scholarly journals Wind speed characteristics and implications for wind power generation: Cape regions, South Africa

2017 ◽  
Vol 113 (7/8) ◽  
Author(s):  
Marc A. Wright ◽  
Stefan W. Grab
Keyword(s):  
South Africa ◽  
Power Generation ◽  
Wind Speed ◽  
Coastal Zone ◽  
Temporal Dynamics ◽  
Surface Wind ◽  
Eastern Cape ◽  
Near Surface ◽  
Wind Speeds ◽  
The Mean

Spatio-temporal dynamics of near-surface wind speeds were examined across the Northern, Western and Eastern Cape regions of South Africa. The regions assessed were geographically subdivided into three zones: coastal, coastal hinterland and inland. Wind speed data (10 m) were evaluated at monthly, seasonal, annual and zonal resolutions, with the aim to establish wind speed attributes and trends. Data from 19 weather stations with high-resolution wind records between 1995 and 2014 were evaluated. The majority of stations (79%) recorded a decrease in mean annual wind speed over the study period. The mean rate of decrease across all stations over the 20-year period equates to -1.25%, quantifying to an annual decrease of -0.002 m/s/year (-0.06% pa). The largest seasonal decline of -0.006 m/s/year (-0.15% pa) was recorded in summer. Statistically significant declines in mean annual wind speed are somewhat more pronounced for the coastal zone (-0.003 m/s/year, -0.08% pa) than over interior regions (-0.002 m/s/year, -0.06% pa) for the study period. The largest decrease (-0.08% pa) was recorded for the coastal zone, followed by the inland zone (-0.06% pa), equating to an annual reduction in available energy of 0.18% pa and 0.09% pa, respectively. When considering all stations over the study period, the mean inter-annual variability is 3.11%. Despite such decreases in wind speed, the variance identified in this study would not have posed any risk to power generation from wind across the assessed stations, based on the period 1995 to 2014.

scholarly journals Model-Based Projections and Uncertainties of Near-Surface Wind Climate in Western Canada

2016 ◽  
Vol 55 (10) ◽  
pp. 2229-2245 ◽  
Author(s):  
Jeffrey T. Daines ◽  
Adam H. Monahan ◽  
Charles L. Curry
Keyword(s):  
Power Generation ◽  
Standard Deviation ◽  
Wind Speed ◽  
Wind Power ◽  
Surface Wind ◽  
Western Canada ◽  
Near Surface ◽  
Wind Speeds ◽  
Ensemble Mean ◽  
Wind Climate

AbstractNear-surface wind is important in forestry, agriculture, air pollution, building energy use, and wind power generation. In western Canada it presently plays a minor role in power generation, but ongoing reductions in the cost of wind power infrastructure and the increasing costs of conventional power generation (including environmental costs) motivate the assessment of the projected future wind climate and uncertainties in this projection. Multiple realizations of the Canadian Regional Climate Model (CRCM) at 45-km resolution were driven by two global climate models over the periods 1971–2000 (using historical greenhouse gas concentrations) and 2031–60 (using the SRES-A2 concentration scenario). Hourly wind speeds from 30 stations were analyzed over 1971–2000 and used to calibrate downscaled ensembles of projected wind speed distributions over 2031–60. At most station locations modest increases in mean wind speed were found for a majority of the projections, but with an ensemble spread of the same order of magnitude as the increases. Relative changes in mean wind speeds at station locations were found to be insensitive to the station observations and calibration technique. In view of this result, projected relative changes in future wind climate over the entire CRCM domain were estimated using uncalibrated pairs of past-period and future-period wind speed distributions. The relative changes are robust, in the sense that their ensemble mean relative change is greater than their standard deviation, but are not very substantial, in the sense that their ensemble mean change is generally less than the standard deviation of their annual means.

scholarly journals Snow density along the route traversed by the Japanese-Swedish Antarctic Expedition 2007/08

2012 ◽  
Vol 58 (209) ◽  
pp. 529-539 ◽  
Author(s):  
Shin Sugiyama ◽  
Hiroyuki Enomoto ◽  
Shuji Fujita ◽  
Kotaro Fukui ◽  
Fumio Nakazawa ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Coastal Region ◽  
Snow Density ◽  
Syowa Station ◽  
Near Surface ◽  
A Value ◽  
Surface Snow ◽  
The Mean ◽  
The Antarctic

AbstractDuring the Japanese-Swedish Antarctic traverse expedition of 2007/08, we measured the surface snow density at 46 locations along the 2800 km long route from Syowa station to Wasa station in East Antarctica. The mean snow density for the upper 1 (or 0.5) m layer varied from 333 to 439 kg m-3 over a region spanning an elevation range of 365-3800 ma.s.l. The density variations were associated with the elevation of the sampling sites; the density decreased as the elevation increased, moving from the coastal region inland. However, the density was relatively insensitive to the change in elevation along the ridge on the Antarctic plateau between Dome F and Kohnen stations. Because surface wind is weak in this region, irrespective of elevation, the wind speed was suggested to play a key role in the near-surface densification. The results of multiple regression performed on the density using meteorological variables were significantly improved by the inclusion of wind speed as a predictor. The regression analysis yielded a linear dependence between the density and the wind speed, with a coefficient of 13.5 kg m-3 (m s-1)-1. This relationship is nearly three times stronger than a value previously computed from a dataset available in Antarctica. Our data indicate that the wind speed is more important to estimates of the surface snow density in Antarctica than has been previously assumed.

scholarly journals Evaluation of the Ocean Surface Wind Speed Change following the Super Typhoon from Space-Borne GNSS-Reflectometry

2020 ◽  
Vol 12 (12) ◽  
pp. 2034 ◽  
Author(s):  
Hongsu Liu ◽  
Shuanggen Jin ◽  
Qingyun Yan
Keyword(s):  
Wind Speed ◽  
Correlation Coefficient ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Wind Speeds ◽  
Mean Error ◽  
Super Typhoon ◽  
The Mean ◽  
Ocean Surface Wind

Ocean surface wind speed is an essential parameter for typhoon monitoring and forecasting. However, traditional satellite and buoy observations are difficult to monitor the typhoon due to high cost and low temporal-spatial resolution. With the development of spaceborne GNSS-R technology, the cyclone global navigation satellite system (CYGNSS) with eight satellites in low-earth orbit provides an opportunity to measure the ocean surface wind speed of typhoons. Though observations are made at the extremely efficient spatial and temporal resolution, its accuracy and reliability are unclear in an actual super typhoon case. In this study, the wind speed variations over the life cycle of the 2018 Typhoon Mangkhut from CYGNSS observations were evaluated and compared with European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-5 (ERA-5). The results show that the overall root-mean-square error (RMSE) of CYGNSS versus ECMWF was 4.12 m/s, the mean error was 1.36 m/s, and the correlation coefficient was 0.96. For wind speeds lower and greater than 15 m/s, the RMSE of CYGNSS versus ECMWF were 1.02 and 4.36 m/s, the mean errors were 0.05 and 1.61 m/s, the correlation coefficients were 0.91 and 0.90, and the average relative errors were 9.8% and 11.6%, respectively. When the typhoon reached a strong typhoon or super typhoon, the RMSE of CYGNSS with respect to ERA-5 from ECMWF was 5.07 m/s; the mean error was 3.57 m/s; the correlation coefficient was 0.52 and the average relative error was 11.0%. The CYGNSS estimation had higher precision for wind speeds below 15 m/s, but degraded when the wind speed was above 15 m/s.

scholarly journals CYGNSS Ocean Surface Wind Validation in the Tropics

2020 ◽  
Author(s):  
Shakeel Asharaf ◽  
Duane E. Waliser ◽  
Derek J. Posselt ◽  
Christopher S. Ruf ◽  
Chidong Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Satellite System ◽  
Cold Pool ◽  
Tropical Ocean ◽  
Near Surface ◽  
Wind Speeds ◽  
Low Wind Speeds ◽  
Global Navigation Satellite

AbstractSurface wind plays a crucial role in many local/regional weather and climate processes, especially through the exchanges of energy, mass and momentum across the Earth’s surface. However, there is a lack of consistent observations with continuous coverage over the global tropical ocean. To fill this gap, the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission was launched in December 2016, consisting of a constellation of eight small spacecrafts that remotely sense near surface wind speed over the tropical and sub-tropical oceans with relatively high sampling rates both temporally and spatially. This current study uses data obtained from the Tropical Moored Buoy Arrays to quantitatively characterize and validate the CYGNSS derived winds over the tropical Indian, Pacific, and Atlantic Oceans. The validation results show that the uncertainty in CYGNSS wind speed, as compared with these tropical buoy data, is less than 2 m s-1 root mean squared difference, meeting the NASA science mission Level-1 uncertainty requirement for wind speeds below 20 m s-1. The quality of the CYGNSS wind is further assessed under different precipitation conditions, and in convective cold-pool events, identified using buoy rain and temperature data. Results show that CYGNSS winds compare fairly well with buoy observations in the presence of rain, though at low wind speeds the presence of rain appears to cause a slight positive wind speed bias in the CYGNSS data. The comparison indicates the potential utility of the CYGNSS surface wind product, which in turn may help to unravel the complexities of air-sea interaction in regions that are relatively under-sampled by other observing platforms.

scholarly journals Spatiotemporal Characteristics of Near-Surface Wind in Shenzhen

2020 ◽  
Vol 12 (2) ◽  
pp. 739 ◽  
Author(s):  
Cheng Liu ◽  
Qinglan Li ◽  
Wei Zhao ◽  
Yuqing Wang ◽  
Riaz Ali ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Surface Wind ◽  
Prevailing Wind ◽  
Average Wind Speed ◽  
Near Surface ◽  
Average Wind ◽  
Prevailing Wind Direction ◽  
Seasonal Wind ◽  
The Mean

The spatiotemporal characteristics of near-surface wind in Shenzhen were investigated in this study by using hourly observations at 92 automatic weather stations (AWSs) from 2009 to 2018. The results show that during the past 10 years, most of the stations showed a decreasing trend in the annual mean of the 10 min average wind speed (avg-wind) and the mean of the 3 s average wind speed (gust wind). Over half of the decreasing trends at the stations were statistically significant (p < 0.05). Seasonally, the decrease in wind speed was the most severe in spring, followed by autumn, winter, and summer. The distribution of wind speed tends to be greater in the east and coastal areas for both avg-wind and gust wind. From September to March of the following year, the prevailing wind direction in Shenzhen was northerly, and from April to August, the prevailing wind direction was southerly. The seasonal wind speed distribution exhibited two different types, spring–summer type and autumn–winter type, which may be induced by their different prevailing wind directions. The analysis by the empirical orthogonal function (EOF) method confirmed the previous findings that the mean wind speed was decreasing in Shenzhen and that two different seasonal wind speed spatial distribution patterns existed. Such a study could provide references for wind forecasting and risk assessment in the study area.

scholarly journals Homogenization and Trend Analysis of Canadian Near-Surface Wind Speeds

2010 ◽  
Vol 23 (5) ◽  
pp. 1209-1225 ◽  
Author(s):  
Hui Wan ◽  
Xiaolan L. Wang ◽  
Val R. Swail
Keyword(s):  
Wind Speed ◽  
Trend Analysis ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
The United States ◽  
Homogeneity Test ◽  
Near Surface ◽  
Wind Speeds ◽  
Long Term Trends

Abstract Near-surface wind speeds recorded at 117 stations in Canada for the period from 1953 to 2006 were analyzed in this study. First, metadata and a logarithmic wind profile were used to adjust hourly wind speeds measured at nonstandard anemometer heights to the standard 10-m level. Monthly mean near-surface wind speed series were then derived and subjected to a statistical homogeneity test, with homogeneous monthly mean geostrophic wind (geowind) speed series being used as reference series. Homogenized monthly mean near-surface wind speed series were obtained by adjusting all significant mean shifts, using the results of the statistical test and modeling along with all available metadata, and were used to assess the long-term trends. This study shows that station relocation and anemometer height change are the main causes for discontinuities in the near-surface wind speed series, followed by instrumentation problems or changes, and observing environment changes. It also shows that the effects of artificial mean shifts on the results of trend analysis are remarkable, and that the homogenized near-surface wind speed series show good spatial consistency of trends, which are in agreement with long-term trends estimated from independent datasets, such as surface winds in the United States and cyclone activity indices and ocean wave heights in the region. These indicate success in the homogenization of the wind data. During the period analyzed, the homogenized near-surface wind speed series show significant decreases throughout western Canada and most parts of southern Canada (except the Maritimes) in all seasons, with significant increases in the central Canadian Arctic in all seasons and in the Maritimes in spring and autumn.

Characteristics of the wind drift layer and microscale breaking waves

2007 ◽  
Vol 573 ◽  
pp. 417-456 ◽  
Author(s):  
M. H. KAMRAN SIDDIQUI ◽  
MARK R. LOEWEN
Keyword(s):  
Wind Speed ◽  
Wave Breaking ◽  
Breaking Waves ◽  
Mean Velocity ◽  
Wind Drift ◽  
Near Surface ◽  
Wind Speeds ◽  
The Mean ◽  
Rate Of Dissipation ◽  
Drift Layer

An experimental study, investigating the mean flow and turbulence in the wind drift layer formed beneath short wind waves was conducted. The degree to which these flows resemble the flows that occur in boundary layers adjacent to solid walls (i.e. wall-layers) was examined. Simultaneous DPIV (digital particle image velocimetry) and infrared imagery were used to investigate these near-surface flows at a fetch of 5.5 m and wind speeds from 4.5 to 11 m s−1. These conditions produced short steep waves with dominant wavelengths from 6 cm to 18 cm. The mean velocity profiles in the wind drift layer were found to be logarithmic and the flow was hydrodynamically smooth at all wind speeds. The rate of dissipation of turbulent kinetic energy was determined to be significantly greater in magnitude than would occur in a comparable wall-layer. Microscale breaking waves were detected using the DPIV data and the characteristics of breaking and non-breaking waves were compared. The percentage of microscale breaking waves increased abruptly from 11% to 80% as the wind speed increased from 4.5 to 7.4 m s− and then gradually increased to 90% as the wind speed increased to 11 m s−. At a depth of 1 mm, the rate of dissipation was 1.7 to 3.2 times greater beneath microscale breaking waves compared to non-breaking waves. In the crest–trough region beneath microscale breaking waves, 40% to 50% of the dissipation was associated with wave breaking. These results demonstrated that the enhanced near-surface turbulence in the wind drift layer was the result of microscale wave breaking. It was determined that the rate of dissipation of turbulent kinetic energy due to wave breaking is a function of depth, friction velocity, wave height and phase speed as proposed by Terray et al. (1996). Vertical profiles of the rate of dissipation showed that beneath microscale breaking waves there were two distinct layers. Immediately beneath the surface, the dissipation decayed as ζ−0.7 and below this in the second layer it decayed as ζ−2. The enhanced turbulence associated with microscale wave breaking was found to extend to a depth of approximately one significant wave height. The only similarity between the flows in these wind drift layers and wall-layers is that in both cases the mean velocity profiles are logarithmic. The fact that microscale breaking waves were responsible for 40%–50% of the near-surface turbulence supports the premise that microscale breaking waves play a significant role in enhancing the transfer of gas and heat across the air–sea interface.

scholarly journals Natural variability in air–sea gas transfer efficiency of CO2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingxi Yang ◽  
Timothy J. Smyth ◽  
Vassilis Kitidis ◽  
Ian J. Brown ◽  
Charel Wohl ◽  
...  
Keyword(s):  
Wind Speed ◽  
Transfer Efficiency ◽  
Gas Transfer ◽  
Transfer Velocity ◽  
Concentration Difference ◽  
Near Surface ◽  
Wind Speeds ◽  
Naturally Occurring ◽  
Surface Active ◽  
The Mean

AbstractThe flux of CO2 between the atmosphere and the ocean is often estimated as the air–sea gas concentration difference multiplied by the gas transfer velocity (K660). The first order driver for K660 over the ocean is wind through its influence on near surface hydrodynamics. However, field observations have shown substantial variability in the wind speed dependencies of K660. In this study we measured K660 with the eddy covariance technique during a ~ 11,000 km long Southern Ocean transect. In parallel, we made a novel measurement of the gas transfer efficiency (GTE) based on partial equilibration of CO2 using a Segmented Flow Coil Equilibrator system. GTE varied by 20% during the transect, was distinct in different water masses, and related to K660. At a moderate wind speed of 7 m s−1, K660 associated with high GTE exceeded K660 with low GTE by 30% in the mean. The sensitivity of K660 towards GTE was stronger at lower wind speeds and weaker at higher wind speeds. Naturally-occurring organics in seawater, some of which are surface active, may be the cause of the variability in GTE and in K660. Neglecting these variations could result in biases in the computed air–sea CO2 fluxes.

scholarly journals Wind potential assessment over Morocco`s Marrakesh - Safi Region in 2021-2050 based on the RCM`s forecasts as part of the CORDEX-Africa project

2021 ◽  
pp. 34-41
Author(s):  
Y. El. Hadri ◽  
M. Slizhe ◽  
K. Sernytska
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Atlantic Coast ◽  
Surface Wind ◽  
Specific Power ◽  
Wind Flow ◽  
Model Calculations ◽  
Near Surface ◽  
Wind Speeds ◽  
Wind Potential

The purpose of the study is to determine the features of the spatial distribution of the wind speed in Marrakesh - Safi region in 2021-2050, as well as the distribution of the specific power of the wind flow at various altitudes above the earth’s surface to determine the wind class of the area in the coming decades. Currently, the region has two large wind farms: Essaouira-Amogdoul and Tarfayer. To assess the future state of climate in Marrakesh − Safi region, the results of calculations of regional climate models (RCM) of the CORDEX-Africa project for the period 2021-2050 were used. The RCM modeling was carried out for the region of Africa, in a rectangular coordinate system with a spatial resolution of ~ 44 km. Model calculation was performed taking into account the greenhouse gas concentration trajectory of RCP 4.5. As a result of simulation for the period 2021-2050, mean monthly values of wind speed "sfcWind" (m·s-1) and the daily maximum near-surface wind speed "sfcwindmax" (m·s-1) at 10 m height were obtained. Then, based on the wind speed rows, the values of the wind power density at a height of 50 m and 100 m were calculated. The results of model calculations of wind speed showed that the ensemble mean of wind speed for the period 2021-2050 will be from 3.8 m∙s-1 in Kelaat Sraghna Province to 7.2 m∙s-1 on the stretch of the Atlantic coast between Cap Sim and Cap Tafelny.The distribution over the territory will be influenced by proximity to the ocean, models predict the highest wind speeds on the coast, and when moving deep into the region, the wind speed will decrease.The analysis of simulation results showed that in the coastal areas of the region favorable conditions in terms of wind energy development will remain, and the highest wind speeds of the model are predicted on the Atlantic coast between Cap Sim and Cap Tafelny. By the size of the specific power of the wind flow, significant wind resources will have the territory lying along the coast from Cap Sim to the southern border of the region, and in the area of the power plants Essaouira-Amogdoul and Tarfayer models predict the conditions corresponding to the outstanding wind power class.

scholarly journals Local-scale wind speed features captured by seasonal forecasts

2021 ◽  
Author(s):  
Jaume Ramon ◽  
Llorenç Lledó ◽  
Pierre-Antoine Bretonnière ◽  
Margarida Samsó ◽  
Francisco J. Doblas-Reyes
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Surface Wind ◽  
Climate Modelling ◽  
Seasonal Forecasts ◽  
Economic Sectors ◽  
Skill Levels ◽  
Near Surface ◽  
Wind Speeds ◽  
Surface Climate

&lt;p&gt;Thanks to the recent advances in climate modelling, seasonal predictions are becoming more skilful at anticipating the future state of near-surface climate variables over extratropics. Nevertheless, such predictions are delivered on too coarse grids with horizontal resolutions of hundreds of kilometres so that local events happening at much finer scales cannot be reproduced. This is particularly noted for variables with high spatial variability like wind or precipitation: wind speeds can vary substantially over a few kilometres, from the top of a mountain to a valley floor. The differences in magnitude might be relevant for the deriving sectoral indicators, for example, within the wind industry and at a wind farm level.&lt;/p&gt;&lt;p&gt;This work presents and applies a downscaling methodology to generate fine-scale seasonal forecasts ---up to station scale--- for near-surface wind speeds in Europe. The hybrid forecasts are based on a statistical downscaling with a perfect prognosis approach, fitting a multi-linear regression with the four main Euro-Atlantic Teleconnections (EATC) indices as predictors. Seasonal predictions of EATC indices, which are predictable with relatively good skill levels, are later inserted into the multi-linear model. This results in skilful seasonal predictions of surface wind speeds. Indeed, the comparison of the hybrid forecasts against the dynamical forecasts of wind speed shows that the skill of such forecasts is not only maintained but also increased over most of Europe. The hybrid forecasts are generated at 17 locations where tall tower wind speed data are available and at a pan-European scale using the 100-metre wind speeds from the ERA5 reanalysis. Improving the accuracy of seasonal predictions is an essential step to inform weather-and-climate-vulnerable socio-economic sectors of seasonal anomalies a few months ahead.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document