Impact on the tropical cyclone "Vongfong" forecast using the QuikSCAT wind data

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.

Estimation of Sand Transportation Rate for Fixed and Semi-Fixed Dunes Using Meteorological Wind Data

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.

Preliminary assessment of ERA5 wind data in Jiangsu sea area

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.

Comparison of remote sensing data with in-situ wind observation during the development of the South China Sea monsoon

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.

Missing interpolation model for wind power data based on the improved CEEMDAN method and generative adversarial interpolation network

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.

Three-dimensional variational data assimilation of WindSat ocean surface winds for the genesis and forecasting of tropical storm Henri

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.

Assimilation of HY-2A scatterometer sea surface wind data in a 3DVAR data assimilation system-A case study of Typhoon Bolaven

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.

Automatic Fault Prediction of Wind Turbine Main Bearing Based on SCADA Data and Artificial Neural Network

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.

Evaluation on monthly sea surface wind speed of four reanalysis data sets over the China seas after 1988

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.

ASSIMILATION OF ALTIMETER WIND DATA IN MESOSCALE NUMERICAL MODEL (MM5)

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.

WINDOWS环境下的风洞测量、控制、处理与管理系统

用PC- 586 微机取代PDP系列机实现NEFF720 模拟和数字量数据采集及处理系统、风洞控制系统、PSI780B 电子扫描测压系统的全部功能。自行开发了32 位代码软件,使用标准WINDOWS风格的人机交互界面,中文显示,操作简便。引入虚拟仪器概念,适时图形显示实验进程及实验数据,可扩展成多媒体的风洞实验数据采集、马赫数控制、迎角控制、数据处理及风洞管理。

Google Earth和World Wind比较研究

Google Earth和World Wind是目前最具代表性的两款基于网络的三维地理信息浏览器,为空间信息的共享发布提供了新的解决思路和技术手段。本文首先深入分析了这两款软件的技术特点,并在此基础上作了比较研究。

Wind Energy Potential Assessment in Republic of Macedonia

The paper presents the measurement campaign of wind energy potential undertaken in Republic of Macedonia on four sites from the middle of 2006. The wind data analysis has been performed for one site, following with the assessment of energy production of simulated wind park with six wind turbine generators.

基于LabWindows/CVI实验室的网络化大气参数采集系统

大气参数（温度、湿度和大气压力等）是各专业实验室在进行教学和科研实验时非常重要的环境参数。该文详细阐述了网络化测控系统的基本概念,结合西北工业大学翼型叶栅空气动力学国家重点实验室的NF-3风洞,用LabWindows/CVI集成开发环境实现了NF-3风洞网络化大气参数的自动采集、存储和处理,最后对该系统的扩展性、实时性进行了分析。

基于World Wind的数据加载方法的研究

通过修改World Wind源码的方式实现了服务器向客户端提供DEM数据并加载和显示,解决了利用繁琐的瓦片金字塔模型修改客户端缓存来达到加载数据的难题。大多数情况下,用户不必了解瓦片金字塔的切割算法、标准和格式等问题,大大提高了工作效率。该方法提供了一种通用的实现方法,只要配置好WMS服务器便可向多个不同的终端提供数据,实现数据的高效共享。

基于World Wind移动端的地质数据野外采集系统

针对传统的野外地质数据采集与数字化工作步骤繁琐、效率低、工作周期长等问题,研发了一种基于World Wind移动端的地质数据野外采集系统,系统集成了World Wind地图技术、网络通信技术、多线程技术和数据存储技术.重点阐述了定位模块、数据录入模块、实体投影模块以及三维展示模块的具体实现方法,本系统的研发实现了野外地质工作的信息化采集、浏览和展示,为地质工作人员提供便捷的数据录入方式,推动地矿工作数字化、信息化、现代化的向前发展.

基于WindPRO软件的不同时间尺度下的风电场产能评估

测风数据的准确性对风电场的产能评估具有重要的意义。文章以某风电场一年内每10 min的测风数据为基准,通过WindPRO软件,分别对3种时间尺度(30 min,1 h,2 h)的测风数据进行评估,对比了不同时间尺度下的发电量误差,分析了不同时间尺度下测风数据发电量的误差范围。当风电场选址区域的测风数据不完整时,研究结果可为测风数据时间尺度的选取提供指导性意见。

基于World Wind的海洋数据可视化研究

以World Wind提供的类和接口为基础,设计、开发了栅格图面图元、矢量箭头和等值线生成算法,并进行了可视化实现。此外,还实现了基于三维地形的多层叠加图。不仅提高了可视化效率,还丰富了World Wind的海洋数据可视化表现形式。研究开发的海洋数据可视化算法,能够满足实际应用需求,并已成功应用到南海海洋信息服务系统中。

Improvement of wind field hindcasts for tropical cyclones

This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform （CCMP） reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.