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 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).

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 Land Cover Change Effects on the Climate of the La Plata Basin

2012 ◽  
Vol 13 (1) ◽  
pp. 84-102 ◽  
Author(s):  
Seung-Jae Lee ◽  
Ernesto Hugo Berbery
Keyword(s):  
Surface Roughness ◽  
Land Cover ◽  
Surface Temperature ◽  
River Basin ◽  
Land Surface ◽  
Roughness Length ◽  
Sensible Heat Flux ◽  
Near Surface ◽  
La Plata ◽  
Surface Roughness Length

Abstract Deforestation and replacement of natural pastures by agriculture have become a common practice in the La Plata River basin in South America. The changes in land cover imply changes in the biophysical properties of the land surface, with possible impacts on the basin’s hydroclimate. To help understand to what extent the climate could be affected, and through which processes, ensembles of seasonal simulations were prepared using the Weather Research and Forecasting Model for a control case and a scenario assuming an expansion of the agricultural activities to cover the entire basin. The La Plata River basin shows different climate responses to the land cover changes depending on the region. The northern part of the basin, where forests and savanna were replaced by crops, experiences an overall increase in albedo that leads to a reduction of sensible heat flux and near-surface temperature. A reduction of surface roughness length leads to stronger low-level winds that, in turn, favor a larger amount of moisture being advected out of the northern part of the basin. The result is a reduction of the vertically integrated moisture flux convergence (VIMFC) and, consequently, in precipitation. In the southern part of the basin, changes from grasslands to crops reduce the albedo and thus increase the near-surface temperature. The reduction in surface roughness length is not as large as in the northern sector, reducing the northerly moisture fluxes and resulting in a net increase of VIMFC and, thus, in precipitation. Notably, advective processes modify the downstream circulation and precipitation patterns over the South Atlantic Ocean.

scholarly journals Sensitivity Analysis of the High-Resolution WISE-WRF Model with the Use of Surface Roughness Length in Seoul Metropolitan Areas

Atmosphere ◽  
2016 ◽  
Vol 26 (1) ◽  
pp. 111-126 ◽  
Author(s):  
Joon-Bum Jee ◽  
Min Jang ◽  
Chaeyeon Yi ◽  
Il-Sung Zo ◽  
Bu-Yo Kim ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Surface Roughness ◽  
High Resolution ◽  
Roughness Length ◽  
Metropolitan Areas ◽  
Wrf Model ◽  
Surface Roughness Length

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 Reduced Sea-Surface Roughness Length at a Coastal Site

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 991
Author(s):  
Yuncheng He ◽  
Jiyang Fu ◽  
Pak Wai Chan ◽  
Qiusheng Li ◽  
Zhenru Shu ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Roughness ◽  
Atmospheric Boundary Layer ◽  
Roughness Length ◽  
Sea Surface ◽  
Marine Atmospheric Boundary Layer ◽  
Coastal Site ◽  
Surface Roughness Length ◽  
Sea Surface Roughness ◽  
Roughness Lengths

Sea-surface roughness length is a key parameter for characterizing marine atmospheric boundary layer. Although aerodynamic roughness lengths for homogeneous land and open water surfaces have been examined extensively, the extension of relevant knowledge to the highly inhomogeneous coastal area is problematic due to the complex mechanisms controlling coastal meteorology. This study presented a lidar-based observational analysis of sea-surface roughness length at a coastal site in Hong Kong, in which the wind data recorded from March 2012 to November 2015 were considered and analyzed. The results indicated the turning of wind near the land-sea boundary, leading to a dominative wind direction parallel to the coastline and an acceleration in wind. Moreover, the roughness lengths corresponding to two representative azimuthal sectors were compared, in which the roughness lengths for the onshore wind sector (i.e., 120°–240°) appear to be larger than the constant value (z0 = 0.2 mm) recommended in much existing literature, whereas the values for the alongshore wind sector (i.e., 60°–90°) are significantly smaller, i.e., about two orders of magnitude less than that of a typical sea surface. However, it is to be noted that the effect of atmospheric stability, which is of crucial importance in governing the marine atmospheric boundary layer, is not taken into account in this study.

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.

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