Surface wind speed(SWS)not only plays a crucial role in regulating the Earth's energy and hydrological cycle,but also is an important source of sustainable renewable energy.This study assesses the credibility of s...Surface wind speed(SWS)not only plays a crucial role in regulating the Earth's energy and hydrological cycle,but also is an important source of sustainable renewable energy.This study assesses the credibility of sws in three reanalyses(ERA5,MERRA2,and JRA-55)in East Asia using both satellite and in-situ observations.Results show all three reanalyses can capture the spatial pattern of swS as in observations,yet there are notable differences in magnitude.On land,ERA5 and MERRA2 overestimate the SWS by about 0.6 and 1.5 m s^(-1),respectively,whereas JRA-55 underestimates it.The biases over the oceans are opposite to those on land and are relatively small due to the assimilation of observations of oceanic surface winds.Overall,JRA-55 and ERA5 offer better estimates of seasonal means and variances of SWS than MERRA2.The observed SWS shows a negative trend of-0.08 m s^(-1)/10 yr on land and a positive trend of 0.09 m s^(-1)/10 yr in the western North Pacific.Only JRA-55 shows similar trends to observations over both land and ocean,while ERA5 and MERRA2 show varying degrees of deviation from the observations.Further investigation shows that there is a strong link between the trend of SWS and that of the large-scale circulation,and that a large part of the SwS trend can be attributed to changes in large-scale circulations.展开更多
As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wi...As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wind speed correlation,a multi-scenario PLF calculation method that combines random sampling and segmented discrete wind farm power was proposed.Firstly,based on constructing discrete scenes of wind farms,the Nataf transform is used to handle the correlation between wind speeds.Then,the random sampling method determines the output probability of discrete wind power scenarios when wind speed exhibits correlation.Finally,the PLF calculation results of each scenario areweighted and superimposed following the total probability formula to obtain the final power flow calculation result.Verified in the IEEE standard node system,the absolute percent error(APE)for the mean and standard deviation(SD)of the node voltages and branch active power are all within 1%,and the average root mean square(AMSR)values of the probability curves are all less than 1%.展开更多
Previous studies have indicated a global reversal of near-surface wind speeds from a declining trend to an increasing trend around 2010;however,it remains unclear whether upper-air wind speeds exhibit a similar revers...Previous studies have indicated a global reversal of near-surface wind speeds from a declining trend to an increasing trend around 2010;however,it remains unclear whether upper-air wind speeds exhibit a similar reversal.This study evaluates reanalysis products using surface and radiosonde observations to analyze upper-air wind speed variations in the Northern Hemisphere,focusing on their seasonal and latitudinal differences.Results demonstrate that JRA-55 effectively captures wind speed variations in the Northern Hemisphere.Notably,upper-air wind speeds over land experienced a reversal in winter 2010 with significant latitudinal differences.The trend reversal of upper wind speed between the midlatitudes and subtropics presents a dipole pattern.From 1990 to 2010,upper-air wind speeds in the midlatitudes(40°-70°N)significantly declined,while the subtropical zone(20°-40°N)displayed an opposite trend.However,during 2010-2020,wind speeds in the midlatitudes shifted to a significant positive trend,whereas the subtropics experienced a significant negative trend.The variations in Northern Hemisphere winter wind speeds can be attributed to changes in low-level baroclinicity driven by tropical diabatic heating and midlatitude transient eddy feedback.Enhanced diabatic heating and weakened eddy feedback during 1990-2010 contributed to reduced wind speeds in the midlatitudes and increased speeds in the subtropics,while reduced diabatic heating and strengthened eddy feedback during 2010-2020 resulted in increased wind speeds in the midlatitudes and decreased speeds in the subtropics.The reversal of upper-air wind speeds could affect surface wind speeds by downward momentum transfer,which could contribute to the reversal of surface wind speeds.展开更多
Sea-surface wind is a vital meteorological element in marine activities and climate research.This study proposed the spectral attention enhanced multidimensional feature fusion convolutional long short-term memory(LST...Sea-surface wind is a vital meteorological element in marine activities and climate research.This study proposed the spectral attention enhanced multidimensional feature fusion convolutional long short-term memory(LSTM)network(SAMFF-Conv-LSTM),a novel approach for sea-surface wind-speed prediction that emphasizes the temporal characteristics of data samples.The model incorporates the Fourier transform to extract time-and frequency-domain features from wave and wind variables.For the 12 h prediction,the SAMFF-ConvLSTM achieved a correlation coefficient of 0.960 and a root mean square error(RMSE)of 1.350 m/s,implying a high prediction accuracy.For the 24 h prediction,the RMSE of the SAMFF-ConvLSTM was reduced by 38.11%,14.26%,and 13.36%compared with those of the convolutional neural network,gated recurrent units,and convolutional LSTM(ConvLSTM),respectively.These results confirm the superior reliability and accuracy of the SAMFF-ConvLSTM over traditional models in theoretical and practical applications.展开更多
Due to global warming and diminishing ice cover in Arctic regions,the northern sea route(NSR)has attracted increasing attention in recent years.Extreme cold temperatures and high wind speeds in Arctic regions present ...Due to global warming and diminishing ice cover in Arctic regions,the northern sea route(NSR)has attracted increasing attention in recent years.Extreme cold temperatures and high wind speeds in Arctic regions present substantial risks to vessels operating along the NSR.Consequently,analyzing extreme temperature and wind speed values along the NSR is essential for ensuring maritime operational safety in the region.This study analyzes wind and temperature data spanning 40 years,from 1981 to 2020,at four representative sites along the NSR for extreme value analysis.The average conditional exceedance rate(ACER)method and the Gumbel method are employed to estimate extreme wind speed and air temperature at these sites.Comparative analysis reveals that the ACER method provides higher accuracy and lower uncertainty in estimations.The predicted extreme wind speed for a 100-year return period is 30.36 m/s,with a minimum temperature of-56.66°C,varying across the four sites.Furthermore,the study presents extreme values corresponding to each return period,providing temperature extremes as a basis for guiding steel thickness specifications.These findings provide valuable reference for designing polar vessels and offshore structures,contributing to enhanced engineering standards for Arctic conditions.展开更多
Accurate wind speed measurements on maritime vessels are crucial for weather forecasting,sea state prediction,and safe navigation.However,vessel motion and challenging environmental conditions often affect measurement...Accurate wind speed measurements on maritime vessels are crucial for weather forecasting,sea state prediction,and safe navigation.However,vessel motion and challenging environmental conditions often affect measurement precision.To address this issue,this study proposes an innovative framework for correcting and predicting shipborne wind speed.By integrating a main network with a momentum updating network,the proposed framework effectively extracts features from the time and frequency domains,thereby allowing for precise adjustments and predictions of shipborne wind speed data.Validation using real sensor data collected at the Qingdao Oceanographic Institute demonstrates that the proposed method outperforms existing approaches in single-and multi-step predictions compared to existing methods,achieving higher accuracy in wind speed forecasting.The proposed innovative approach offers a promising direction for future validation in more realistic maritime onboard scenarios.展开更多
A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical dis...A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical distribution of the two variables may show multimodal characteristics.In this work,a finite mixture bivariate statistical model was designed to describe the statistical properties,which is composed of several components,each with a Weibull distribution and a normal distribution for wind speed and wind shear,respectively,with a Gaussian copula to describe the dependency structure between the two variables.To confirm the developed model,reanalysis data from six positions in the coastal sea areas of China were used.Our results disclosed that the developed joint statistical model can accurately capture the different multimodal structures presented in all the bivariate samples under mixed atmospheric conditions,giving acceptable predictions of the joint probability distributions.Proper consideration of wind shear coefficient variation is crucial in estimating height-dependent wind resource characteristics.Importantly,unlike traditional methods that are limited to specific hub heights,the model developed here can estimate wind energy potential across different hub heights,enhancing the economic viability assessment of wind power projects.展开更多
The successful launch of the Cyclone Global Navigation Satellite System(CYGNSS)has opened an unprecedented opportunity for rapid observation of Wind Speed(WS)across vast oceanic regions.However,considerable debate per...The successful launch of the Cyclone Global Navigation Satellite System(CYGNSS)has opened an unprecedented opportunity for rapid observation of Wind Speed(WS)across vast oceanic regions.However,considerable debate persists over the choice of input feature parameters for WS retrieval models based on CYGNSS data,and enhancing the accuracy of WS retrieval is a focal point of current research.To address the aforementioned problems,this study establishes a comprehensive CYGNSS wind speed retrieval feature parameter set through an in-depth analysis of CYGNSS data,thereby providing a reference and basis for selecting input features for WS retrieval models.Through this analysis,we identified three crucial observational features:the normalized bistatic radar cross section,leading edge slope,and signal-to-noise ratio.Using these features,we developed a WS retrieval model based on the geophysical model function for CYGNSS data.Furthermore,acknowledging the intrinsic interconnection between wind and wave dynamics,we incorporate significant wave height into the WS retrieval model to further improve the WS retrieval accuracy.Comparative assessments with datasets from the European Centre for Medium-Range Weather Forecasts,the Chinese-French Oceanography Satellite Scatterometer,and buoy WS data underscore the high accuracy of our model,demonstrating its utility as a valuable tool for research in ocean dynamics and marine environmental prediction.展开更多
Affected by the Super Typhoon“Mangkhut,”a total of five base towers of a transmission line in the mountainous area of China collapsed.In this paper,a mathematical model is established based on the Shuttle Radar Topo...Affected by the Super Typhoon“Mangkhut,”a total of five base towers of a transmission line in the mountainous area of China collapsed.In this paper,a mathematical model is established based on the Shuttle Radar Topography Mission(SRTM)data near the accident tower.The measured wind speed in the plain area under the mountain is used as the calculation boundary condition.The wind speed at the top of the mountain is calculated by using a numerical simulation method.The design wind speed and calculated wind speed at the tower site are compared,and the influence of wind speed on tower position in this wind disaster accident is analyzed.展开更多
The maintenance of sand-fixing vegetation is important for the stability of artificial sand-fixing systems in which seed dispersal plays a key role.Based on field wind tunnel experiments using 11 common plant species ...The maintenance of sand-fixing vegetation is important for the stability of artificial sand-fixing systems in which seed dispersal plays a key role.Based on field wind tunnel experiments using 11 common plant species on the southeastern edge of the Tengger Desert,China,we studied the secondary seed dispersal in the fixed and semi-fixed sand dunes as well as in the mobile dunes in order to understand the limitations of vegetation regeneration and the maintenance of its stability.Our results indicated that there were significant variations among the selected 11 plant species in the threshold of wind speed(TWS).The TWS of Caragana korshinskii was the highest among the 11 plant species,whereas that of Echinops gmelinii was the lowest.Seed morphological traits and underlying surface could generally explain the TWS.During the secondary seed dispersal processes,the proportions of seeds that did not disperse(no dispersal)and only dispersed over short distance(short-distance dispersal within the wind tunnel test section)were significantly higher than those of seeds that were buried(including lost seeds)and dispersed over long distance(long-distance dispersal beyond the wind tunnel test section).Compared with other habitats,the mobile dunes were the most difficult places for secondary seed dispersal.Buried seeds were the easiest to be found in the semi-fixed sand dunes,whereas fixed sand dunes were the best sites for seeds that dispersed over long distance.The results of linear mixed models showed that after controlling the dispersal distance,smaller and rounder seeds dispersed farther.Shape index and wind speed were the two significant influencing factors on the burial of seeds.The explanatory power of wind speed,underlying surface,and seed morphological traits on the seeds that did not disperse and dispersed over short distance was far greater than that on the seeds that were buried and dispersed over long distance,implying that the processes and mechanisms of burial and long-distance dispersal are more complex.In summary,most seeds in the study area either did not move,were buried,or dispersed over short distance,promoting local vegetation regeneration.展开更多
Optical remote sensing has been widely used to study internal solitary waves(ISWs).Wind speed has an important effect on ISW imaging of optical remote sensing.The light and dark bands of ISWs cannot be observed by opt...Optical remote sensing has been widely used to study internal solitary waves(ISWs).Wind speed has an important effect on ISW imaging of optical remote sensing.The light and dark bands of ISWs cannot be observed by optical remote sensing when the wind is too strong.The relationship between the characteristics of ISWs bands in optical remote sensing images and the wind speed is still unclear.The influence of wind speeds on the characteristics of the ISWs bands is investigated based on the physical simulation experiments with the wind speeds of 1.6,3.1,3.5,3.8,and 3.9 m/s.The experimental results show that when the wind speed is 3.9 m/s,the ISWs bands cannot be observed in optical remote sensing images with the stratification of h_(1)∶h_(2)=7∶58,ρ_(1)∶ρ_(2)=1∶1.04.When the wind speeds are 3.1,3.5,and 3.8 m/s,which is lower than 3.9 m/s,the ISWs bands can be obtained in the simulated optical remote sensing image.The location of the band’s dark and light extremum and the band’s peak-to-peak spacing are almost not affected by wind speed.More-significant wind speeds can cause a greater gray difference of the light-dark bands.This provided a scientific basis for further understanding of ISW optical remote sensing imaging.展开更多
Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting ...Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting wind speed accurately is difficult.A new hybrid deep learning model based on empirical wavelet transform,recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper.The empirical wavelet transformation is applied to decompose the original wind speed series.The long short term memory network and the Elman neural network are adopted to predict low-frequency and high-frequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy.The error correction strategy based on deep long short term memory network is developed to modify the prediction errors.Four actual wind speed series are utilized to verify the effectiveness of the proposed model.The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction.展开更多
Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SM...Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.展开更多
Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 ...Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.展开更多
Amid the randomness and volatility of wind speed, an improved VMD-BP-CNN-LSTM model for short-term wind speed prediction was proposed to assist in power system planning and operation in this paper. Firstly, the wind s...Amid the randomness and volatility of wind speed, an improved VMD-BP-CNN-LSTM model for short-term wind speed prediction was proposed to assist in power system planning and operation in this paper. Firstly, the wind speed time series data was processed using Variational Mode Decomposition (VMD) to obtain multiple frequency components. Then, each individual frequency component was channeled into a combined prediction framework consisting of BP neural network (BPNN), Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) after the execution of differential and normalization operations. Thereafter, the predictive outputs for each component underwent integration through a fully-connected neural architecture for data fusion processing, resulting in the final prediction. The VMD decomposition technique was introduced in a generalized CNN-LSTM prediction model;a BPNN model was utilized to predict high-frequency components obtained from VMD, and incorporated a fully connected neural network for data fusion of individual component predictions. Experimental results demonstrated that the proposed improved VMD-BP-CNN-LSTM model outperformed other combined prediction models in terms of prediction accuracy, providing a solid foundation for optimizing the safe operation of wind farms.展开更多
The Pearl River Estuary(PRE)is one of China’s busiest shipping hubs and fishery production centers,as well as a region with abundant island tourism and wind energy resources,which calls for accurate short-term wind f...The Pearl River Estuary(PRE)is one of China’s busiest shipping hubs and fishery production centers,as well as a region with abundant island tourism and wind energy resources,which calls for accurate short-term wind forecasts.First,this study evaluated three operational numerical models,i.e.,ECMWF-EC,NCEP-GFS,and CMA-GD,for their ability to predict short-term wind speed over the PRE against in-situ observations during 2018-2021.Overall,ECMWF-EC out-performs other models with an average RMSE of 2.24 m s^(-1)and R of 0.57,but the NCEP-GFS performs better in the case of strong winds.Then,various bias correction and multi-model ensemble(MME)methods are used to perform the deterministic post-processing using a local and lead-specific scheme.Two-factor model output statistics(MOS2)is the optimal bias correction method for reducing(increasing)the overall RMSE(R)to 1.62(0.70)m s^(-1),demonstrating the benefits of considering both initial and lead-specific information.Intercomparison of MME results reveals that Multiple linear regression(MLR)presents superior skills,followed by random forest(RF),but it is slightly inferior to MOS2,particularly for the first few forecasting hours.Furthermore,the incorporation of additional features in MLR reduces the overall RMSE to 1.53 m s^(-1)and increases R to 0.74.Similarly,RF presents comparable results,and both outperform MOS2 in terms of correcting their deficiencies at the first few lead hours and limiting the error growth rate.Despite the satisfactory skill of deterministic post-processing techniques,they are unable to achieve a balanced performance between mean and extreme statistics.This highlights the necessity for further development of probabilistic forecasts.展开更多
Based on the data of the wind speed from 20 m meteorological tower and PM10 mass concentration in Zhurihe region from January of 2005 to April of 2006,the evolution characteristics of wind speed profile in near surfac...Based on the data of the wind speed from 20 m meteorological tower and PM10 mass concentration in Zhurihe region from January of 2005 to April of 2006,the evolution characteristics of wind speed profile in near surface layer and PM10 in three representative dust weather processes (dust storm,blowing sand and floating dust) were analyzed.The results showed that wind speed was higher during dust storm and blowing sand with remarkable vertical gradient.The speed in floating dust was relatively lower and increased during the whole process.In general,wind speed after dust weather was smaller with respect to that before the event.The average mass concentrations of PM10 in the processes of dust storm,blowing sand and floating dust were in the ranges of 5 436.38-10 000,1 799.49-4 006.06 and 1 765.53 μg/m3,respectively.展开更多
In grassland ecosystems,the aerodynamic roughness(Z0)and frictional wind speed(u*)contribute to the aerodynamic impedance of the grassland canopy.Thus,they are often used in the studies of wind erosion and evapotransp...In grassland ecosystems,the aerodynamic roughness(Z0)and frictional wind speed(u*)contribute to the aerodynamic impedance of the grassland canopy.Thus,they are often used in the studies of wind erosion and evapotranspiration.However,the effect of wind speed and grazing measures on the aerodynamic impedance of the grassland canopy has received less analysis.In this study,we monitored wind speeds at multiple heights in grazed and grazing-prohibited grasslands for 1 month in 2021,determined the transit wind speed at 2.0 m height by comparing wind speed differences at the same height in both grasslands,and divided these transit wind speeds at intervals of 2.0 m/s to analyze the effect of the transit wind speed on the relationship among Z0,u*,and wind speed within the grassland canopy.The results showed that dividing the transit wind speeds into intervals has a positive effect on the logarithmic fit of the wind speed profile.After dividing the transit wind speeds into intervals,the wind speed at 0.1 m height(V0.1)gradually decreased with the increase of Z0,exhibiting three distinct stages:a sharp change zone,a steady change zone,and a flat zone;while the overall trend of u*increased first and then decreased with the increase of V0.1.Dividing the transit wind speeds into intervals improved the fitting relationship between Z0 and V0.1 and changed their fitting functions in grazed and grazing-prohibited grasslands.According to the computational fluid dynamic results,we found that the number of tall-stature plants has a more significant effect on windproof capacity than their height.The results of this study contribute to a better understanding of the relationship between wind speed and the aerodynamic impedance of vegetation in grassland environments.展开更多
In the study a fire and fire environment model is set up and by using PHEONICS software 3 cases of surface fires are studied. The results fit the experimental studies well generally. The simulation reveals that (1) Th...In the study a fire and fire environment model is set up and by using PHEONICS software 3 cases of surface fires are studied. The results fit the experimental studies well generally. The simulation reveals that (1) The wind speed fields in front of fire front generally can be divided into 3 zones and there is always an eddy immediately at the corner between just in front of the fire and the ground. (2) The shape and dimension of the division of the 3 zones is mainly decided by slope angle and ambient wind speed given fire line intensity. (3) There exits an upwind zone in front of fire front. Ambient wind speeds have little effect on the magnitude of the upwind speed when slope angle is 0. But when the slope angle is negative, the upwind is apparently stronger.展开更多
Comparing and analyzing the difference between automatic-observed and manual-observed wind speed based on the wind speed parallel observations in two methods, we find that many elements can influence the difference be...Comparing and analyzing the difference between automatic-observed and manual-observed wind speed based on the wind speed parallel observations in two methods, we find that many elements can influence the difference between automatic-observed and manual-observed wind speed, including the levels of speed wind, observation instruments and different regions. According to these elements, correction has been conducted, and find that the correction according to the level of wind speed has the best correction effect.展开更多
基金supported by the National Natural Science Foundation of China[grant numbers 42361144708,42205041,and 42175165]a scientific research project of the Shanghai Investigation,Design and Research Institute Co.,Ltd.[grant number 2023CN(83)-001]the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”(EarthLab).
文摘Surface wind speed(SWS)not only plays a crucial role in regulating the Earth's energy and hydrological cycle,but also is an important source of sustainable renewable energy.This study assesses the credibility of sws in three reanalyses(ERA5,MERRA2,and JRA-55)in East Asia using both satellite and in-situ observations.Results show all three reanalyses can capture the spatial pattern of swS as in observations,yet there are notable differences in magnitude.On land,ERA5 and MERRA2 overestimate the SWS by about 0.6 and 1.5 m s^(-1),respectively,whereas JRA-55 underestimates it.The biases over the oceans are opposite to those on land and are relatively small due to the assimilation of observations of oceanic surface winds.Overall,JRA-55 and ERA5 offer better estimates of seasonal means and variances of SWS than MERRA2.The observed SWS shows a negative trend of-0.08 m s^(-1)/10 yr on land and a positive trend of 0.09 m s^(-1)/10 yr in the western North Pacific.Only JRA-55 shows similar trends to observations over both land and ocean,while ERA5 and MERRA2 show varying degrees of deviation from the observations.Further investigation shows that there is a strong link between the trend of SWS and that of the large-scale circulation,and that a large part of the SwS trend can be attributed to changes in large-scale circulations.
基金supported by Basic Science Research Program through the National Natural Science Foundation of China(Grant No.61867003).
文摘As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wind speed correlation,a multi-scenario PLF calculation method that combines random sampling and segmented discrete wind farm power was proposed.Firstly,based on constructing discrete scenes of wind farms,the Nataf transform is used to handle the correlation between wind speeds.Then,the random sampling method determines the output probability of discrete wind power scenarios when wind speed exhibits correlation.Finally,the PLF calculation results of each scenario areweighted and superimposed following the total probability formula to obtain the final power flow calculation result.Verified in the IEEE standard node system,the absolute percent error(APE)for the mean and standard deviation(SD)of the node voltages and branch active power are all within 1%,and the average root mean square(AMSR)values of the probability curves are all less than 1%.
基金supported by the National Natural Science Foundation of China[grant numbers U2442207,42122034,42075043,and 42330609]the Youth Innovation Promotion Association[grant number 2021427]+2 种基金the West Light Foundation[grant number xbzgzdsys-202409]of the Chinese Academy of Sciencesthe Key Talent Projects in Gansu Provincethe Central Guidance Fund for Local Science and Technology Development Projects in Gansu Province[grant number 24ZYQA031].
文摘Previous studies have indicated a global reversal of near-surface wind speeds from a declining trend to an increasing trend around 2010;however,it remains unclear whether upper-air wind speeds exhibit a similar reversal.This study evaluates reanalysis products using surface and radiosonde observations to analyze upper-air wind speed variations in the Northern Hemisphere,focusing on their seasonal and latitudinal differences.Results demonstrate that JRA-55 effectively captures wind speed variations in the Northern Hemisphere.Notably,upper-air wind speeds over land experienced a reversal in winter 2010 with significant latitudinal differences.The trend reversal of upper wind speed between the midlatitudes and subtropics presents a dipole pattern.From 1990 to 2010,upper-air wind speeds in the midlatitudes(40°-70°N)significantly declined,while the subtropical zone(20°-40°N)displayed an opposite trend.However,during 2010-2020,wind speeds in the midlatitudes shifted to a significant positive trend,whereas the subtropics experienced a significant negative trend.The variations in Northern Hemisphere winter wind speeds can be attributed to changes in low-level baroclinicity driven by tropical diabatic heating and midlatitude transient eddy feedback.Enhanced diabatic heating and weakened eddy feedback during 1990-2010 contributed to reduced wind speeds in the midlatitudes and increased speeds in the subtropics,while reduced diabatic heating and strengthened eddy feedback during 2010-2020 resulted in increased wind speeds in the midlatitudes and decreased speeds in the subtropics.The reversal of upper-air wind speeds could affect surface wind speeds by downward momentum transfer,which could contribute to the reversal of surface wind speeds.
基金supported by the National Natural Science Foundation(No.42176020)the Open Research Fund of State Key Laboratory of Target Vulnerability Assessment(No.YSX2024KFYS001)+1 种基金the National Key Research and Development Program(No.2022YFC3105002)the Project from Key Laboratory of Marine Environmental Information Technology(No.2023GFW-1047).
文摘Sea-surface wind is a vital meteorological element in marine activities and climate research.This study proposed the spectral attention enhanced multidimensional feature fusion convolutional long short-term memory(LSTM)network(SAMFF-Conv-LSTM),a novel approach for sea-surface wind-speed prediction that emphasizes the temporal characteristics of data samples.The model incorporates the Fourier transform to extract time-and frequency-domain features from wave and wind variables.For the 12 h prediction,the SAMFF-ConvLSTM achieved a correlation coefficient of 0.960 and a root mean square error(RMSE)of 1.350 m/s,implying a high prediction accuracy.For the 24 h prediction,the RMSE of the SAMFF-ConvLSTM was reduced by 38.11%,14.26%,and 13.36%compared with those of the convolutional neural network,gated recurrent units,and convolutional LSTM(ConvLSTM),respectively.These results confirm the superior reliability and accuracy of the SAMFF-ConvLSTM over traditional models in theoretical and practical applications.
基金supported by the National Natural Science Foundation of China(Grant No.52201379)the Fundamental Research Funds for the Central Universities(Grant No.WUT:3120622898)+2 种基金State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment,Dalian University of Technology(Grant No.GZ 231088)Shanghai Key Laboratory of Naval Architecture Engineering(Grant No.SE202305)funded by European Research Council project under the European Union’s Horizon 2020 research and innovation program(Grant No.TRUST CoG 2019864724).
文摘Due to global warming and diminishing ice cover in Arctic regions,the northern sea route(NSR)has attracted increasing attention in recent years.Extreme cold temperatures and high wind speeds in Arctic regions present substantial risks to vessels operating along the NSR.Consequently,analyzing extreme temperature and wind speed values along the NSR is essential for ensuring maritime operational safety in the region.This study analyzes wind and temperature data spanning 40 years,from 1981 to 2020,at four representative sites along the NSR for extreme value analysis.The average conditional exceedance rate(ACER)method and the Gumbel method are employed to estimate extreme wind speed and air temperature at these sites.Comparative analysis reveals that the ACER method provides higher accuracy and lower uncertainty in estimations.The predicted extreme wind speed for a 100-year return period is 30.36 m/s,with a minimum temperature of-56.66°C,varying across the four sites.Furthermore,the study presents extreme values corresponding to each return period,providing temperature extremes as a basis for guiding steel thickness specifications.These findings provide valuable reference for designing polar vessels and offshore structures,contributing to enhanced engineering standards for Arctic conditions.
基金supported by the Major Innovation Project for the Integration of Science,Education,and Industry of Qilu University of Technology(Shandong Academy of Sciences)(Nos.2023HYZX01,2023JBZ02)the Open Project of Key Laboratory of Computing Power Network and Information Security,Ministry of Education,Qilu University of Technology(Shandong Academy of Sciences)(No.2023ZD007)+2 种基金the Talent Research Projects of Qilu University of Technology(Shandong Academy of Sciences)(No.2023RCKY136)the Technology and Innovation Major Project of the Ministry of Science and Technology of China(No.2022ZD0118600)the Jinan‘20 New Colleges and Universities’Funded Project(No.202333043)。
文摘Accurate wind speed measurements on maritime vessels are crucial for weather forecasting,sea state prediction,and safe navigation.However,vessel motion and challenging environmental conditions often affect measurement precision.To address this issue,this study proposes an innovative framework for correcting and predicting shipborne wind speed.By integrating a main network with a momentum updating network,the proposed framework effectively extracts features from the time and frequency domains,thereby allowing for precise adjustments and predictions of shipborne wind speed data.Validation using real sensor data collected at the Qingdao Oceanographic Institute demonstrates that the proposed method outperforms existing approaches in single-and multi-step predictions compared to existing methods,achieving higher accuracy in wind speed forecasting.The proposed innovative approach offers a promising direction for future validation in more realistic maritime onboard scenarios.
基金supported by the Key R&D Program of Shandong Province,China(No.2021ZLGX04)the National Natural Science Foundation of China(No.52171284)。
文摘A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical distribution of the two variables may show multimodal characteristics.In this work,a finite mixture bivariate statistical model was designed to describe the statistical properties,which is composed of several components,each with a Weibull distribution and a normal distribution for wind speed and wind shear,respectively,with a Gaussian copula to describe the dependency structure between the two variables.To confirm the developed model,reanalysis data from six positions in the coastal sea areas of China were used.Our results disclosed that the developed joint statistical model can accurately capture the different multimodal structures presented in all the bivariate samples under mixed atmospheric conditions,giving acceptable predictions of the joint probability distributions.Proper consideration of wind shear coefficient variation is crucial in estimating height-dependent wind resource characteristics.Importantly,unlike traditional methods that are limited to specific hub heights,the model developed here can estimate wind energy potential across different hub heights,enhancing the economic viability assessment of wind power projects.
基金The Fund of Key Laboratory of Space Ocean Remote Sensing and Application,Ministry of Natural Resources under contract No.2023CFO016the National Natural Science Foundation of China under contract No.61931025the Key Program of Joint Fund of the National Natural Science Foundation of China and Shandong Province under contract No.U22A20586.
文摘The successful launch of the Cyclone Global Navigation Satellite System(CYGNSS)has opened an unprecedented opportunity for rapid observation of Wind Speed(WS)across vast oceanic regions.However,considerable debate persists over the choice of input feature parameters for WS retrieval models based on CYGNSS data,and enhancing the accuracy of WS retrieval is a focal point of current research.To address the aforementioned problems,this study establishes a comprehensive CYGNSS wind speed retrieval feature parameter set through an in-depth analysis of CYGNSS data,thereby providing a reference and basis for selecting input features for WS retrieval models.Through this analysis,we identified three crucial observational features:the normalized bistatic radar cross section,leading edge slope,and signal-to-noise ratio.Using these features,we developed a WS retrieval model based on the geophysical model function for CYGNSS data.Furthermore,acknowledging the intrinsic interconnection between wind and wave dynamics,we incorporate significant wave height into the WS retrieval model to further improve the WS retrieval accuracy.Comparative assessments with datasets from the European Centre for Medium-Range Weather Forecasts,the Chinese-French Oceanography Satellite Scatterometer,and buoy WS data underscore the high accuracy of our model,demonstrating its utility as a valuable tool for research in ocean dynamics and marine environmental prediction.
基金CRSRI Open Research Program(Project No.CKWV2014202/KY).
文摘Affected by the Super Typhoon“Mangkhut,”a total of five base towers of a transmission line in the mountainous area of China collapsed.In this paper,a mathematical model is established based on the Shuttle Radar Topography Mission(SRTM)data near the accident tower.The measured wind speed in the plain area under the mountain is used as the calculation boundary condition.The wind speed at the top of the mountain is calculated by using a numerical simulation method.The design wind speed and calculated wind speed at the tower site are compared,and the influence of wind speed on tower position in this wind disaster accident is analyzed.
基金supported by the Key R&D Program of Ningxia Hui Autonomous Region,China(2021BEG03008)the Natural Science Foundation of Ningxia Hui Autonomous Region,China(2021AAC03083).
文摘The maintenance of sand-fixing vegetation is important for the stability of artificial sand-fixing systems in which seed dispersal plays a key role.Based on field wind tunnel experiments using 11 common plant species on the southeastern edge of the Tengger Desert,China,we studied the secondary seed dispersal in the fixed and semi-fixed sand dunes as well as in the mobile dunes in order to understand the limitations of vegetation regeneration and the maintenance of its stability.Our results indicated that there were significant variations among the selected 11 plant species in the threshold of wind speed(TWS).The TWS of Caragana korshinskii was the highest among the 11 plant species,whereas that of Echinops gmelinii was the lowest.Seed morphological traits and underlying surface could generally explain the TWS.During the secondary seed dispersal processes,the proportions of seeds that did not disperse(no dispersal)and only dispersed over short distance(short-distance dispersal within the wind tunnel test section)were significantly higher than those of seeds that were buried(including lost seeds)and dispersed over long distance(long-distance dispersal beyond the wind tunnel test section).Compared with other habitats,the mobile dunes were the most difficult places for secondary seed dispersal.Buried seeds were the easiest to be found in the semi-fixed sand dunes,whereas fixed sand dunes were the best sites for seeds that dispersed over long distance.The results of linear mixed models showed that after controlling the dispersal distance,smaller and rounder seeds dispersed farther.Shape index and wind speed were the two significant influencing factors on the burial of seeds.The explanatory power of wind speed,underlying surface,and seed morphological traits on the seeds that did not disperse and dispersed over short distance was far greater than that on the seeds that were buried and dispersed over long distance,implying that the processes and mechanisms of burial and long-distance dispersal are more complex.In summary,most seeds in the study area either did not move,were buried,or dispersed over short distance,promoting local vegetation regeneration.
基金Supported by the National Natural Science Foundation of China(Nos.61871353,42006164)。
文摘Optical remote sensing has been widely used to study internal solitary waves(ISWs).Wind speed has an important effect on ISW imaging of optical remote sensing.The light and dark bands of ISWs cannot be observed by optical remote sensing when the wind is too strong.The relationship between the characteristics of ISWs bands in optical remote sensing images and the wind speed is still unclear.The influence of wind speeds on the characteristics of the ISWs bands is investigated based on the physical simulation experiments with the wind speeds of 1.6,3.1,3.5,3.8,and 3.9 m/s.The experimental results show that when the wind speed is 3.9 m/s,the ISWs bands cannot be observed in optical remote sensing images with the stratification of h_(1)∶h_(2)=7∶58,ρ_(1)∶ρ_(2)=1∶1.04.When the wind speeds are 3.1,3.5,and 3.8 m/s,which is lower than 3.9 m/s,the ISWs bands can be obtained in the simulated optical remote sensing image.The location of the band’s dark and light extremum and the band’s peak-to-peak spacing are almost not affected by wind speed.More-significant wind speeds can cause a greater gray difference of the light-dark bands.This provided a scientific basis for further understanding of ISW optical remote sensing imaging.
基金the Gansu Province Soft Scientific Research Projects(No.2015GS06516)the Funds for Distinguished Young Scientists of Lanzhou University of Technology,China(No.J201304)。
文摘Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting wind speed accurately is difficult.A new hybrid deep learning model based on empirical wavelet transform,recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper.The empirical wavelet transformation is applied to decompose the original wind speed series.The long short term memory network and the Elman neural network are adopted to predict low-frequency and high-frequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy.The error correction strategy based on deep long short term memory network is developed to modify the prediction errors.Four actual wind speed series are utilized to verify the effectiveness of the proposed model.The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction.
基金supported by the National Natural Science Foundation of China(No.U2142206).
文摘Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.
基金the National Natural Science Foundation of China(42176243)。
文摘Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.
文摘Amid the randomness and volatility of wind speed, an improved VMD-BP-CNN-LSTM model for short-term wind speed prediction was proposed to assist in power system planning and operation in this paper. Firstly, the wind speed time series data was processed using Variational Mode Decomposition (VMD) to obtain multiple frequency components. Then, each individual frequency component was channeled into a combined prediction framework consisting of BP neural network (BPNN), Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) after the execution of differential and normalization operations. Thereafter, the predictive outputs for each component underwent integration through a fully-connected neural architecture for data fusion processing, resulting in the final prediction. The VMD decomposition technique was introduced in a generalized CNN-LSTM prediction model;a BPNN model was utilized to predict high-frequency components obtained from VMD, and incorporated a fully connected neural network for data fusion of individual component predictions. Experimental results demonstrated that the proposed improved VMD-BP-CNN-LSTM model outperformed other combined prediction models in terms of prediction accuracy, providing a solid foundation for optimizing the safe operation of wind farms.
基金Science and Technology Research Project of Guangdong Meteorological Service(GRMC2021M19,GRMC2022Q16,GRMC2023M29)。
文摘The Pearl River Estuary(PRE)is one of China’s busiest shipping hubs and fishery production centers,as well as a region with abundant island tourism and wind energy resources,which calls for accurate short-term wind forecasts.First,this study evaluated three operational numerical models,i.e.,ECMWF-EC,NCEP-GFS,and CMA-GD,for their ability to predict short-term wind speed over the PRE against in-situ observations during 2018-2021.Overall,ECMWF-EC out-performs other models with an average RMSE of 2.24 m s^(-1)and R of 0.57,but the NCEP-GFS performs better in the case of strong winds.Then,various bias correction and multi-model ensemble(MME)methods are used to perform the deterministic post-processing using a local and lead-specific scheme.Two-factor model output statistics(MOS2)is the optimal bias correction method for reducing(increasing)the overall RMSE(R)to 1.62(0.70)m s^(-1),demonstrating the benefits of considering both initial and lead-specific information.Intercomparison of MME results reveals that Multiple linear regression(MLR)presents superior skills,followed by random forest(RF),but it is slightly inferior to MOS2,particularly for the first few forecasting hours.Furthermore,the incorporation of additional features in MLR reduces the overall RMSE to 1.53 m s^(-1)and increases R to 0.74.Similarly,RF presents comparable results,and both outperform MOS2 in terms of correcting their deficiencies at the first few lead hours and limiting the error growth rate.Despite the satisfactory skill of deterministic post-processing techniques,they are unable to achieve a balanced performance between mean and extreme statistics.This highlights the necessity for further development of probabilistic forecasts.
基金Supported by the Scientific Project of Jiangsu Environmental Protection(2009008)The Preliminary Research Projects of Jiangsu "Shier Wu" Environmental Protection Planning
文摘Based on the data of the wind speed from 20 m meteorological tower and PM10 mass concentration in Zhurihe region from January of 2005 to April of 2006,the evolution characteristics of wind speed profile in near surface layer and PM10 in three representative dust weather processes (dust storm,blowing sand and floating dust) were analyzed.The results showed that wind speed was higher during dust storm and blowing sand with remarkable vertical gradient.The speed in floating dust was relatively lower and increased during the whole process.In general,wind speed after dust weather was smaller with respect to that before the event.The average mass concentrations of PM10 in the processes of dust storm,blowing sand and floating dust were in the ranges of 5 436.38-10 000,1 799.49-4 006.06 and 1 765.53 μg/m3,respectively.
基金funded by the National Natural Science Foundation of China(52279017 and 52079063)Technological Achievements of Inner Mongolia Autonomous Region of China(2020CG0054 and 2022YFDZ0050)+1 种基金the Graduate Education Innovation Program of Inner Mongolia Autonomous Region of China(B20210188Z)the Program for Innovative Research Team in Universities of Inner Mongolia Autonomous Region,China(NMGIRT2313).
文摘In grassland ecosystems,the aerodynamic roughness(Z0)and frictional wind speed(u*)contribute to the aerodynamic impedance of the grassland canopy.Thus,they are often used in the studies of wind erosion and evapotranspiration.However,the effect of wind speed and grazing measures on the aerodynamic impedance of the grassland canopy has received less analysis.In this study,we monitored wind speeds at multiple heights in grazed and grazing-prohibited grasslands for 1 month in 2021,determined the transit wind speed at 2.0 m height by comparing wind speed differences at the same height in both grasslands,and divided these transit wind speeds at intervals of 2.0 m/s to analyze the effect of the transit wind speed on the relationship among Z0,u*,and wind speed within the grassland canopy.The results showed that dividing the transit wind speeds into intervals has a positive effect on the logarithmic fit of the wind speed profile.After dividing the transit wind speeds into intervals,the wind speed at 0.1 m height(V0.1)gradually decreased with the increase of Z0,exhibiting three distinct stages:a sharp change zone,a steady change zone,and a flat zone;while the overall trend of u*increased first and then decreased with the increase of V0.1.Dividing the transit wind speeds into intervals improved the fitting relationship between Z0 and V0.1 and changed their fitting functions in grazed and grazing-prohibited grasslands.According to the computational fluid dynamic results,we found that the number of tall-stature plants has a more significant effect on windproof capacity than their height.The results of this study contribute to a better understanding of the relationship between wind speed and the aerodynamic impedance of vegetation in grassland environments.
基金TheresearchissupportedbyFoundationforDoctoralStudiesofMinistryofEducation (No .19980 0 2 2 0 6 )
文摘In the study a fire and fire environment model is set up and by using PHEONICS software 3 cases of surface fires are studied. The results fit the experimental studies well generally. The simulation reveals that (1) The wind speed fields in front of fire front generally can be divided into 3 zones and there is always an eddy immediately at the corner between just in front of the fire and the ground. (2) The shape and dimension of the division of the 3 zones is mainly decided by slope angle and ambient wind speed given fire line intensity. (3) There exits an upwind zone in front of fire front. Ambient wind speeds have little effect on the magnitude of the upwind speed when slope angle is 0. But when the slope angle is negative, the upwind is apparently stronger.
基金Supported by Meteorological Data Sharing Center Project (2005DKA31700-01,GX07-01-01)2009 Specific Research in Non-profit Sector (200906041-053)
文摘Comparing and analyzing the difference between automatic-observed and manual-observed wind speed based on the wind speed parallel observations in two methods, we find that many elements can influence the difference between automatic-observed and manual-observed wind speed, including the levels of speed wind, observation instruments and different regions. According to these elements, correction has been conducted, and find that the correction according to the level of wind speed has the best correction effect.
