Since QuikSCAT is available in cloudy and rainy condition, its wind data are valuable in monitoring and real time forecasting the wind field, especially in sparse genesis regions of tropical cyclones. In order to unde...Since QuikSCAT is available in cloudy and rainy condition, its wind data are valuable in monitoring and real time forecasting the wind field, especially in sparse genesis regions of tropical cyclones. In order to understand and investigate the impact of QuikSCAT wind data, the three-dimensional variational data assimilation (3D-VAR) of scatterometric wind data has been employed for the tropical cyclone 'Vongfong' in the year 2002. The result shows that the QuikSCAT wind data have positive impact on the analysis and forecasting. But the positive impact is slight. The present results suggest that how to assimilate QuikSCAT wind data effectively is important and will be a challenge to meteorologists.展开更多
Taibus County, Inner Mongolia, China, lies in a farming-pastoral ecotone, where severe wind erosion and various aeolian sand hazards are prevalent and fixed and semi-fixed sand dunes occur frequently. This study was c...Taibus County, Inner Mongolia, China, lies in a farming-pastoral ecotone, where severe wind erosion and various aeolian sand hazards are prevalent and fixed and semi-fixed sand dunes occur frequently. This study was conducted to investigate the relationships between sand transportation rate and wind speed for the fixed and semi-fixed sand dunes based on field measurements. The annual quantity of soil erosion by wind was estimated using meteorological wind data. The results indicated that the sand transportation rate in Taibus County in 2000 was 57.38 kg cm-1 year-1 for the semi-fixed dunes and 4.56 kg cm-1 year-1 for the fixed dunes. The total duration of erosive winds covered 12.5% of the time of the year, and spring posed the highest potential of sand transportation. Wind with low speed (≤ 17 m s-1) and high frequency plays a dominant role in sand transportation, while strong wind (≥ 17 m s-1) with low frequency significantly enhanced the sand transportation. Erosive wind speed, directions, and frequency were three crucial dynamic factors influencing sand hazards in the farming-pastoral ecotone. The dominant factors intensifying sand and dust storms in Taibus County might be related to the favorable wind condition in combination with the durable drought, which led to land desertification and vegetation degradation.展开更多
ERA5 data and station observation data are both of great importance in studying the regional meteorological and environmental characteristics.The accuracy of ERA5 reanalysis wind field data was evaluated using observa...ERA5 data and station observation data are both of great importance in studying the regional meteorological and environmental characteristics.The accuracy of ERA5 reanalysis wind field data was evaluated using observations at five offshore platforms in Jiangsu sea area in this study.Results revealed that ERA5 wind speed was generally in reasonable agreement with that observed at each station,and that the accuracy of ERA5 wind speed data was significant better than that of wind direction.The consistency of wind direction between ERA5 and each observation station was better in autumn and winter than that in spring and summer.With increasing wind speed,the mean absolute error and root mean squared error between the ERA5 and observed wind speed(direction)data increased(decreased)obviously.During periods of typhoon,ERA5 wind data were largely consistent with observational data in terms of increasing wind speed and changing wind direction;however,the ERA5 wind speeds were slightly low.The findings of this study could provide a basis for the application and further research of ERA5 wind data in Jiangsu offshore sea area.展开更多
Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms tha...Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms that QuikSCAT estimates of wind speed and direction are generally accurate, except for the extremes of high wind speeds (>13.8m/s) and very low wind speeds (<1.5m/s) where direction is poorly predicted. In-situ observations show that the summer monsoon in the northern SCS starts between May 6 and June 1. From March 13, 2010 to August 31, 2010, comparisons of sea surface temperature (SST) and rainfall from AMSR-E with data from a buoy located at Xisha Islands, as well as wind measurements derived from ASCAT and observations from an automatic weather station show that QuikSCAT, ASCAT and AMSR-E data are good enough for research. It is feasible to optimize the usage of remote-sensing data if validated with in-situ measurements. Remarkable changes were observed in wind, barometric pressure, humidity, outgoing longwave radiation (OLR), air temperature, rainfall and SST during the monsoon onset. The eastward shift of western Pacific subtropical high and the southward movement of continental cold front preceded the monsoon onset in SCS. The starting dates of SCS summer monsoon indicated that the southwest monsoon starts in the Indochinese Peninsula and forms an eastward zonal belt, and then the belt bifurcates in the SCS, with one part moving northeastward into the tropical western North Pacific, and another southward into western Kalimantan. This largely determined the pattern of the SCS summer monsoon. Wavelet analysis of zonal wind and OLR at Xisha showed that intra-seasonal variability played an important role in the summer. This work improves the accuracy of the amplitude of intra-seasonal and synoptic variation obtained from remote-sensed data.展开更多
Randomness and fluctuations in wind power output may cause changes in important parameters(e.g.,grid frequency and voltage),which in turn affect the stable operation of a power system.However,owing to external factors...Randomness and fluctuations in wind power output may cause changes in important parameters(e.g.,grid frequency and voltage),which in turn affect the stable operation of a power system.However,owing to external factors(such as weather),there are often various anomalies in wind power data,such as missing numerical values and unreasonable data.This significantly affects the accuracy of wind power generation predictions and operational decisions.Therefore,developing and applying reliable wind power interpolation methods is important for promoting the sustainable development of the wind power industry.In this study,the causes of abnormal data in wind power generation were first analyzed from a practical perspective.Second,an improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN)method with a generative adversarial interpolation network(GAIN)network was proposed to preprocess wind power generation and interpolate missing wind power generation sub-components.Finally,a complete wind power generation time series was reconstructed.Compared to traditional methods,the proposed ICEEMDAN-GAIN combination interpolation model has a higher interpolation accuracy and can effectively reduce the error impact caused by wind power generation sequence fluctuations.展开更多
With available high-resolution ocean surface wind vectors retrieved from the U.S.Naval Research Laboratory's WindSat on Coriolis,the impact of these data on genesis and forecasting of tropical storm Henri is exami...With available high-resolution ocean surface wind vectors retrieved from the U.S.Naval Research Laboratory's WindSat on Coriolis,the impact of these data on genesis and forecasting of tropical storm Henri is examined using the non-hydrostatic,fifth-generation mesoscale model(MM5) of Pennsylvania State University-National Center for Atmospheric Research plus its newly released three-dimensional variational data assimilation(3DVAR) system.It is shown that the assimilation of the WindSat-retrieved ocean surface wind vectors in the 3DVAR system improves the model initialization fields by introducing a stronger vortex in the lower troposphere.As a result,the model reproduces the storm formation and track reasonably close to the observations.Compared to the experiment without the WindSat surface winds,the WindSat assimilation reduced an error between the model simulated track and observations of more than 80 km and also improved the storm intensity by nearly 2 hPa.It suggests that these data could provide early detection and prediction of tropical storms or hurricanes.展开更多
The scatterometer （SCAT） on-board China＇s HY-2A satellite has the capability to provide high resolution wind vector information over the global ocean surface. These wind vector data produced by the HY-2A scatterome...The scatterometer （SCAT） on-board China＇s HY-2A satellite has the capability to provide high resolution wind vector information over the global ocean surface. These wind vector data produced by the HY-2A scatterometer （HY-2A SCAT） are available to the data assimilation system with real-time information of high accuracy. In this paper, two experiments are designed to investigate the impact of HY-2A SCAT data in the three- dimensional variational assimilation system for the Weather Research and Forecast model （WRF 3DVAR）. The powerful Typhoon Bolaven, which struck South Korea in August 2012, is selected for this case study. The results clearly demonstrate that HY-2A SCAT data can effectively complement the scarce observations over the ocean surface and improve the prediction of the wind and pressure fields of a typhoon. The case study of Typhoon Bolaven exhibits the significant and positive impact of HY- 2A SCAT data on the numerical prediction of the tropical cyclone track.展开更多
As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Pr...As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Prediction of wind turbine failures before they reach a catastrophic stage is critical to reduce the O & M cost due to unnecessary scheduled maintenance. A SCADA-data based condition monitoring system, which takes advantage of data already collected at the wind turbine controller, is a cost-effective way to monitor wind turbines for early warning of failures. This article proposes a methodology of fault prediction and automatically generating warning and alarm for wind turbine main bearings based on stored SCADA data using Artificial Neural Network (ANN). The ANN model of turbine main bearing normal behavior is established and then the deviation between estimated and actual values of the parameter is calculated. Furthermore, a method has been developed to generate early warning and alarm and avoid false warnings and alarms based on the deviation. In this way, wind farm operators are able to have enough time to plan maintenance, and thus, unanticipated downtime can be avoided and O & M costs can be reduced.展开更多
This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution...This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set(CCMP), NCEP climate forecast system reanalysis data set(CFSR),ERA-interim reanalysis data set(ERA-int) and Japanese 55-year reanalysis data set(JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the longterm and homogeneous observation wind speeds data recorded at ten stations. The results reveal that(1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively.The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s,respectively;(2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea;(3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.展开更多
Making use of altimeter wind data and standard sounding data in a mesoscale numerical model of PSU/NCAR (MM5), we test four-dimensional data assimilation scheme based on nudging. The purpose of this paper is to determ...Making use of altimeter wind data and standard sounding data in a mesoscale numerical model of PSU/NCAR (MM5), we test four-dimensional data assimilation scheme based on nudging. The purpose of this paper is to determine what meteorological fields and what assimilation method have positive effect on typhoon sea surface wind by simulating two typhoon cases in MM5. We perform seven experiments for 9608 Typhoon (Case 1): one control experiment, three analysis nudging experiments, two observation nudging experiments and one analysis and observation nudging experiment; we perform one control experiment and one analysis nudging experiment for 9711 Typhoon (Case 2). The results show assimilating wind-thermal fields can effectively improve simulation accuracy of the model; the experiment combining standard sounding data and surface observations can improve greatly the simulation accuracy of the model; the altimeter data contain lots of sea surface information and also have positive impact on typhoon sea surface wind.展开更多
The accuracy of fluctuating pressure test in wind tunnel is affected by the tube system. By employing contradistinctive experimental method, systematic study was conducted to investigate the effects of the tube system...The accuracy of fluctuating pressure test in wind tunnel is affected by the tube system. By employing contradistinctive experimental method, systematic study was conducted to investigate the effects of the tube system on fluctuating pressure. The analyzed tube system parameters include tube length, inside diameter, curvature, deflection angle, thickness, material, restrictor length,restrictor inside diameter, and restrictor place. It is found that all the tube system parameters mentioned above except tube curvature have non-negligible effects on fluctuating pressure. Based on the research results, test methods were presented for the fluctuating pressure measurement in low-speed wind tunnel, which can obviously improve the data accuracy but not lose test efficiency. The effectiveness of the method is verified by the wind tunnel test.展开更多
文摘Since QuikSCAT is available in cloudy and rainy condition, its wind data are valuable in monitoring and real time forecasting the wind field, especially in sparse genesis regions of tropical cyclones. In order to understand and investigate the impact of QuikSCAT wind data, the three-dimensional variational data assimilation (3D-VAR) of scatterometric wind data has been employed for the tropical cyclone 'Vongfong' in the year 2002. The result shows that the QuikSCAT wind data have positive impact on the analysis and forecasting. But the positive impact is slight. The present results suggest that how to assimilate QuikSCAT wind data effectively is important and will be a challenge to meteorologists.
基金supported by the National Natural Science Foundation of China (No.40771021)the Ministry of Education ofChina (No.20070027020)the Ministry of Science & Technology of China (Nos.2006BAD20B03 and 2006BAD20B02).
文摘Taibus County, Inner Mongolia, China, lies in a farming-pastoral ecotone, where severe wind erosion and various aeolian sand hazards are prevalent and fixed and semi-fixed sand dunes occur frequently. This study was conducted to investigate the relationships between sand transportation rate and wind speed for the fixed and semi-fixed sand dunes based on field measurements. The annual quantity of soil erosion by wind was estimated using meteorological wind data. The results indicated that the sand transportation rate in Taibus County in 2000 was 57.38 kg cm-1 year-1 for the semi-fixed dunes and 4.56 kg cm-1 year-1 for the fixed dunes. The total duration of erosive winds covered 12.5% of the time of the year, and spring posed the highest potential of sand transportation. Wind with low speed (≤ 17 m s-1) and high frequency plays a dominant role in sand transportation, while strong wind (≥ 17 m s-1) with low frequency significantly enhanced the sand transportation. Erosive wind speed, directions, and frequency were three crucial dynamic factors influencing sand hazards in the farming-pastoral ecotone. The dominant factors intensifying sand and dust storms in Taibus County might be related to the favorable wind condition in combination with the durable drought, which led to land desertification and vegetation degradation.
文摘ERA5 data and station observation data are both of great importance in studying the regional meteorological and environmental characteristics.The accuracy of ERA5 reanalysis wind field data was evaluated using observations at five offshore platforms in Jiangsu sea area in this study.Results revealed that ERA5 wind speed was generally in reasonable agreement with that observed at each station,and that the accuracy of ERA5 wind speed data was significant better than that of wind direction.The consistency of wind direction between ERA5 and each observation station was better in autumn and winter than that in spring and summer.With increasing wind speed,the mean absolute error and root mean squared error between the ERA5 and observed wind speed(direction)data increased(decreased)obviously.During periods of typhoon,ERA5 wind data were largely consistent with observational data in terms of increasing wind speed and changing wind direction;however,the ERA5 wind speeds were slightly low.The findings of this study could provide a basis for the application and further research of ERA5 wind data in Jiangsu offshore sea area.
基金Supported by the National Basic Research Program of China (973 Program)(No. 2011CB403504)the Knowledge Innovation Program of Chinese Academy of Sciences (Nos. KZCX2-YW-Q11-02, KZCX2-YW-Y202)the National Natural Science Foundation of China (Nos. 40830851, 41006011)
文摘Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms that QuikSCAT estimates of wind speed and direction are generally accurate, except for the extremes of high wind speeds (>13.8m/s) and very low wind speeds (<1.5m/s) where direction is poorly predicted. In-situ observations show that the summer monsoon in the northern SCS starts between May 6 and June 1. From March 13, 2010 to August 31, 2010, comparisons of sea surface temperature (SST) and rainfall from AMSR-E with data from a buoy located at Xisha Islands, as well as wind measurements derived from ASCAT and observations from an automatic weather station show that QuikSCAT, ASCAT and AMSR-E data are good enough for research. It is feasible to optimize the usage of remote-sensing data if validated with in-situ measurements. Remarkable changes were observed in wind, barometric pressure, humidity, outgoing longwave radiation (OLR), air temperature, rainfall and SST during the monsoon onset. The eastward shift of western Pacific subtropical high and the southward movement of continental cold front preceded the monsoon onset in SCS. The starting dates of SCS summer monsoon indicated that the southwest monsoon starts in the Indochinese Peninsula and forms an eastward zonal belt, and then the belt bifurcates in the SCS, with one part moving northeastward into the tropical western North Pacific, and another southward into western Kalimantan. This largely determined the pattern of the SCS summer monsoon. Wavelet analysis of zonal wind and OLR at Xisha showed that intra-seasonal variability played an important role in the summer. This work improves the accuracy of the amplitude of intra-seasonal and synoptic variation obtained from remote-sensed data.
基金We gratefully acknowledge the support of National Natural Science Foundation of China(NSFC)(Grant No.51977133&Grant No.U2066209).
文摘Randomness and fluctuations in wind power output may cause changes in important parameters(e.g.,grid frequency and voltage),which in turn affect the stable operation of a power system.However,owing to external factors(such as weather),there are often various anomalies in wind power data,such as missing numerical values and unreasonable data.This significantly affects the accuracy of wind power generation predictions and operational decisions.Therefore,developing and applying reliable wind power interpolation methods is important for promoting the sustainable development of the wind power industry.In this study,the causes of abnormal data in wind power generation were first analyzed from a practical perspective.Second,an improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN)method with a generative adversarial interpolation network(GAIN)network was proposed to preprocess wind power generation and interpolate missing wind power generation sub-components.Finally,a complete wind power generation time series was reconstructed.Compared to traditional methods,the proposed ICEEMDAN-GAIN combination interpolation model has a higher interpolation accuracy and can effectively reduce the error impact caused by wind power generation sequence fluctuations.
文摘With available high-resolution ocean surface wind vectors retrieved from the U.S.Naval Research Laboratory's WindSat on Coriolis,the impact of these data on genesis and forecasting of tropical storm Henri is examined using the non-hydrostatic,fifth-generation mesoscale model(MM5) of Pennsylvania State University-National Center for Atmospheric Research plus its newly released three-dimensional variational data assimilation(3DVAR) system.It is shown that the assimilation of the WindSat-retrieved ocean surface wind vectors in the 3DVAR system improves the model initialization fields by introducing a stronger vortex in the lower troposphere.As a result,the model reproduces the storm formation and track reasonably close to the observations.Compared to the experiment without the WindSat surface winds,the WindSat assimilation reduced an error between the model simulated track and observations of more than 80 km and also improved the storm intensity by nearly 2 hPa.It suggests that these data could provide early detection and prediction of tropical storms or hurricanes.
文摘The scatterometer （SCAT） on-board China＇s HY-2A satellite has the capability to provide high resolution wind vector information over the global ocean surface. These wind vector data produced by the HY-2A scatterometer （HY-2A SCAT） are available to the data assimilation system with real-time information of high accuracy. In this paper, two experiments are designed to investigate the impact of HY-2A SCAT data in the three- dimensional variational assimilation system for the Weather Research and Forecast model （WRF 3DVAR）. The powerful Typhoon Bolaven, which struck South Korea in August 2012, is selected for this case study. The results clearly demonstrate that HY-2A SCAT data can effectively complement the scarce observations over the ocean surface and improve the prediction of the wind and pressure fields of a typhoon. The case study of Typhoon Bolaven exhibits the significant and positive impact of HY- 2A SCAT data on the numerical prediction of the tropical cyclone track.
文摘As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Prediction of wind turbine failures before they reach a catastrophic stage is critical to reduce the O & M cost due to unnecessary scheduled maintenance. A SCADA-data based condition monitoring system, which takes advantage of data already collected at the wind turbine controller, is a cost-effective way to monitor wind turbines for early warning of failures. This article proposes a methodology of fault prediction and automatically generating warning and alarm for wind turbine main bearings based on stored SCADA data using Artificial Neural Network (ANN). The ANN model of turbine main bearing normal behavior is established and then the deviation between estimated and actual values of the parameter is calculated. Furthermore, a method has been developed to generate early warning and alarm and avoid false warnings and alarms based on the deviation. In this way, wind farm operators are able to have enough time to plan maintenance, and thus, unanticipated downtime can be avoided and O & M costs can be reduced.
基金The National Key R&D Program of China under contract No.2016YFC1401905the National Natural Science Foundation of China under contract No.41776004the Fundamental Research Funds for the Central Universities under contract No.2016B12514
文摘This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set(CCMP), NCEP climate forecast system reanalysis data set(CFSR),ERA-interim reanalysis data set(ERA-int) and Japanese 55-year reanalysis data set(JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the longterm and homogeneous observation wind speeds data recorded at ten stations. The results reveal that(1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively.The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s,respectively;(2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea;(3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.
文摘Making use of altimeter wind data and standard sounding data in a mesoscale numerical model of PSU/NCAR (MM5), we test four-dimensional data assimilation scheme based on nudging. The purpose of this paper is to determine what meteorological fields and what assimilation method have positive effect on typhoon sea surface wind by simulating two typhoon cases in MM5. We perform seven experiments for 9608 Typhoon (Case 1): one control experiment, three analysis nudging experiments, two observation nudging experiments and one analysis and observation nudging experiment; we perform one control experiment and one analysis nudging experiment for 9711 Typhoon (Case 2). The results show assimilating wind-thermal fields can effectively improve simulation accuracy of the model; the experiment combining standard sounding data and surface observations can improve greatly the simulation accuracy of the model; the altimeter data contain lots of sea surface information and also have positive impact on typhoon sea surface wind.
基金supported by the Pre-research Fund of Vibration and Noise Control Technology (No. 51334060101)
文摘The accuracy of fluctuating pressure test in wind tunnel is affected by the tube system. By employing contradistinctive experimental method, systematic study was conducted to investigate the effects of the tube system on fluctuating pressure. The analyzed tube system parameters include tube length, inside diameter, curvature, deflection angle, thickness, material, restrictor length,restrictor inside diameter, and restrictor place. It is found that all the tube system parameters mentioned above except tube curvature have non-negligible effects on fluctuating pressure. Based on the research results, test methods were presented for the fluctuating pressure measurement in low-speed wind tunnel, which can obviously improve the data accuracy but not lose test efficiency. The effectiveness of the method is verified by the wind tunnel test.
