scholarly journals Investigating the Aerodynamic Surface Roughness Length over Baghdad City Utilizing Remote Sensing and GIS Techniques

2021 ◽  
Vol 18 (2(Suppl.)) ◽  
pp. 1048
Author(s):  
Al-Zahraa A. Mohsen ◽  
Monim H. Al-Jiboori ◽  
Yaseen K. Al-Timimi
Keyword(s):  
Remote Sensing ◽  
Surface Roughness ◽  
Wind Speed ◽  
Roughness Length ◽  
Roughness Element ◽  
Surface Model ◽  
Gis Applications ◽  
Surface Roughness Length ◽  
Green Zone ◽  
Elevation Model

This study calculated the surface roughness length (Zo), zero-displacement length (Zd) and height of the roughness elements (ZH) using GIS applications. The practical benefit of this study is to classify the development of Baghdad, choose the appropriate places for installing wind turbines, improve urban planning, find rates of turbulence, pollution and others. The surface roughness length (Zo) of Baghdad city was estimated based on the data of the wind speed obtained from an automatic weather station installed at Al-Mustansiriyah University, the data of the satellite images digital elevation model (DEM), and the digital surface model (DSM), utilizing Remote Sensing Techniques. The study area was divided into 15 municipalities (Rasheed, Mansour, Shulaa, Karrada, Shaab, Adhamiyah, Sadre 2, Sadre 1, Rusafa, Alghadeer, Baghdad Aljadeedah, Karkh, Kadhumiya, Green zone, and Dora). The results indicated that the variations in Zo depend strongly on zero-displacement length (Zd) and the roughness element height (ZH) and wind speed. The research results demonstrated that Baghdad Aljadeedah has the largest (Zo) with 0.43 m and Rasheed has the lowest value of (Zo) with 0.19 m.; the average (Zo) of Baghdad city was 0.32 m.

CORRECTION OF WIND SPEED DATA ACCORDING TO THE OPEN TERRAIN CONDITIONS

2019 ◽  
pp. 131-139
Author(s):  
D.O. Oshurok ◽  
O.Y. Skrynyk
Keyword(s):  
Surface Roughness ◽  
Wind Speed ◽  
Roughness Length ◽  
Pearson Correlation ◽  
Aerodynamic Characteristics ◽  
Google Earth ◽  
Homogeneous Distribution ◽  
Heterogeneous Structure ◽  
Wind Speed Data ◽  
Surface Roughness Length

Wind speed spatial distribution over the territory of Ukraine built based on weather stations measurements has been analyzed. Interpolated field of wind speed averaged over 1981-2010 indicated fairly heterogeneous structure with a number of artificial spots of larger/smaller values compared to surrounding areas. The main reason of such heterogeneity might be associated with representativeness of observation site regarding the landscape zone. It is well known that surrounding obstacles have a great impact on wind flow in horizontal direction. In order to solve this problem we have corrected sub-daily wind speed data measured at 207 meteorological stations of Ukraine for the period of 1981-2010 according to the open terrain conditions and the standard height (10 m). Generally, aerodynamic characteristics (e.g. surface roughness length) of measurement sites are needed in order to perform such adjustment. However, the only usable parameter available at a climatological reference book is horizon closure degree. The research revealed significant relationship between this characteristic and wind speed records (Pearson correlation coefficient equals -0.58). Given that horizon closure degree could not be used in correction procedure directly, surface roughness length has been calculated for 10 stations and statistical relationship has been determined between these two parameters. Based on the obtained relation and additional information we have found roughness length for all 207 stations at eight directions. Supplementary materials for analysis included observation sites description and Google Earth snapshots as well. In the final step, there has been applied a correction formula derived from the neutral logarithmic profile of wind speed in the atmospheric surface layer. The output of the research is new database of corrected wind speed measurements for the multiyear period. These results have been compared with observations. Mean 30-yr corrected speeds are featured by more homogeneous distribution over Ukraine and mostly higher values (with positive mean spatial bias ~0.35 m/s). The applied method allowed us to remove uncertainties related to differences in vertical level of measurements and considerably eliminate influence of the micro-scale terrain inhomogeneity. Obtained datasets may facilitate to perform spatial interpolation and further development of Ukrainian Wind Atlas.

scholarly journals Influence of sea surface roughness length parameterization on Mistral and Tramontane simulations

2016 ◽  
Vol 13 ◽  
pp. 107-112 ◽  
Author(s):  
Anika Obermann ◽  
Benedikt Edelmann ◽  
Bodo Ahrens
Keyword(s):  
Surface Roughness ◽  
Wind Speed ◽  
Wind Direction ◽  
Roughness Length ◽  
Western Mediterranean ◽  
Sea Surface ◽  
Surface Roughness Length ◽  
Sea Surface Roughness ◽  
Simulated Wind ◽  
Simulated Wind Speed

Abstract. The Mistral and Tramontane are mesoscale winds in southern France and above the Western Mediterranean Sea. They are phenomena well suited for studying channeling effects as well as atmosphere–land/ocean processes. This sensitivity study deals with the influence of the sea surface roughness length parameterizations on simulated Mistral and Tramontane wind speed and wind direction. Several simulations with the regional climate model COSMO-CLM were performed for the year 2005 with varying values for the Charnock parameter α. Above the western Mediterranean area, the simulated wind speed and wind direction pattern on Mistral days changes depending on the parameterization used. Higher values of α lead to lower simulated wind speeds. In areas, where the simulated wind speed does not change much, a counterclockwise rotation of the simulated wind direction is observed.

scholarly journals Methods to Estimate Surface Roughness Length for Offshore Wind Energy

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Maryam Golbazi ◽  
Cristina L. Archer
Keyword(s):  
Surface Roughness ◽  
Wind Speed ◽  
Statistical Method ◽  
Analytical Method ◽  
Roughness Length ◽  
Robust Statistics ◽  
Atmospheric Stability ◽  
Offshore Wind ◽  
Surface Roughness Length ◽  
Wind Measurements

The northeastern coast of the U.S. is projected to expand its offshore wind capacity from the existing 30 MW to over 22 GW in the next decade, yet, only a few wind measurements are available in the region and none at hub height (around 100 m today); thus, extrapolations are needed to estimate wind speed as a function of height. A common method is the log-law, which is based on surface roughness length (z0). No reliable estimates of z0 for the region have been presented in the literature. Here, we fill this knowledge gap using two field campaigns that were conducted in the Nantucket Sound at the Cape Wind (CW) platform: the 2003–2009 “CW Historical”, which collected wind measurements on a meteorological tower at three levels (20, 41, and 60 m AMSL) with sonic and cup/vane anemometers, and the 2013–2014 IMPOWR (Improving the Mapping and Prediction of Offshore Wind Resources), which collected high-frequency wind and flux measurements at 12 m AMSL. We tested three different methods to calculate z0: (1) analytical method, dependent on friction velocity u∗ and a stability function ψ; (2) the Charnock relationship between z0 and u∗; and (3) a statistical method based on wind speed observed at the three levels. The first two methods are physical, whereas the statistical method is purely mathematical. Comparing mean and median of z0, we find that the median is a more robust statistics because the mean varies by over four orders of magnitude across the three methods and the two campaigns. In general, the median z0 exhibits little seasonal variability and a weak dependency on atmospheric stability, which was predominantly unstable (54–67%). With the goal of providing the most accurate estimates of wind speed near the hub height of modern turbines, the statistical method, despite delivering unrealistic z0 values at times, gives the best estimates of 60 m winds, even when the 5 m wind speed from a nearby buoy is used as the reference. The unrealistic z0 values are caused by nonmonotonic wind speed profiles, occurring about 41% of the time, and should not be rejected because they produce realistic fits. Furthermore, the statistical method outperforms the other two even though it does not need any stability information. In summary, if wind speed data from multiple levels are available, as is the case with vertically pointing floating lidar and meteorological towers, the statistical method is recommended, regardless of the seemingly unrealistic z0 values at times. If multilevel wind speeds are not available but advanced sonic anemometry is available at one level, the analytical method is recommended over Charnock’s. Lastly, if a single, constant value of z0 is sought after to characterize the region, we recommend the median from the statistical method, i.e., 6.09×10−3 m, which is typical of rough seas.

scholarly journals Effects of Modified Surface Roughness Length over Shallow Waters in a Regional Model Simulation

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 818
Author(s):  
So-Young Kim ◽  
Song-You Hong ◽  
Young Cheol Kwon ◽  
Yong Hee Lee ◽  
Da-Eun Kim
Keyword(s):  
Surface Roughness ◽  
Wind Speed ◽  
Roughness Length ◽  
Control Experiment ◽  
Lower Troposphere ◽  
Sea Surface ◽  
Shallow Waters ◽  
Surface Roughness Length ◽  
Sea Surface Roughness ◽  
Modified Surface

The effects of modified sea-surface roughness length over shallow waters are examined in a regional climate simulation over East Asia centered on the Korean Peninsula, using the Advanced Research Weather Research and Forecasting model (WRF-ARW). The control experiment calculates the sea-surface roughness length as a function of friction velocity based on the Charnock relationship. The experiment considering water depth in the sea-surface roughness length over shallow waters is compared with the control experiment. In the experiment considering water depth, the excessive near-surface wind speed over shallow waters is reduced compared to that of the control experiment. Wind speed is reduced also in the lower troposphere. The effects of modified surface roughness over shallow waters are not localized to the lower troposphere but extended into the upper troposphere. Through the vertical interaction between the lower and upper levels, upper tropospheric wind—which is underestimated in the control experiment—is enhanced in the experiment with modified sea-surface roughness length, not only over the shallow waters, but also over the entire domain. As a result, the vertical shear of zonal wind increases, leading to the enhancement of the negative meridional temperature gradient in the mid troposphere.

scholarly journals Effects of Land Use and Meteorological Conditions on Local and Regional Momentum Transport and Roughness for Midwestern Cropping Systems

2005 ◽  
Vol 6 (6) ◽  
pp. 825-839 ◽  
Author(s):  
William P. Kustas ◽  
John H. Prueger ◽  
J. Ian MacPherson ◽  
Mengistu Wolde ◽  
Fuqin Li
Keyword(s):  
Heat Flux ◽  
Surface Roughness ◽  
Wind Speed ◽  
Roughness Length ◽  
Single Source ◽  
Effective Surface ◽  
Area Index ◽  
Blending Height ◽  
Surface Roughness Length ◽  
Aircraft Observations

Abstract Eddy covariance measurements of wind speed u and shear velocity u* from tower- and aircraft-based systems collected over rapidly developing corn- (Zea mays L.) and soybean [Glycine max (L.) Merr.] fields were used in determining the local and regional (effective) surface roughness length zo and 〈zo〉, respectively. For corn, canopy height increased from ∼1 to 2 m and the leaf area index changed from ∼1 to 4 during the study period, while for soybean, canopy height increased from ∼0.1 to 0.5 m and the leaf area index increased from ∼0.5 to 2. A procedure for the aggregation of local roughness values from the different land cover types based on blending-height concepts yielded effective surface roughness values that were from ∼1/2 to 1/4 of the magnitude estimated with the aircraft data. This indicated additional kinematic stress caused by form drag from isolated obstacles (i.e., trees, houses, and farm buildings), and the interaction of adjacent corn- and soybean fields were probably important factors influencing the effective surface roughness length for this landscape. The comparison of u* measurements from the towers versus the aircraft indicated that u* from aircraft was 20%–30% higher, on average, and that u* over corn was 10%–30% higher than over soybean, depending on stability. These results provide further evidence for the likely sources of additional kinematic stress. Although there was an increase in zo and 〈zo〉 over time as the crops rapidly developed, particularly for corn, there was a more significant trend of increasing roughness length with decreasing wind speed at wind speed thresholds of around 5 m s−1 for the aircraft and 3 m s−1 for the tower measurements. Other studies have recently reported such a trend. The impact on computed sensible heat flux H using 〈zo〉 derived from the aggregation of zo from the different land cover types, using the blending-height scheme, and that estimated from the aircraft observations, was evaluated using a calibrated single-source/bulk resistance approach with surface–air temperature differences from the aircraft observations. An underestimate of 〈zo〉 by 50% and 75% resulted in a bias in the H estimates of approximately 10% and 15%, respectively. This is a relatively minor error when considering that the root-mean-square error (rmse) value between single-source estimates and the aircraft observations of H was 15 W m−2 using the aircraft-derived 〈zo〉, and only increased to approximately 20 and 25 W m−2 using the 1/2 and 1/4 〈zo〉 values, as estimated from the blending-height scheme. The magnitude of the excess resistance relative to the aerodynamic resistance to heat transfer was a major contributing factor in minimizing the error in heat flux calculations resulting from these underestimations of 〈zo〉.

scholarly journals The making of the New European Wind Atlas – Part 1: Model sensitivity

2020 ◽  
Vol 13 (10) ◽  
pp. 5053-5078 ◽  
Author(s):  
Andrea N. Hahmann ◽  
Tija Sīle ◽  
Björn Witha ◽  
Neil N. Davis ◽  
Martin Dörenkämper ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Roughness ◽  
Wind Speed ◽  
Planetary Boundary Layer ◽  
Roughness Length ◽  
Wrf Model ◽  
Model Sensitivity ◽  
Surface Roughness Length ◽  
Wind Climate ◽  
Physical Parameterizations

Abstract. This is the first of two papers that document the creation of the New European Wind Atlas (NEWA). It describes the sensitivity analysis and evaluation procedures that formed the basis for choosing the final setup of the mesoscale model simulations of the wind atlas. The suitable combination of model setup and parameterizations, bound by practical constraints, was found for simulating the climatology of the wind field at turbine-relevant heights with the Weather Research and Forecasting (WRF) model. Initial WRF model sensitivity experiments compared the wind climate generated by using two commonly used planetary boundary layer schemes and were carried out over several regions in Europe. They confirmed that the most significant differences in annual mean wind speed at 100 m a.g.l. (above ground level) mostly coincide with areas of high surface roughness length and not with the location of the domains or maximum wind speed. Then an ensemble of more than 50 simulations with different setups for a single year was carried out for one domain covering northern Europe for which tall mast observations were available. We varied many different parameters across the simulations, e.g. model version, forcing data, various physical parameterizations, and the size of the model domain. These simulations showed that although virtually every parameter change affects the results in some way, significant changes in the wind climate in the boundary layer are mostly due to using different physical parameterizations, especially the planetary boundary layer scheme, the representation of the land surface, and the prescribed surface roughness length. Also, the setup of the simulations, such as the integration length and the domain size, can considerably influence the results. We assessed the degree of similarity between winds simulated by the WRF ensemble members and the observations using a suite of metrics, including the Earth Mover's Distance (EMD), a statistic that measures the distance between two probability distributions. The EMD was used to diagnose the performance of each ensemble member using the full wind speed and direction distribution, which is essential for wind resource assessment. We identified the most realistic ensemble members to determine the most suitable configuration to be used in the final production run, which is fully described and evaluated in the second part of this study (Dörenkämper et al., 2020).

scholarly journals The Making of the New European Wind Atlas, Part 1: Model Sensitivity

2020 ◽  
Author(s):  
Andrea N. Hahmann ◽  
Tija Sile ◽  
Björn Witha ◽  
Neil N. Davis ◽  
Martin Dörenkämper ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Roughness ◽  
Wind Speed ◽  
Planetary Boundary Layer ◽  
Land Surface ◽  
Roughness Length ◽  
Wrf Model ◽  
Model Sensitivity ◽  
Surface Roughness Length ◽  
Wind Climate

Abstract. This is the first of two papers that documents the creation of the New European Wind Atlas (NEWA). It describes the sensitivity analysis and evaluation procedures that formed the basis for choosing the final setup of the mesoscale model simulations of the wind atlas. An optimal combination of model setup and parameterisations was found for simulating the climatology of the wind field at turbine-relevant heights with the Weather Research and Forecasting (WRF) model. Initial WRF model sensitivity experiments compared the wind climate generated by using two commonly used planetary boundary layer schemes and were carried out over several regions in Europe. They confirmed that the largest differences in annual mean wind speed at 100 m above ground level mostly coincide with areas of high surface roughness length and not with the location of the domains or maximum wind speed. Then an ensemble of more than 50 simulations with different setups for a single year was carried out for one domain covering Northern Europe, for which tall mast observations were available. Many different parameters were varied across the simulations, for example, model version, forcing data, various physical parameterisations and the size of the model domain. These simulations showed that although virtually every parameter change affects the results in some way, significant changes on the wind climate in the boundary layer are mostly due to using different physical parameterisations, especially the planetary boundary layer scheme, the representation of the land surface, and the prescribed surface roughness length. Also, the setup of the simulations, such as the integration length and the domain size can considerably influence the results. The degree of similarity between winds simulated by the WRF ensemble members and the observations was assessed using a suite of metrics, including the Earth Mover's Distance (EMD), a statistic that measures the distance between two probability distributions. The EMD was used to diagnose the performance of each ensemble member using the full wind speed distribution, which is important for wind resource assessment. The most realistic ensemble members were identified to determine the most suitable configuration to be used in the final production run, which is fully described and evaluated in the second part of this study.

scholarly journals Determination of the surface roughness length for use in mesoscale air quality modelling

1987 ◽  
Vol 7 (3) ◽  
Author(s):  
T.C.M Vleggaar ◽  
O.L Fourie
Keyword(s):  
Surface Roughness ◽  
Air Quality ◽  
Wind Speed ◽  
Roughness Length ◽  
Air Quality Modelling ◽  
Surface Roughness Length ◽  
Geographical Maps ◽  
Modelling Methods ◽  
Mesoscale Air Quality

The surface roughnesss legth z0 is an important parameter in air quality modelling. Methods for estimating this parameter for the Estaern Highveld, using availabe data, were investigated. The use of existing geographical maps to determine land cover suffers from certain deficiences. Tethersonde wind speed profiles were found to be inadequate for the purpose of the determination of z0, and it would seem that time-averaged wind speed measurements along a mast are required

Sign in / Sign up

Export Citation Format

Share Document