the TP. Cu therefore acts as a safety valve to modulate the atmospheric environment that prevents the formation of superclusters of stratiform clouds and precipitation over the TP.

Zooming through scales by the billion

2019 ◽  
Author(s):  
Shaun Lovejoy
Keyword(s):  
The Internet ◽  
Greek Mythology ◽  
Complex Objects ◽  
Cumulus Clouds ◽  
Warm Up ◽  
Weather And Climate ◽  
Extreme Cold ◽  
Cloud Patterns ◽  
Molecular Nature ◽  
Molecular Substructure

“The climate is what you expect, the weather is what you get”: The climate is a kind of average weather. But is it really? Those of us who have thirty years or more of recall are likely aware of subtle but systematic changes between today’s weather and the weather of their youth. I remember Montreal winters with much more snow and with longer spells of extreme cold. Did it really change? If so, was it only Montreal that changed? Or did all of Quebec change? Or did the whole planet warm up? And which is the real climate? Todays’ experience or that of the past? The key to answering these questions is the notion of scale, both in time (du­ration) and in space (size). Spatial variability is probably easier to grasp because structures of different sizes can be visualized readily (Fig. 1.1). In a puff of cigarette smoke, one can casually observe tiny wisps, whirls, and eddies. Looking out the window, we may see fluffy cumulus clouds with bumps and wiggles kilometers across. With a quick browse on the Internet, we can find satellite images of cloud patterns literally the size of the planet. Such visual inspection confirms that structures exist over a range of 10 billion or so: from 10,000 km down to less than 1 mm. At 0.1 mm, the atmosphere is like molasses; friction takes over and any whirls are quickly smoothed out. But even at this scale, matter is still “smooth.” To discern its granular, molecular nature, we would have to zoom in 1,000 times more to reach submicron scales. For weather and climate, the millimetric “dissipation scale” is thus a natural place to stop zooming, and the fact that it is still much larger than molecular scales indicates that, at this scale, we can safely discuss atmos­pheric properties without worrying about its molecular substructure. Clouds are highly complex objects. How should we deal with such apparent chaos? According to Greek mythology, at first there was only chaos; cosmos emerged later.

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