scholarly journals Statistical Downscaling of Daily Wind Speed Variations

2014 ◽  
Vol 53 (3) ◽  
pp. 660-675 ◽  
Author(s):  
Megan C. Kirchmeier ◽  
David J. Lorenz ◽  
Daniel J. Vimont
Keyword(s):  
Wind Speed ◽  
Gamma Distribution ◽  
Large Scale ◽  
Probabilistic Method ◽  
Probabilistic Approach ◽  
Local Scale ◽  
Scale Parameters ◽  
Wind Speeds ◽  
Distribution Shape ◽  
Realistic Information

AbstractThis study presents the development of a method to statistically downscale daily wind speed variations in an extended Great Lakes region. A probabilistic approach is used, predicting a daily-varying probability density function (PDF) of local-scale daily wind speed conditioned on large-scale daily wind speed predictors. Advantages of a probabilistic method are that it provides realistic information on the variance and extremes in addition to information on the mean, it allows the autocorrelation of downscaled realizations to be tuned to match the autocorrelation of local-scale observations, and it allows flexibility in the use of the final downscaled product. Much attention is given to fitting the proper functional form of the PDF by investigating the observed local-scale wind speed distribution (predictand) as a function of the decile of the large-scale wind (predictor). It is found that the local-scale standard deviation and the local-scale shape parameter (from a gamma distribution) are nonconstant functions of the large-scale predictor. As such, a vector generalized linear model is developed to relate the large-scale and local-scale wind speeds. Maximum likelihood and cross validation are used to fit local-scale gamma distribution shape and scale parameters to the large-scale wind speed. The result is a daily-varying probability distribution of local-scale wind speed, conditioned on the large-scale wind speed.

scholarly journals Atmospheric Circulation Effects on Wind Speed Variability at Turbine Height

2007 ◽  
Vol 46 (4) ◽  
pp. 445-456 ◽  
Author(s):  
Katherine Klink
Keyword(s):  
Wind Speed ◽  
Pressure Gradient ◽  
Large Scale ◽  
Ground Level ◽  
The Arctic ◽  
Circulation Index ◽  
Regression Equations ◽  
Change Models ◽  
Wind Speeds ◽  
The North

Abstract Mean monthly wind speed at 70 m above ground level is investigated for 11 sites in Minnesota for the period 1995–2003. Wind speeds at these sites show significant spatial and temporal coherence, with prolonged periods of above- and below-normal values that can persist for as long as 12 months. Monthly variation in wind speed primarily is determined by the north–south pressure gradient, which captures between 22% and 47% of the variability (depending on the site). Regression on wind speed residuals (pressure gradient effects removed) shows that an additional 6%–15% of the variation can be related to the Arctic Oscillation (AO) and Niño-3.4 sea surface temperature (SST) anomalies. Wind speeds showed little correspondence with variation in the Pacific–North American (PNA) circulation index. The effect of the strong El Niño of 1997/98 on the wind speed time series was investigated by recomputing the regression equations with this period excluded. The north–south pressure gradient remains the primary determinant of mean monthly 70-m wind speeds, but with 1997/98 removed the influence of the AO increases at nearly all stations while the importance of the Niño-3.4 SSTs generally decreases. Relationships with the PNA remain small. These results suggest that long-term patterns of low-frequency wind speed (and thus wind power) variability can be estimated using large-scale circulation features as represented by large-scale climatic datasets and by climate-change models.

scholarly journals Factors Controlling Rain on Small Tropical Islands: Diurnal Cycle, Large-Scale Wind Speed, and Topography

2017 ◽  
Vol 74 (11) ◽  
pp. 3515-3532 ◽  
Author(s):  
Shuguang Wang ◽  
Adam H. Sobel
Keyword(s):  
Wind Speed ◽  
Gravity Waves ◽  
Large Scale ◽  
Sea Breeze ◽  
Flow Regimes ◽  
Prevailing Wind ◽  
Tropical Islands ◽  
Wind Speeds ◽  
Upward Deflection ◽  
Quantitative Impact

Abstract A set of idealized cloud-permitting simulations is performed to explore the influence of small islands on precipitating convection as a function of large-scale wind speed. The islands are situated in a long narrow ocean domain that is in radiative–convective equilibrium (RCE) as a whole, constraining the domain-average precipitation. The island occupies a small part of the domain, so that significant precipitation variations over the island can occur, compensated by smaller variations over the larger surrounding oceanic area. While the prevailing wind speeds vary over flat islands, three distinct flow regimes occur. Rainfall is greatly enhanced, and a local symmetric circulation is formed in the time mean around the island, when the prevailing large-scale wind speed is small. The rainfall enhancement over the island is much reduced when the wind speed is increased to a moderate value. This difference is characterized by a change in the mechanisms by which convection is forced. A thermally forced sea breeze due to surface heating dominates when the large-scale wind is weak. Mechanically forced convection, on the other hand, is favored when the large-scale wind is moderately strong, and horizontal advection of temperature reduces the land–sea thermal contrast that drives the sea breeze. Further increases of the prevailing wind speed lead to strong asymmetry between the windward and leeward sides of the island, owing to gravity waves that result from the land–sea contrast in surface roughness as well as upward deflection of the horizontal flow by elevated diurnal heating. Small-amplitude topography (up to 800-m elevation is considered) has a quantitative impact but does not qualitatively alter the flow regimes or their dependence on wind speed.

scholarly journals Influence of the Bermuda High on interannual variability of summertime ozone in the Houston-­Galveston-Brazoria region

2016 ◽  
Author(s):  
Yuxuan Wang ◽  
Beixi Jia ◽  
Sing-Chun Wang ◽  
Mark Estes ◽  
Lu Shen ◽  
...  
Keyword(s):  
Wind Speed ◽  
Interannual Variability ◽  
Large Scale ◽  
Gulf Coast ◽  
Surface Ozone ◽  
Circulation Pattern ◽  
Local Scale ◽  
Metropolitan Region ◽  
Southern Us ◽  
Mlr Model

Abstract. The Bermuda High (BH) quasi-permanent pressure system is the key large-scale circulation pattern influencing summertime weather over the eastern and southern US. Here we developed a multiple linear regression (MLR) model to characterize the effect of the BH on year-to-year changes of monthly-mean maximum daily 8-hour average (MDA8) ozone in the Houston-Galveston-Brazoria (HGB) metropolitan region during June, July and August (JJA). The BH indicators include the longitude of the BH western edge (BH-Lon), and the BH intensity index (BHI) defined as the pressure gradient along its western edge. Both BH-Lon and BHI are selected by MLR as significant predictors (p < 0.05) of the interannual (1990–2015) variability of the HGB-mean ozone throughout JJA, while local-scale meridional wind speed is selected as an additional predictor for August only. Local-scale temperature and zonal wind speed are not identified as important factors for any summer month. The best-fit MLR model can explain 61 %–72 % of the interannual variability of the HGB-mean summertime ozone over 1990–2015 and shows good performance in cross-validation (R2 higher than 0.48). The BH-Lon is the most important factor, which alone explains 38 %–48 % of such variability. The location and strength of the Bermuda High appears to control whether or not low-ozone maritime air from the Gulf of Mexico can enter southeastern Texas and affect air quality. This mechanism also applies to other coastal urban regions along the Gulf Coast (e.g. New Orleans, LA; Mobile, AL; and Pensacola, FL), suggesting that the BH circulation pattern can affect surface ozone variability through a large portion of the Gulf Coast.

scholarly journals Study on the Influence of Baseline Control System on the Fragility of Large-Scale Wind Turbine considering Seismic-Aerodynamic Combination

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Chenyang Yuan ◽  
Jing Li ◽  
Jianyun Chen ◽  
Qiang Xu ◽  
Yunfei Xie
Keyword(s):  
Control System ◽  
Wind Speed ◽  
Wind Turbine ◽  
Large Scale ◽  
Fragility Curves ◽  
Operating Conditions ◽  
Ground Acceleration ◽  
Wind Speeds ◽  
Speed Range ◽  
Wind Actions

The purpose of this paper is to explore the effect of the baseline control system (BCS) on the fragility of large-scale wind turbine when seismic and wind actions are considered simultaneously. The BCS is used to control the power output by regulating rotor speed and blade-pitch angle in real time. In this study, the fragility analysis was performed and compared between two models using different peak ground acceleration, wind speeds, and specified critical levels. The fragility curves with different wind conditions are obtained using the multiple stripe analysis (MSA) method. The calculation results show that the probability of exceedance specified critical level increases as the wind speed increases in model 1 without considering BCS, while does not have an obvious change in the below-rated wind speed range and has a significant decrease in the above-rated wind speed range in model 2 with considering BCS. The comparison depicts that if the BCS is neglected, the fragility of large-scale wind turbine will be underestimated in around the cut-in wind speed range and overestimated in the over-rated wind speed range. It is concluded that the BCS has a great effect on the fragility especially within the operating conditions when the rated wind speed is exceeded, and it should be considered when estimating the fragility of wind turbine subjected to the interaction of seismic and aerodynamic loads.

scholarly journals Influencing Mechanisms of a Crosswind on the Thermo-Hydraulic Characteristics of a Large-Scale Air-Cooled Heat Exchanger

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1128
Author(s):  
Yanqiang Kong ◽  
Weijia Wang ◽  
Zhitao Zuo ◽  
Lijun Yang ◽  
Xiaoze Du ◽  
...  
Keyword(s):  
Heat Exchanger ◽  
Wind Speed ◽  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Large Scale ◽  
Air Mass ◽  
Heat Rejection ◽  
Wind Speeds ◽  
Air Cooled Heat Exchanger

For the large scale air-cooled heat exchanger of a natural draft dry cooling system (NDDCS) in power plants, its thermo-flow characteristics are basically dominated by crosswinds. Unfortunately however, the detailed mechanisms of the crosswind effects have yet to be fully uncovered. Therefore, in this research, the local flow and heat transfer performances of the cooling deltas, which are also termed as the fundamental cells of the large-scale air-cooled heat exchanger, are specifically investigated with full consideration for the cell structure and the water-side temperature distribution at various wind speeds. A 3D CFD method with a realizable k-ε turbulence model, heat exchanger model, and porous media model is developed, and the accuracy and credibility of the numerical model are experimentally validated. With the numerical simulation, the overall 3D outlet air temperature of the large-scale air-cooled heat exchanger, and the corresponding local air velocity and temperature fields of the cooling deltas are qualitatively analyzed. Furthermore, the air-mass flow rate and heat rejection are also quantitatively studied at both the global and local views. The results depict that with an increase in the wind speed, the air mass flow rate and heat rejection will increase greatly for the frontal deltas; however, they will drop dramatically for the middle-front deltas. As for the middle- as well as the middle-rear deltas, the thermo-flow performances vary markedly at various wind speeds, which behave in the most deteriorated manner at a wind speed of 12 m/s. The rear deltas show the best thermo-flow performances at a wind speed of 12 m/s, but the worst at 16 m/s. A detailed analysis of the variable fields for each cooling delta may contribute to the performance improvement of the large-scale air-cooled heat exchanger of NDDCS.

scholarly journals Hydrological response unit-based blowing snow modelling over an alpine ridge

2010 ◽  
Vol 7 (1) ◽  
pp. 1167-1208 ◽  
Author(s):  
M. K. MacDonald ◽  
J. W. Pomeroy ◽  
A. Pietroniro
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Large Scale ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Hydrological Response ◽  
Wind Speeds ◽  
Response Unit ◽  
Winter Snow ◽  
Hydrological Response Unit

Abstract. Snow redistribution by wind and the resulting accumulation regimes were simulated for two winters over an alpine ridge transect located in the Canada Rocky Mountains. Simulations were performed using physically based blowing snow and snowmelt models. A hydrological response unit (HRU)-based spatial discretization was used rather than a more computationally expensive fully-distributed one. The HRUs were set up to follow an aerodynamic sequence, whereby eroded snow was transported from windswept, upwind HRUs to drift accumulating, downwind HRUs. HRUs were selected by examining snow accumulation patterns from manual snow depth measurements. Simulations were performed using two sets of wind speed forcing: (1) station observed wind speed, and (2) modelled wind speed from a widely applied empirical, terrain-based windflow model. Best results were obtained when using the site meteorological station wind speed data. The windflow model performed poorly when comparing the magnitude of modelled and observed wind speeds, though over-winter snow accumulation results obtained when using the modelled wind speeds were reasonable. However, there was a notable discrepancy (17%) between blowing snow sublimation quantities estimated when using the modelled and observed wind speeds. As a result, the end-of-winter snow accumulation was considerably underestimated (32%) when using the modelled wind speeds. That snow redistribution by wind can be adequately simulated in computationally efficient HRUs over this alpine ridge has important implications for representing snow transport in large-scale hydrology models and land surface schemes. Snow redistribution by wind was shown to significantly impact snow accumulation regimes in mountainous environments as snow accumulation was reduced to less than one-third of snowfall on windswept landscapes and nearly doubled in certain lee slope and treeline areas. Blowing snow sublimation losses were shown to be significant (approximately one-quarter of snowfall or greater).

scholarly journals Centennial-scale variability of terrestrial near-surface wind speed over China from reanalysis

2021 ◽  
pp. 1-52
Author(s):  
Cheng Shen ◽  
Jinlin Zha ◽  
Jian Wu ◽  
Deming Zhao
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Stepwise Regression ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Wind Speeds ◽  
Ocean Atmosphere ◽  
Forward Stepwise ◽  
Strong Winds

AbstractInvestigations of variations and causes of near-surface wind speed (NWS) further understanding of the atmospheric changes and improve the ability of climate analysis and projections. NWS varies on multiple temporal scales; however, the centennial-scale variability in NWS and associated causes over China remains unknown. In this study, we employ the European Centre for Medium-Range Weather Forecasts (ECMWF) twentieth century reanalysis (ERA-20C) to study the centennial-scale changes in NWS from 1900–2010. Meanwhile, a forward stepwise regression algorithm is used to reveal the relationships between NWS and large-scale ocean-atmosphere circulations. The results show three unique periods in annual mean NWS over China from 1900–2010. The annual mean NWS displayed a decreasing trend of -0.87% decade-1 and -11.75% decade-1 from 1900–1925 and 1957–2010, respectively, which were caused by the decreases in the days with strong winds, with trends of -6.64 and -4.66 days decade-1, respectively. The annual mean NWS showed an upward trend of 55.47% decade-1 from 1926–1956, which was caused by increases in the days with moderate (0.43 days decade-1) and strong winds (23.55 days decade-1). The reconstructed wind speeds based on forward stepwise regression algorithm matched well with the original wind speeds; therefore, the decadal changes in NWS over China at centennial-scale were mainly induced by large-scale ocean-atmosphere circulations, with the total explanation power of 66%. The strongest explanation power was found in winter (74%), and the weakest explanation power was found in summer (46%).

scholarly journals Evaluation of ERA5, MERRA-2, COSMO-REA6, NEWA and AROME to simulate wind power production over France

2020 ◽  
Vol 17 ◽  
pp. 63-77 ◽  
Author(s):  
Bénédicte Jourdier
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Farm ◽  
Regional Scale ◽  
Power Production ◽  
Local Scale ◽  
Electric System ◽  
Wind Speeds ◽  
Diurnal Cycles ◽  
Nwp Model

Abstract. As variable renewable energies are developing, their impacts on the electric system are growing. To anticipate these impacts, prospective studies may use wind power production simulations in the form of 1 h or 30 min time series that are often based on reanalysis wind-speed data. The purpose of this study is to assess how several wind-speed datasets are performing when used to simulate wind-power production at the local scale, when no observation is available to use bias correction methods. The study evaluates two global reanalysis (MERRA-2 from NASA and ERA5 from ECMWF), two high-resolution models (COSMO-REA6 reanalysis from DWD, AROME NWP model from Météo-France) and the New European Wind Atlas mesoscale data. The study is conducted over continental France. In a first part, wind-speed measurements (between 55 and 100 m above ground) at eight locations are directly compared to modelled wind speeds. In a second part, 30 min wind-power productions are simulated for every wind farm in France and compared to two open datasets of observed production published by the distribution and transmission system operators, either at the local scale in terms of annual bias, or aggregated at the regional scale, in terms of bias, correlations and diurnal cycles. ERA5 is very skilled, despite its low resolution compared to the regional models, but it underestimates wind speeds, especially in mountainous areas. AROME and COSMO-REA6 have better skills in complex areas and have generally low biases. MERRA-2 and NEWA have large biases and overestimate wind speeds especially at night. Several problems affecting diurnal cycles are detected in ERA5 and COSMO-REA6.

scholarly journals Time Series Analysis and Forecasting for Wind Speeds Using Support Vector Regression Coupled with Artificial Intelligent Algorithms

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Ping Jiang ◽  
Shanshan Qin ◽  
Jie Wu ◽  
Beibei Sun
Keyword(s):  
Wind Speed ◽  
Support Vector Regression ◽  
Wind Turbines ◽  
Large Scale ◽  
Wind Farm ◽  
Hybrid Models ◽  
Parameter Determination ◽  
Support Vector ◽  
Short Term ◽  
Wind Speeds

Wind speed/power has received increasing attention around the earth due to its renewable nature as well as environmental friendliness. With the global installed wind power capacity rapidly increasing, wind industry is growing into a large-scale business. Reliable short-term wind speed forecasts play a practical and crucial role in wind energy conversion systems, such as the dynamic control of wind turbines and power system scheduling. In this paper, an intelligent hybrid model for short-term wind speed prediction is examined; the model is based on cross correlation (CC) analysis and a support vector regression (SVR) model that is coupled with brainstorm optimization (BSO) and cuckoo search (CS) algorithms, which are successfully utilized for parameter determination. The proposed hybrid models were used to forecast short-term wind speeds collected from four wind turbines located on a wind farm in China. The forecasting results demonstrate that the intelligent hybrid models outperform single models for short-term wind speed forecasting, which mainly results from the superiority of BSO and CS for parameter optimization.

scholarly journals Influence of the Bermuda High on interannual variability of summertime ozone in the Houston–Galveston–Brazoria region

2016 ◽  
Vol 16 (23) ◽  
pp. 15265-15276 ◽  
Author(s):  
Yuxuan Wang ◽  
Beixi Jia ◽  
Sing-Chun Wang ◽  
Mark Estes ◽  
Lu Shen ◽  
...  
Keyword(s):  
Wind Speed ◽  
Interannual Variability ◽  
Large Scale ◽  
Gulf Coast ◽  
Surface Ozone ◽  
Circulation Pattern ◽  
Local Scale ◽  
Metropolitan Region ◽  
Southern Us ◽  
Mlr Model

Abstract. The Bermuda High (BH) quasi-permanent pressure system is the key large-scale circulation pattern influencing summertime weather over the eastern and southern US. Here we developed a multiple linear regression (MLR) model to characterize the effect of the BH on year-to-year changes in monthly-mean maximum daily 8 h average (MDA8) ozone in the Houston–Galveston–Brazoria (HGB) metropolitan region during June, July, and August (JJA). The BH indicators include the longitude of the BH western edge (BH-Lon) and the BH intensity index (BHI) defined as the pressure gradient along its western edge. Both BH-Lon and BHI are selected by MLR as significant predictors (p < 0.05) of the interannual (1990–2015) variability of the HGB-mean ozone throughout JJA, while local-scale meridional wind speed is selected as an additional predictor for August only. Local-scale temperature and zonal wind speed are not identified as important factors for any summer month. The best-fit MLR model can explain 61–72 % of the interannual variability of the HGB-mean summertime ozone over 1990–2015 and shows good performance in cross-validation (R2 higher than 0.48). The BH-Lon is the most important factor, which alone explains 38–48 % of such variability. The location and strength of the Bermuda High appears to control whether or not low-ozone maritime air from the Gulf of Mexico can enter southeastern Texas and affect air quality. This mechanism also applies to other coastal urban regions along the Gulf Coast (e.g., New Orleans, LA, Mobile, AL, and Pensacola, FL), suggesting that the BH circulation pattern can affect surface ozone variability through a large portion of the Gulf Coast.

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