The impact of variations of low-level structure associated with surface drag on intensification of simulated tornadoes

2021 ◽  
Author(s):  
Qin Jiang ◽  
Daniel Dawson
Author(s):  
Jaroslav Tir ◽  
Johannes Karreth

Civil wars are one of the most pressing problems facing the world. Common approaches such as mediation, intervention, and peacekeeping have produced some results in managing ongoing civil wars, but they fall short in preventing civil wars in the first place. This book argues for considering civil wars from a developmental perspective to identify steps to assure that nascent, low-level armed conflicts do not escalate to full-scale civil wars. We show that highly structured intergovernmental organizations (IGOs, e.g. the World Bank or IMF) are particularly well positioned to engage in civil war prevention. Such organizations have both an enduring self-interest in member-state peace and stability and potent (economic) tools to incentivize peaceful conflict resolution. The book advances the hypothesis that countries that belong to a larger number of highly structured IGOs face a significantly lower risk that emerging low-level armed conflicts on their territories will escalate to full-scale civil wars. Systematic analyses of over 260 low-level armed conflicts that have occurred around the globe since World War II provide consistent and robust support for this hypothesis. The impact of a greater number of memberships in highly structured IGOs is substantial, cutting the risk of escalation by over one-half. Case evidence from Indonesia’s East Timor conflict, Ivory Coast’s post-2010 election crisis, and from the early stages of the conflict in Syria in 2011 provide additional evidence that memberships in highly structured IGOs are indeed key to understanding why some low-level armed conflicts escalate to civil wars and others do not.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Muhammad Ramzan ◽  
Jae Dong Chung ◽  
Seifedine Kadry ◽  
Yu-Ming Chu ◽  
Muhammad Akhtar

Abstract A mathematical model is envisioned to discourse the impact of Thompson and Troian slip boundary in the carbon nanotubes suspended nanofluid flow near a stagnation point along an expanding/contracting surface. The water is considered as a base fluid and both types of carbon nanotubes i.e., single-wall (SWCNTs) and multi-wall (MWCNTs) are considered. The flow is taken in a Dacry-Forchheimer porous media amalgamated with quartic autocatalysis chemical reaction. Additional impacts added to the novelty of the mathematical model are the heat generation/absorption and buoyancy effect. The dimensionless variables led the envisaged mathematical model to a physical problem. The numerical solution is then found by engaging MATLAB built-in bvp4c function for non-dimensional velocity, temperature, and homogeneous-heterogeneous reactions. The validation of the proposed mathematical model is ascertained by comparing it with a published article in limiting case. An excellent consensus is accomplished in this regard. The behavior of numerous dimensionless flow variables including solid volume fraction, inertia coefficient, velocity ratio parameter, porosity parameter, slip velocity parameter, magnetic parameter, Schmidt number, and strength of homogeneous/heterogeneous reaction parameters are portrayed via graphical illustrations. Computational iterations for surface drag force are tabulated to analyze the impacts at the stretched surface. It is witnessed that the slip velocity parameter enhances the fluid stream velocity and diminishes the surface drag force. Furthermore, the concentration of the nanofluid flow is augmented for higher estimates of quartic autocatalysis chemical.


2020 ◽  
Vol 20 (8) ◽  
pp. 5019-5033 ◽  
Author(s):  
Yuning Xie ◽  
Gehui Wang ◽  
Xinpei Wang ◽  
Jianmin Chen ◽  
Yubao Chen ◽  
...  

Abstract. The Chinese government has exerted strict emission controls to mitigate air pollution since 2013, which has resulted in significant decreases in the concentrations of air pollutants such as SO2. Strict pollution control actions also reduced the average PM2.5 concentration to the low level of 39.7 µg m−3 in urban Beijing during the winter of 2017. To investigate the impact of such changes on the physiochemical properties of atmospheric aerosols in China, we conducted a comprehensive observation focusing on PM2.5 in Beijing during the winter of 2017. Compared with the historical record (2014–2017), SO2 decreased to the low level of 3.2 ppbv in the winter of 2017, but the NO2 level was still high (21.4 ppbv in the winter of 2017). Accordingly, the contribution of nitrate (23.0 µg m−3) to PM2.5 far exceeded that of sulfate (13.1 µg m−3) during the pollution episodes, resulting in a significant increase in the nitrate-to-sulfate molar ratio. The thermodynamic model (ISORROPIA II) calculation results showed that during the PM2.5 pollution episodes particle pH increased from 4.4 (moderate acidic) to 5.4 (more neutralized) when the molar ratio of nitrate to sulfate increased from 1 to 5, indicating that aerosols were more neutralized as the nitrate content elevated. Controlled variable tests showed that the pH elevation should be attributed to nitrate fraction increase other than crustal ion and ammonia concentration increases. Based on the results of sensitivity tests, future prediction for the particle acidity change was discussed. We found that nitrate-rich particles in Beijing at low and moderate humid conditions (RH: 20 %–50 %) can absorb twice the amount of water that sulfate-rich particles can, and the nitrate and ammonia with higher levels have synergetic effects, rapidly elevating particle pH to merely neutral (above 5.6). As moderate haze events might occur more frequently under abundant ammonia and nitrate-dominated PM2.5 conditions, the major chemical processes during haze events and the control target should be re-evaluated to obtain the most effective control strategy.


2015 ◽  
Vol 28 (17) ◽  
pp. 6743-6762 ◽  
Author(s):  
Catherine M. Naud ◽  
Derek J. Posselt ◽  
Susan C. van den Heever

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.


2012 ◽  
Vol 140 (10) ◽  
pp. 3300-3326 ◽  
Author(s):  
Xiaoming Sun ◽  
Ana P. Barros

Abstract The influence of large-scale forcing on the high-resolution simulation of Tropical Storm Ivan (2004) in the southern Appalachians was investigated using the Weather Research and Forecasting model (WRF). Two forcing datasets were employed: the North American Regional Reanalysis (NARR; 32 km × 32 km) and the NCEP Final Operational Global Analysis (NCEP FNL; 1° × 1°). Simulated fields were evaluated against rain gauge, radar, and satellite data; sounding observations; and the best track from the National Hurricane Center (NHC). Overall, the NCEP FNL forced simulation (WRF_FNL) captures storm structure and evolution more accurately than the NARR forced simulation (WRF_NARR), benefiting from the hurricane initialization scheme in the NCEP FNL. Further, the performance of WRF_NARR is also negatively affected by a previously documented low-level warm bias in NARR. These factors lead to excessive precipitation in the Piedmont region, delayed rainfall in Alabama, as well as spatially displaced and unrealistically extreme rainbands during its passage over the southern Appalachians. Spatial filtering of the simulated precipitation fields confirms that the storm characteristics inherited from the forcing are critical to capture the storm’s impact at local places. Compared with the NHC observations, the storm is weaker in both NARR and NCEP FNL (up to Δp ~ 5 hPa), yet it is persistently deeper in all WRF simulations forced by either dataset. The surface wind fields are largely overestimated. This is attributed to the underestimation of surface roughness length over land, leading to underestimation of surface drag, reducing low-level convergence, and weakening the dissipation of the simulated cyclone.


Author(s):  
Luke J. LeBel ◽  
Brian H. Tang ◽  
Ross A. Lazear

AbstractThe complex terrain at the intersection of the Mohawk and Hudson valleys of New York has an impact on the development and evolution of severe convection in the region. Specifically, previous research has concluded that terrain-channeled flow in the Mohawk and Hudson valleys likely contributes to increased low-level wind shear and instability in the valleys during severe weather events such as the historic 31 May 1998 event that produced a strong (F3) tornado in Mechanicville, New York.The goal of this study is to further examine the impact of terrain channeling on severe convection by analyzing a high-resolution WRF model simulation of the 31 May 1998 event. Results from the simulation suggest that terrain-channeled flow resulted in the localized formation of an enhanced low-level moisture gradient, resembling a dryline, at the intersection of the Mohawk and Hudson valleys. East of this boundary, the environment was characterized by stronger low-level wind shear and greater low-level moisture and instability, increasing tornadogenesis potential. A simulated supercell intensified after crossing the boundary, as the larger instability and streamwise vorticity of the low-level inflow was ingested into the supercell updraft. These results suggest that terrain can have a key role in producing mesoscale inhomogeneities that impact the evolution of severe convection. Recognition of these terrain-induced boundaries may help in anticipating where the risk of severe weather may be locally enhanced.


2020 ◽  
Vol 9 (4) ◽  
pp. 336-345
Author(s):  
Silpi Hazarika ◽  
Sahin Ahmed

The impact of heat transfer in micropolar fluid may be developed due to its various promising applications in engineering, bio-medical sciences, geo-thermal progression, spherical storage tanks, nuclear power plants, automobile sectors etc. Motivated by such significance, the current study is to expound the influences of micropolar Casson fluid flow over a solid sphere with Brownian motion, thermophoretic force and buoyancy force surrounded by porous medium. The adopted model having complex PDE’s are reduced to dimensionless ODE’s by utilizing proper similarity solutions. A numerical approach have been carried out for velocity, micro rotation, temperature and concentration, the solutions are procured by Matlab Bvp4c code and plotted graphs for diverse involved parameters. An adequate result is acquired by an assessment with earlier available work. The effects of key parameters on surface drag coefficient, surface thermal flux and particles concentration flux are examined and displayed in tabular form. Grash of number raises the profiles of thermal flux and concentration flux where the buoyancy force is more dominant. Further, the obtained results indicate that the angular velocity is elevated near the surface of the sphere, and they behaves asymptotically far away from the surface due to the effect of micropolar parameter. Moreover, temperature and molar species concentration are enriched with upper values of micropolar factor. It is perceived that, augmented values of Casson parameter amplifies the velocity outline.


2021 ◽  
Author(s):  
Priya kaushal ◽  
Tarun Chaudhary ◽  
Gargi Khanna

Abstract The present work is based on the computational study of MoS2 monolayer and effect of tensile strain on its atomic level structure. The bandgap for MoS2 monolayer, defected MoS2 monolayer and Silicon-doped monolayer are 1.82 eV (direct bandgap), 0.04 (indirect bandgap) and 1.25eV (indirect bandgap), respectively. The impact of tensile strain (0-0.7%) on the bandgap and effective mass of charge carriers of these three MoS2 structure has been investigated. The bandgap decrease of 5.76%, 31.86% and 6.03% has been observed in the three structures for biaxial strain while the impact of uniaxial strain is quite low. The impact of higher temperature on the bandgap under biaxial tensile strain has been also analyzed in this paper. These observations are extremely important for 2D material-based research for electronic applications.


2014 ◽  
Vol 29 (3) ◽  
pp. 315-330
Author(s):  
Yanina García Skabar ◽  
Matilde Nicolini

During the warm season 2002-2003, the South American Low-Level Jet Experiment (SALLJEX) was carried out in southeastern South America. Taking advantage of the unique database collected in the region, a set of analyses is generated for the SALLJEX period assimilating all available data. The spatial and temporal resolution of this new set of analyses is higher than that of analyses available up to present for southeastern South America. The aim of this paper is to determine the impact of assimilating data into initial fields on mesoscale forecasts in the region, using the Brazilian Regional Atmospheric Modeling System (BRAMS) with particular emphasis on the South American Low-Level Jet (SALLJ) structure and on rainfall forecasts. For most variables, using analyses with data assimilated as initial fields has positive effects on short term forecast. Such effect is greater in wind variables, but not significant in forecasts longer than 24 hours. In particular, data assimilation does not improve forecasts of 24-hour accumulated rainfall, but it has slight positive effects on accumulated rainfall between 6 and 12 forecast hours. As the main focus is on the representation of the SALLJ, the effect of data assimilation in its forecast was explored. Results show that SALLJ is fairly predictable however assimilating additional observation data has small impact on the forecast of SALLJ timing and intensity. The strength of the SALLJ is underestimated independently of data assimilation. However, Root mean square error (RMSE) and BIAS values reveal the positive effect of data assimilation up to 18-hours forecasts with a greater impact near higher topography.


2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Stelios A. Mitilineos ◽  
Stelios M. Potirakis ◽  
Nicolas-Alexander Tatlas ◽  
Maria Rangoussi

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.


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