Observational Estimates of the Horizontal Eddy Diffusivity and Mixing Length in the Low-Level Region of Intense Hurricanes

2012 ◽  
Vol 69 (4) ◽  
pp. 1306-1316 ◽  
Author(s):  
Jun A. Zhang ◽  
Michael T. Montgomery
Keyword(s):  
Wind Speed ◽  
Momentum Flux ◽  
Numerical Models ◽  
Eddy Diffusivity ◽  
Small Scale ◽  
Mixing Length ◽  
Low Level ◽  
Horizontal Mixing ◽  
Mean Wind Speed ◽  
Horizontal Momentum

Abstract This study examines further the characteristics of turbulent flow in the low-level region of intense hurricanes using in situ aircraft observations. The data analyzed here are the flight-level data collected by research aircraft that penetrated the eyewalls of category-5 Hurricane Hugo (1989), category-4 Hurricane Allen (1980), and category-5 Hurricane David (1979) between 1 km and the sea surface. Estimates of horizontal eddy momentum flux, horizontal eddy diffusivity, and horizontal mixing length are obtained. It is found that the horizontal momentum flux and horizontal diffusivity increase with increasing wind speed. The horizontal mixing length increases slightly with wind speed also, but the mixing length is not significantly dependent on the wind speed. The magnitude of the horizontal momentum flux is found to be comparable to that of the vertical momentum flux, indicating that horizontal mixing by turbulence becomes nonnegligible in the hurricane boundary layer, especially in the eyewall region. Within the context of simple K theory, the results suggest that the average horizontal eddy diffusivity and mixing length are approximately 1500 m2 s−1 and 750 m, respectively, at about 500 m in the eyewall region corresponding to the mean wind speed of approximately 52 m s−1. It is recalled also that the mixing length is a virtual scale in numerical models and is quantitatively smaller than the energy-containing scale of turbulent eddies. The distinction between these two scales is a useful reminder for the modeling community on the representation of small-scale turbulence in hurricanes.

scholarly journals The South Georgia Wave Experiment: A Means for Improved Analysis of Gravity Waves and Low-Level Wind Impacts Generated from Mountainous Islands

2018 ◽  
Vol 99 (5) ◽  
pp. 1027-1040 ◽  
Author(s):  
D. R. Jackson ◽  
A. Gadian ◽  
N. P. Hindley ◽  
L. Hoffmann ◽  
J. Hughes ◽  
...  
Keyword(s):  
High Resolution ◽  
Gravity Waves ◽  
Numerical Models ◽  
Small Island ◽  
Small Scale ◽  
The South ◽  
South Georgia ◽  
Low Level ◽  
Wave Experiment ◽  
Realistic Representation

AbstractGravity waves (GWs) play an important role in many atmospheric processes. However, the observation-based understanding of GWs is limited, and representing them in numerical models is difficult. Recent studies show that small islands can be intense sources of GWs, with climatologically significant effects on the atmospheric circulation. South Georgia, in the South Atlantic, is a notable source of such “small island” waves. GWs are usually too small scale to be resolved by current models, so their effects are represented approximately using resolved model fields (parameterization). However, the small-island waves are not well represented by such parameterizations, and the explicit representation of GWs in very-high-resolution models is still in its infancy. Steep islands such as South Georgia are also known to generate low-level wakes, affecting the flow hundreds of kilometers downwind. These wakes are also poorly represented in models.We present results from the South Georgia Wave Experiment (SG-WEX) for 5 July 2015. Analysis of GWs from satellite observations is augmented by radiosonde observations made from South Georgia. Simulations were also made using high-resolution configurations of the Met Office Unified Model (UM). Comparison with observations indicates that the UM performs well for this case, with realistic representation of GW patterns and low-level wakes. Examination of a longer simulation period suggests that the wakes generally are well represented by the model. The realism of these simulations suggests they can be used to develop parameterizations for use at coarser model resolutions.

scholarly journals Wind Power potential in Kigali and Western provinces of Rwanda

2015 ◽  
Vol 2 (1) ◽  
pp. 25-36
Author(s):  
Otieno Fredrick Onyango ◽  
Sibomana Gaston ◽  
Elie Kabende ◽  
Felix Nkunda ◽  
Jared Hera Ndeda
Keyword(s):  
Wind Speed ◽  
Probability Density ◽  
Wind Power ◽  
Wind Direction ◽  
Small Scale ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Low Wind Speeds

Wind speed and wind direction are the most important characteristics for assessing wind energy potential of a location using suitable probability density functions. In this investigation, a hybrid-Weibull probability density function was used to analyze data from Kigali, Gisenyi, and Kamembe stations. Kigali is located in the Eastern side of Rwanda while Gisenyi and Kamembe are to the West. On-site hourly wind speed and wind direction data for the year 2007 were analyzed using Matlab programmes. The annual mean wind speed for Kigali, Gisenyi, and Kamembe sites were determined as 2.36m/s, 2.95m/s and 2.97m/s respectively, while corresponding dominant wind directions for the stations were ,  and  respectively. The annual wind power density of Kigali was found to be  while the power densities for Gisenyi and Kamembe were determined as and . It is clear, the investigated regions are dominated by low wind speeds thus are suitable for small-scale wind power generation especially at Kamembe site.

Modelling rain heterogeneities within an urban neighbourhood

2021 ◽  
Author(s):  
Karolin S. Ferner ◽  
K. Heinke Schlünzen ◽  
Marita Boettcher
Keyword(s):  
Wind Speed ◽  
Urban Areas ◽  
Climate Model ◽  
Numerical Models ◽  
Urban Climate ◽  
Cloud Microphysics ◽  
In Situ Measurements ◽  
Small Scale ◽  
Atmospheric Processes

<p>Urbanisation locally modifies the regional climate: an urban climate develops. For example, the average wind speed in cities is reduced, while the gustiness is increased. Buildings induce vertical winds, which influence the falling of rain. All these processes lead to heterogeneous patterns of rain at ground and on building surfaces. The small-scale spatial rain heterogeneities may cause discomfort for people. Moreover, non-uniform wetting of buildings affects their hydrothermal performance and durability of their facades.</p><p>Measuring rain heterogeneities between buildings is, however, nearly impossible. Building induced wind gusts negatively influence the representativeness of in-situ measurements, especially in densely urbanised areas. Weather radars are usually too coarse and, more importantly, require an unobstructed view over the domain and thus do not measure ground precipitation in urban areas. Consequently, researchers turn to numerical modelling in order to investigate small-scale precipitation heterogeneities between buildings.</p><p>In building science, numerical models are used to investigate rain heterogeneities typically focussing on single buildings and vertical facades. Only few studies were performed for more than a single building or with inclusion of atmospheric processes such as radiation or condensation. In meteorology, increasing computational power now allows the use of small-scale obstacle-resolving models resolving atmospheric processes while covering neighbourhoods.</p><p>In order to assess rain heterogeneities between buildings we extended the micro-scale and obstacle-resolving transport- and stream model MITRAS (Salim et al. 2019). The same cloud microphysics parameterisation as in its mesoscale sister model METRAS (Schlünzen et al., 2018) was applied and boundary conditions for cloud and rain water content at obstacle surfaces were introduced. MITRAS results are checked for plausibility using radar and in-situ measurements (Ferner et al., 2021). To our knowledge MITRAS is the first numerical urban climate model that includes rain and simulates corresponding processes.</p><p>Model simulations were initialised for various wind speeds and mesoscale rain rates to assess their influence on the heterogeneity of falling rain in a domain of 1.9 x 1.7 km² around Hamburg City Hall. We investigated how wind speed or mesoscale rain rate influence the precipitation patterns at ground and at roof level. Based on these results we assessed the height dependence of precipitation. First analyses show that higher buildings receive more rain on their roofs than lower buildings; the results will be presented in detail in our talk.</p><p>Ferner, K.S., Boettcher, M., Schlünzen, K.H. (2021): Modelling the heterogeneity of rain in an urban neighbourhood. Publication in preparation</p><p>Salim, M.H., Schlünzen, K.H., Grawe, D., Boettcher, M., Gierisch, A.M.U., Fock B.H. (2018): The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory. Geosci. Model Dev., 11, 3427–3445, https://doi.org/10.5194/gmd-11-3427-2018.</p><p>Schlünzen, K.H., Boettcher, M., Fock, B.H., Gierisch, A.M.U., Grawe, D., and Salim, M. (2018): Scientific Documentation of the Multiscale Model System M-SYS. Meteorological Institute, Universität Hamburg. MEMI Technical Report 4</p>

scholarly journals Drifting-snow studies over an instrumented mountainous site: II. Measurements and numerical model at small scale

2001 ◽  
Vol 32 ◽  
pp. 175-181 ◽  
Author(s):  
Jean-Luc Michaux ◽  
Florence Naaim-Bouvet ◽  
Mohamed Naaim
Keyword(s):  
Wind Speed ◽  
Numerical Model ◽  
Small Scale ◽  
Wind Gust ◽  
Strong Wind ◽  
Experimental Site ◽  
In Situ Data ◽  
Drifting Snow ◽  
Mean Wind Speed ◽  
Gust Factors

AbstractThe Érosion torrentielle, neige et avalanche (Etna) unit of CEMAGREF and the Centre d’Etudes de la Neige of Météo-France have been working on snowdrift for 10 years. A numerical model was developed at CEMAGREF to simulate snowdrift (Naaim and others, 1998). To validate this model on in situ data, a high-altitude experimental site was developed, located at 2700 m a.s.l. at the Lac Blanc Pass near the Alpe d’Huez ski resort. It is a nearly flat area and faces winds primarily from north and south. After describing the experimental site, we present the processed data of winter 1998/99. First, we analyze the data from CEMAGREF’s acoustic snowdrift sensor. It is sensitive to snow depth and snow-particle type, so additional calibration is necessary. Nevertheless, it allowed us to study non- stationary aspects of drifting snow. An analysis of gust factors for wind and drifting snow indicates that strong wind-gust factors exist in the mountains, and that drifting snow is more important during a regular and strong wind episode than during high wind-gust periods. Therefore, the numerical model presented here uses only the recorded mean wind speed. The model, which attempts to reproduce several days of storm, takes into account the modification of input parameters (e.g wind speed) as a function of time. The comparison between numerical results and measurements for a given meteorological event shows good agreement.

scholarly journals Wind Resource Assessment and Economic Viability of Conventional and Unconventional Small Wind Turbines: A Case Study of Maryland

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5874
Author(s):  
Navid Goudarzi ◽  
Kasra Mohammadi ◽  
Alexandra St. St. Pé ◽  
Ruben Delgado ◽  
Weidong Zhu
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbines ◽  
Payback Period ◽  
Small Scale ◽  
Small Wind Turbines ◽  
Mean Wind Speed ◽  
Wind Resource ◽  
The Impact

Annual mean wind speed distribution models for power generation based on regional wind resource maps are limited by spatial and temporal resolutions. These models, in general, do not consider the impact of local terrain and atmospheric circulations. In this study, long-term five-year wind data at three sites on the North, East, and West of the Baltimore metropolitan area, Maryland, USA are statistically analyzed. The Weibull probability density function was defined based on the observatory data. Despite seasonal and spatial variability in the wind resource, the annual mean wind speed for all sites is around 3 m/s, suggesting the region is not suitable for large-scale power generation. However, it does display a wind power capacity that might allow for non-grid connected small-scale wind turbine applications. Technical and economic performance evaluations of more than 150 conventional small-scale wind turbines showed that an annual capacity factor and electricity production of 11% and 1990 kWh, respectively, are achievable. It results in a payback period of 13 years. Government incentives can improve the economic feasibility and attractiveness of investments in small wind turbines. To reduce the payback period lower than 10 years, modern/unconventional wind harvesting technologies are found to be an appealing option in this region. Key contributions of this work are (1) highlighting the need for studying the urban physics rather than just the regional wind resource maps for wind development projects in the build-environment, (2) illustrating the implementation of this approach in a real case study of Maryland, and (3) utilizing techno-economic data to determine suitable wind harnessing solutions for the studied sites.

scholarly journals Evaluation of Wind Energy Potential as a Power Generation Source in Chad

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Djamal Hissein Didane ◽  
Nurhayati Rosly ◽  
Mohd Fadhli Zulkafli ◽  
Syariful Syafiq Shamsudin
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Weather Condition ◽  
Small Scale ◽  
Range Analysis ◽  
Energy Potential ◽  
Prevailing Wind Direction ◽  
Wide Range ◽  
Mean Wind Speed

Long-term wind speed data for thirteen meteorological stations, measured over a five-year period, were statistically analyzed using the two-parameter Weibull distribution function. The purpose of this study is to reveal for the first time the wind power potentials in Chad and to provide a comprehensive wind map of the country. The results show that the values of the shape and scale parameters varied over a wide range. Analysis of the seasonal variations showed that higher wind speed values occur when the weather condition is generally dry and they drop considerably when the weather condition is wet. It was also observed that the wind speed increases as one moves from the southern zone to the Saharan zone. Although the wind power at each site varies significantly, however, the potentials of most of the sites were encouraging. Nevertheless, according to the PNNL classification system, they are favorable for small-scale applications only. A few stations in the middle of Sudanian and Sahel regions are found to be not feasible for wind energy generation due to their poor mean wind speed. The prevailing wind direction for both Saharan and Sahel regions is dominated by northeastern wind, while it diverged to different directions in the Sudanian zone.

scholarly journals Assessment of Wind Energy Potential as a Power Generation Source: A Case Study of Eight Selected Locations in Northern Cyprus

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2697 ◽  
Author(s):  
Mohamad Alayat ◽  
Youssef Kassem ◽  
Hüseyin Çamur
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Actual Data ◽  
Small Scale ◽  
Energy Potential ◽  
Northern Cyprus ◽  
Mean Wind Speed ◽  
Wind Energy Potential

This paper presents a techno-economic assessment of the wind power potential for eight locations distributed over the Northern part of Cyprus. The wind speed data were collected from the meteorological department located in Lefkoşa, Northern Cyprus.Ten distribution models were used to analyze the wind speed characteristics and wind energy potential at the selected locations. The maximum-likelihood method was used for calculating the parameters of the distribution functions.The power law model is utilized to determine the mean wind speed at various heights. In addition, the wind power density for each location was estimated. Furthermore, the performances of different small-scale vertical axis 3–10 kW wind turbines were evaluated to find those that were suitable and efficient for power generation in the studied locations.The results showed that the annual mean wind speed in the regions is greater than 2 m/s at a height of 10 m. Moreover, it is indicated that Generalized Extreme Value distribution provided the best fit to the actual data for the regions of Lefkoşa, Ercan, Girne, Güzelyurt, and Dipkarpaz. However, the Log-Logistic, Weibull, and Gamma distributions gave a better fit to the actual data of Gazimağusa, YeniBoğaziçi, and Salamis, respectively. The Rayleigh distribution does not fit the actual data from all regions. Furthermore, the values of wind power densityat the areas studied ranged from 38.76 W/m2 to 134.29 W/m2 at a height of 50 m, which indicated that wind energy sources in these selected locations are classified as poor. Meanwhile, based on the wind analysis, small-scale wind turbine use can be suitable for generating electricity in the studied locations. Consequently, an Aeolos-V2 with a rating of 5 kW was found to be capable of producing the annual energy needs of an average household in Northern Cyprus.

scholarly journals Multilevel Tower Observations of Vertical Eddy Diffusivity and Mixing Length in the Tropical Cyclone Boundary Layer during Landfalls

2018 ◽  
Vol 75 (9) ◽  
pp. 3159-3168 ◽  
Author(s):  
Jie Tang ◽  
Jun A. Zhang ◽  
Sim D. Aberson ◽  
Frank D. Marks ◽  
Xiaotu Lei
Keyword(s):  
Boundary Layer ◽  
Tropical Cyclones ◽  
Numerical Models ◽  
Theoretical Method ◽  
Eddy Diffusivity ◽  
Eddy Correlation ◽  
Mixing Length ◽  
Momentum Fluxes ◽  
Vertical Eddy Diffusivity ◽  
Vertical Eddy

Abstract This study analyzes the fast-response (20 Hz) wind data collected by a multilevel tower during the landfalls of Tropical Storm Lionrock (1006), Typhoon Fanapi (1011), and Typhoon Megi (1015) in 2010. Turbulent momentum fluxes are calculated using the standard eddy-correlation method. Vertical eddy diffusivity Km and mixing length are estimated using the directly measured momentum fluxes and mean-wind profiles. It is found that the momentum flux increases with wind speed at all four levels. The eddy diffusivity calculated using the direct-flux method is compared to that using a theoretical method in which the vertical eddy diffusivity is formulated as a linear function of the friction velocity and height. It is found that below ~60 m, Km can be approximately parameterized using this theoretical method, though this method overestimates Km for higher altitude, indicating that the surface-layer depth is close to 60 m in the tropical cyclones studied here. It is also found that Km at each level varies with wind direction during landfalls: Km estimated based on observations with landward fetch is significantly larger than that estimated using data with seaward fetch. This result suggests that different parameterizations of Km should be used in the boundary layer schemes of numerical models forecasting tropical cyclones over land versus over the ocean.

A MODEL FOR THE SIMULATION OF CROSSWIND INTEGRATED CONCENTRATIONS IN THE SURFACE-BASED INVERSION LAYER

2012 ◽  
Vol 03 (04) ◽  
pp. 1250017
Author(s):  
MANISH MODANI ◽  
MAITHILI SHARAN
Keyword(s):  
Wind Speed ◽  
Numerical Models ◽  
Dispersion Model ◽  
Inversion Layer ◽  
Delta Function ◽  
Eddy Diffusivity ◽  
Analytical Models ◽  
Dirac Delta ◽  
Proposed Model ◽  
Functional Forms

A dispersion model for the estimation of crosswind integrated concentrations in the surface-based inversion is proposed. The generalized forms of eddy diffusivity with spatial dependence in both horizontal and vertical directions and vertical height-dependent wind speed are considered. In view of the computational limitation associated with numerical models for Dirac-delta function, the source term is expressed as a limiting case of normal distribution. The accuracy of the employed numerical scheme to solve the resulting partial differential equation with appropriate physically relevant boundary conditions is checked with those obtained from the respective analytical solutions available in literature for the particular forms of eddy diffusivity and wind speed. Concentrations computed from the proposed model are found close to those obtained from analytical models. The concentrations obtained from the proposed model are evaluated for the generalized functional forms of eddy diffusivity (Degrazia and Moraes, 1992; Degrazia et al., 2001) and diabatic logarithmic profile as well as power-law profile of wind speed with the observations from Hanford (Doran et al., 1984) and Copenhagen (Gryning and Lyck, 1984) diffusion experiments in stable and unstable conditions, respectively. Majority of the cases i.e., 64% and 96% are predicted in factor of two to observations in both stable and unstable conditions, respectively.

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