scholarly journals A CloudSat–CALIPSO View of Cloud and Precipitation Properties across Cold Fronts over the Global Oceans

2015 ◽  
Vol 28 (17) ◽  
pp. 6743-6762 ◽  
Author(s):  
Catherine M. Naud ◽  
Derek J. Posselt ◽  
Susan C. van den Heever
Keyword(s):  
Large Scale ◽  
Cold Front ◽  
Conveyor Belt ◽  
Low Level ◽  
Scale Parameters ◽  
Convective Clouds ◽  
Cold Fronts ◽  
Surface Front ◽  
High Level ◽  
The Impact

Abstract The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the postfrontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low-level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime postfrontal precipitation.

scholarly journals Organization of convective ascents in a warm conveyor belt

2020 ◽  
Author(s):  
Nicolas Blanchard ◽  
Florian Pantillon ◽  
Jean-Pierre Chaboureau ◽  
Julien Delanoë
Keyword(s):  
Large Scale ◽  
Doppler Radar ◽  
Heavy Precipitation ◽  
Conveyor Belt ◽  
Isolated Cells ◽  
Low Level ◽  
The North ◽  
Low Level Jet ◽  
Upper Level ◽  
The Impact

Abstract. Warm conveyor belts (WCBs) are warm, moist airstreams of extratropical cyclones leading to widespread clouds and heavy precipitation, where associated diabatic processes can influence midlatitude dynamics. Although WCBs are traditionally seen as continuous slantwise ascents, recent studies have emphasized the presence of embedded convection and the production of mesoscale bands of negative potential vorticity (PV), the impact of which on large-scale dynamics is still debated. Here, detailed cloud and wind measurements obtained with airborne Doppler radar provide unique information on the WCB of the Stalactite cyclone on 2 October 2016 during the North Atlantic Waveguide and Downstream Impact Experiment. The measurements are complemented by a convection-permitting simulation, enabling online Lagrangian trajectories and 3-D objects clustering. The simulation reproduces well the mesoscale structure of the cyclone shown by satellite infrared observations, while the location of trajectories rising by 150 hPa during a relatively short 12 h window matches the WCB region expected from high clouds. One third of those trajectories, categorized as fast ascents, further reach a 100 hPa (2h)−1 threshold during their ascent and follow the cyclonic flow mainly at lower levels. In agreement with radar observations, convective updrafts are found in the WCB and are characterized by moderate reflectivity values up to 20 dBz and vertical velocities above 0.3 m s−1. Updraft objects and fast ascents consistently show three main types of convection in the WCB: (i) frontal convection along the surface cold front and the western edge of the low-level jet; (ii) banded convection at about 2 km altitude along the eastern edge of the low-level jet; (iii) mid-level convection below the upper-level jet. Mesoscale PV dipoles with strong positive and negative values are located in the vicinity of convective ascents and appear to accelerate both low-level and upper-level jets. Both convective ascents and negative PV organize into structures with coherent shape, location and evolution, thus suggesting a dynamical linkage. The results show that convection embedded in WCBs occurs in a coherent and organized manner rather than as isolated cells.

scholarly journals Reply to “Comments on ‘A CloudSat–CALIPSO View of Cloud and Precipitation Properties across Cold Fronts over the Global Oceans’”

2018 ◽  
Vol 31 (7) ◽  
pp. 2969-2975 ◽  
Author(s):  
Catherine M. Naud ◽  
Derek J. Posselt ◽  
Susan C. van den Heever
Keyword(s):  
Large Scale ◽  
Cold Front ◽  
Numerical Models ◽  
Conveyor Belt ◽  
Sensitivity Study ◽  
Surface Precipitation ◽  
Cold Fronts ◽  
Scale Properties ◽  
Location Methods ◽  
Global Oceans

In Naud et al., a compositing method was utilized with CloudSat– CALIPSO observations to obtain mean transects of cloud vertical distribution and surface precipitation across cold fronts, and to examine their sensitivity to the large-scale properties of the parent extratropical cyclone. This reply demonstrates the value of compositing for evaluating numerical models, and presents additional results that address the issue of the sensitivity of the initial results to the frontal detection methodology and the potential misclassification of occlusions as cold fronts. Here a sensitivity study of the cold front composite transects of cloud cover to the input datasets or the method utilized to locate the cold fronts demonstrates that these composite transects are robust and only marginally sensitive to cold front location methods. The same conclusion is reached for the robustness of the contrast between Northern and Southern Hemisphere cloud transects. While occlusions cannot directly be flagged within the database at this point, comparisons of transects obtained for subsets of cyclones of different age indicate that the misclassification of occluded fronts as cold fronts does not explain the predominance of cloud and precipitation on the warm side of the cold fronts. The strong signal on the warm side might be better explained by a predominance of forward sloping cold fronts, or the presence of the warm conveyor belt.

scholarly journals Organization of convective ascents in a warm conveyor belt

2020 ◽  
Vol 1 (2) ◽  
pp. 617-634
Author(s):  
Nicolas Blanchard ◽  
Florian Pantillon ◽  
Jean-Pierre Chaboureau ◽  
Julien Delanoë
Keyword(s):  
Large Scale ◽  
Doppler Radar ◽  
Heavy Precipitation ◽  
Conveyor Belt ◽  
Isolated Cells ◽  
Low Level ◽  
The North ◽  
Low Level Jet ◽  
Upper Level Jet ◽  
The Impact

Abstract. Warm conveyor belts (WCBs) are warm, moist airstreams of extratropical cyclones leading to widespread clouds and heavy precipitation, where associated diabatic processes can influence midlatitude dynamics. Although WCBs are traditionally seen as continuous slantwise ascents, recent studies have emphasized the presence of embedded convection, the impact of which on large-scale dynamics is still debated. Here, detailed cloud and wind measurements obtained with airborne Doppler radar provide unique information on the WCB of the Stalactite cyclone on 2 October 2016 during the North Atlantic Waveguide and Downstream Impact Experiment. The measurements are complemented by a convection-permitting simulation, enabling online Lagrangian trajectories and 3-D objects clustering. Trajectories rising by 150 hPa during a relatively short 12 h window are identified as ascents and examined in the WCB region. One-third take an anticyclonic turn at upper levels, while two-thirds follow the cyclonic flow at lower levels. Identified trajectories that reach a 100 hPa (2 h)−1 threshold are further categorized as fast ascents. They represent one-third of the ascents and are located at lower levels mainly. Both radar observations and simulation reveal the presence of convective updrafts in the WCB region, which are characterized by moderate reflectivity values up to 20 dBZ. Fast ascents and updraft objects with vertical velocities above 0.3 m s−1 consistently show three main types of convection in the WCB region: (i) frontal convection along the surface cold front and the western edge of the low-level jet, (ii) banded convection at about 2 km altitude along the eastern edge of the low-level jet, and (iii) mid-level convection below the upper-level jet. Frontal and banded convection result in shallow ascents, while mid-level convection contributes to the anticyclonic WCB outflow. The results emphasize that convection embedded in WCBs occurs in a coherent and organized manner rather than as isolated cells.

scholarly journals The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis

2015 ◽  
Vol 8 (1) ◽  
pp. 421-434 ◽  
Author(s):  
M. P. Jensen ◽  
T. Toto ◽  
D. Troyan ◽  
P. E. Ciesielski ◽  
D. Holdridge ◽  
...  
Keyword(s):  
Large Scale ◽  
Scale Model ◽  
Data Sets ◽  
Central Plains ◽  
Data Set ◽  
Convective Systems ◽  
Convective Clouds ◽  
Quality Checks ◽  
Network Operations ◽  
The Impact

Abstract. The Midlatitude Continental Convective Clouds Experiment (MC3E) took place during the spring of 2011 centered in north-central Oklahoma, USA. The main goal of this field campaign was to capture the dynamical and microphysical characteristics of precipitating convective systems in the US Central Plains. A major component of the campaign was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state with the intent of deriving model forcing data sets. Over the course of the 46-day MC3E campaign, a total of 1362 radiosondes were launched from the enhanced sonde network. This manuscript provides details on the instrumentation used as part of the sounding array, the data processing activities including quality checks and humidity bias corrections and an analysis of the impacts of bias correction and algorithm assumptions on the determination of convective levels and indices. It is found that corrections for known radiosonde humidity biases and assumptions regarding the characteristics of the surface convective parcel result in significant differences in the derived values of convective levels and indices in many soundings. In addition, the impact of including the humidity corrections and quality controls on the thermodynamic profiles that are used in the derivation of a large-scale model forcing data set are investigated. The results show a significant impact on the derived large-scale vertical velocity field illustrating the importance of addressing these humidity biases.

scholarly journals A Two-Level Sound Classification Platform for Environmental Monitoring

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Stelios A. Mitilineos ◽  
Stelios M. Potirakis ◽  
Nicolas-Alexander Tatlas ◽  
Maria Rangoussi
Keyword(s):  
Cultural Heritage ◽  
Organizational Innovation ◽  
Gaussian Mixture ◽  
Low Level ◽  
Heritage Sites ◽  
Acoustic Sensor Networks ◽  
Preventive Actions ◽  
Integrated Platform ◽  
High Level ◽  
The Impact

STORM is an ongoing European research project that aims at developing an integrated platform for monitoring, protecting, and managing cultural heritage sites through technical and organizational innovation. Part of the scheduled preventive actions for the protection of cultural heritage is the development of wireless acoustic sensor networks (WASNs) that will be used for assessing the impact of human-generated activities as well as for monitoring potentially hazardous environmental phenomena. Collected sound samples will be forwarded to a central server where they will be automatically classified in a hierarchical manner; anthropogenic and environmental activity will be monitored, and stakeholders will be alarmed in the case of potential malevolent behavior or natural phenomena like excess rainfall, fire, gale, high tides, and waves. Herein, we present an integrated platform that includes sound sample denoising using wavelets, feature extraction from sound samples, Gaussian mixture modeling of these features, and a powerful two-layer neural network for automatic classification. We contribute to previous work by extending the proposed classification platform to perform low-level classification too, i.e., classify sounds to further subclasses that include airplane, car, and pistol sounds for the anthropogenic sound class; bird, dog, and snake sounds for the biophysical sound class; and fire, waterfall, and gale for the geophysical sound class. Classification results exhibit outstanding classification accuracy in both high-level and low-level classification thus demonstrating the feasibility of the proposed approach.

scholarly journals The effects of grouping types on promoting critical thinking in EFL collaborative writing

2020 ◽  
Vol 9 (2) ◽  
pp. 108-120
Author(s):  
Nguyen Thi Minh Tram ◽  
Bui Thi Thuc Quyen
Keyword(s):  
Critical Thinking ◽  
Collaborative Learning ◽  
Tertiary Education ◽  
Collaborative Writing ◽  
Homogeneous Groups ◽  
Learning And Teaching ◽  
Low Level ◽  
Heterogeneous Groups ◽  
High Level ◽  
The Impact

Nurturing critical thinking (CT) has been acknowledged as a core objective of tertiary education, and drawn attention from academia of teaching English as a Foreign Language (EFL), particularly in EFL argumentative writing. It has been claimed that collaborative learning which stimulates the active exchange of ideas within small groups not only increases interest among the participants but also promotes critical thinking. One of the important aspects of learning and teaching through collaboration is the group composition or grouping “who with whom”. The present study was an attempt to investigate the impact of homogeneous and heterogeneous groupings on critical thinking in collaborative writing. Having been required to write an argumentative essay as a pre-test, 75 participants, who were categorized by their prior critical thinking levels, were assigned into three group types: heterogeneous, homogeneous high and homogeneous low groups. As a consequence, four types of students were considered their improvement before and after the experiment: high-level students in heterogeneous groups, lowlevel students in heterogeneous groups, high-level students in homogeneous groups, low-level students in homogeneous groups. The results demonstrated that learners improved their critical thinking level through collaborative writing, whether working with stronger or weaker peers. However, heterogeneous grouping showed superiority over homogeneous grouping at the low level. The results revealed that cooperative learning could be especially beneficial for low students. It is hoped that the findings of the present study will give teachers deep insights into group compositions in collaborative learning courses, and will help them make better group experiences for students.

scholarly journals Effect of Interventional Programme on Enhancing Empowerment Status through Decision Making Skills of Tribal Working Women in Utnoor Mandal Adilabad District, India

2021 ◽  
pp. 41-45
Author(s):  
N. Sandhya Rani ◽  
M. Sarada Devi
Keyword(s):  
Decision Making ◽  
Working Women ◽  
Total Sample ◽  
Average Level ◽  
Sample Population ◽  
Test Results ◽  
Low Level ◽  
Tribal Women ◽  
High Level ◽  
The Impact

Empowerment of tribal women is one of the central issues in the process of development all over the world. Empowerment is the process that allows one to gain the knowledge and attitude needed to cope with the changing world and the circumstances in which one lives [1]. Women empowerment is a process in which women gain greater share of control over material, human and intellectual resources as well as control over decision-making in their home, community, society and nation. Given the need to analyze the empowerment status of tribal women, the present study aimed to enhance the empowerment status through enhancing decision-making skills of tribal working women in India. The specific objective is to study the impact of intervention on enhancing status of empowerment through decision-making skills of tribal working women in Utnoor Mandal Adilabad district. The total sample population for the study was 50 tribal working women, and data was analyzed using a paired t test. Results revealed that at pretest, majority of the women were at average level of decision-making skills (78%), 12% were at low level and only 10% were at high level. After the intervention, post test results revealed that 74% of the women were high in decision making skills and remaining 26% were at average level. Interestingly, none of the respondents had low level of life skills. Thus, intervention found to be effective among women respondents to develop and enhance their empowerment status through decision-making skills.

scholarly journals Coupling of Precipitation and Cloud Structures in Oceanic Extratropical Cyclones to Large-Scale Moisture Flux Convergence

2018 ◽  
Vol 31 (23) ◽  
pp. 9565-9584 ◽  
Author(s):  
Sun Wong ◽  
Catherine M. Naud ◽  
Brian H. Kahn ◽  
Longtao Wu ◽  
Eric J. Fetzer
Keyword(s):  
Large Scale ◽  
Moisture Flux ◽  
Extratropical Cyclones ◽  
Flux Divergence ◽  
Moisture Flux Convergence ◽  
Convective Clouds ◽  
Moisture Advection ◽  
Deep Convective Clouds ◽  
Stratiform Clouds ◽  
High Level

Precipitation (from TMPA) and cloud structures (from MODIS) in extratropical cyclones (ETCs) are modulated by phases of large-scale moisture flux convergence (from MERRA-2) in the sectors of ETCs, which are studied in a new coordinate system with directions of both surface warm fronts (WFs) and surface cold fronts (CFs) fixed. The phase of moisture flux convergence is described by moisture dynamical convergence Qcnvg and moisture advection Qadvt. Precipitation and occurrence frequencies of deep convective clouds are sensitive to changes in Qcnvg, while moisture tendency is sensitive to changes in Qadvt. Increasing Qcnvg and Qadvt during the advance of the WF is associated with increasing occurrences of both deep convective and high-level stratiform clouds. A rapid decrease in Qadvt with a relatively steady Qcnvg during the advance of the CF is associated with high-level cloud distribution weighting toward deep convective clouds. Behind the CF (cold sector or area with polar air intrusion), the moisture flux is divergent with abundant low- and midlevel clouds. From deepening to decaying stages, the pre-WF and WF sectors experience high-level clouds shifting to more convective and less stratiform because of decreasing Qadvt with relatively steady Qcnvg, and the CF experiences shifting from high-level to midlevel clouds. Sectors of moisture flux divergence are less influenced by cyclone evolution. Surface evaporation is the largest in the cold sector and the CF during the deepening stage. Deepening cyclones are more efficient in poleward transport of water vapor.

scholarly journals Computational Modeling of the Human Microbiome

2020 ◽  
Vol 8 (2) ◽  
pp. 197
Author(s):  
Shomeek Chowdhury ◽  
Stephen S. Fong
Keyword(s):  
Computational Modeling ◽  
Human Health ◽  
Large Scale ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Microbial Composition ◽  
Site Specific ◽  
Microbiome Research ◽  
High Level ◽  
The Impact

The impact of microorganisms on human health has long been acknowledged and studied, but recent advances in research methodologies have enabled a new systems-level perspective on the collections of microorganisms associated with humans, the human microbiome. Large-scale collaborative efforts such as the NIH Human Microbiome Project have sought to kick-start research on the human microbiome by providing foundational information on microbial composition based upon specific sites across the human body. Here, we focus on the four main anatomical sites of the human microbiome: gut, oral, skin, and vaginal, and provide information on site-specific background, experimental data, and computational modeling. Each of the site-specific microbiomes has unique organisms and phenomena associated with them; there are also high-level commonalities. By providing an overview of different human microbiome sites, we hope to provide a perspective where detailed, site-specific research is needed to understand causal phenomena that impact human health, but there is equally a need for more generalized methodology improvements that would benefit all human microbiome research.

scholarly journals A High-Density Crowd Counting Method Based on Convolutional Feature Fusion

2018 ◽  
Vol 8 (12) ◽  
pp. 2367 ◽  
Author(s):  
Hongling Luo ◽  
Jun Sang ◽  
Weiqun Wu ◽  
Hong Xiang ◽  
Zhili Xiang ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Large Scale ◽  
Feature Fusion ◽  
High Density ◽  
Counting Problem ◽  
Crowd Counting ◽  
Low Level ◽  
Density Map ◽  
High Level

In recent years, the trampling events due to overcrowding have occurred frequently, which leads to the demand for crowd counting under a high-density environment. At present, there are few studies on monitoring crowds in a large-scale crowded environment, while there exists technology drawbacks and a lack of mature systems. Aiming to solve the crowd counting problem with high-density under complex environments, a feature fusion-based deep convolutional neural network method FF-CNN (Feature Fusion of Convolutional Neural Network) was proposed in this paper. The proposed FF-CNN mapped the crowd image to its crowd density map, and then obtained the head count by integration. The geometry adaptive kernels were adopted to generate high-quality density maps which were used as ground truths for network training. The deconvolution technique was used to achieve the fusion of high-level and low-level features to get richer features, and two loss functions, i.e., density map loss and absolute count loss, were used for joint optimization. In order to increase the sample diversity, the original images were cropped with a random cropping method for each iteration. The experimental results of FF-CNN on the ShanghaiTech public dataset showed that the fusion of low-level and high-level features can extract richer features to improve the precision of density map estimation, and further improve the accuracy of crowd counting.

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