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61.
The scenario assumed for this study was that of a region with a complete or first‐order weather station surrounded by a network of second‐order stations, where only monthly air temperature data were available. The objective was to evaluate procedures to estimate the monthly α parameter of the Priestley–Taylor equation in the second‐order stations by adjusting and extrapolating α values determined at the first‐order station. These procedures were applied in two climatic zones of north‐east Spain with semi‐arid continental and semi‐arid Mediterranean climates, respectively. Procedure A assumed α to be constant over each zone for each month (direct extrapolation). Procedure B accounted for differences in vapour pressure deficit and available energy for evapotranspiration between the first‐ and second‐order stations. Procedure C was based on equating the Penman–Monteith (P–M) and Priestley–Taylor (P–T) equations on a monthly basis to solve for α. Methods to estimate monthly mean vapour pressure deficit, net radiation and wind speed were developed and evaluated. A total of 11 automated first‐order weather stations with a minimum period of record of 6 years (ranging from 6 to 10 years) were used for this study. Six of these stations were located in the continental zone and five in the Mediterranean zone. One station in each zone was assumed to be first‐order whereas the remainder were taken as second‐order stations. Monthly α parameters were calibrated using P–M reference crop evapotranspiration (ET0) values, calculated hourly and integrated for monthly periods, which were taken as ‘true’ values of ET0. For the extrapolation of monthly α parameters, procedure A was found to perform slightly better than procedure B in the Mediterranean zone. The opposite was true in the continental zone. Procedure C had the worst performance owing to the non‐linearity of the P–M equation and errors in the estimation of monthly available energy, vapour pressure deficit and wind speed. Procedures A and B are simpler and performed better. Overall, monthly P–T ET0 estimates using extrapolated α parameters and Rn?G values were in a reasonable agreement with P–M ET0 calculated on an hourly basis and integrated for monthly periods. The methods presented for the spatial extrapolation of monthly available energy, vapour pressure deficit and wind speed from first‐ to second‐order stations could be useful for other applications. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
62.
Aldo Vitagliano 《Celestial Mechanics and Dynamical Astronomy》1996,66(3):293-308
A simplified model of the solar system has been developed along with an integration method, enabling to compute planetary and lunar ephemerides to an accuracy better than 1 and 2 milliarcsecs, respectively. On current personal computers, the integration procedure (SOLEX) is fast enough that by using a relatively small ( 20 Kbytes/Cy) database of starting conditions, any epoch in the time interval (up to ±100 Cy) covered by the database can be reached by the integrator in a few seconds. This makes the algorithm convenient for the direct computation of high precision ephemerides over a time span of several millennia. 相似文献
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A new radar echo tracking algorithm known as multi-scale tracking radar echoes by cross-correlation(MTREC) was developed in this study to analyze movements of radar echoes at different spatial scales.Movement of radar echoes,particularly associated with convective storms,exhibits different characteristics at various spatial scales as a result of complex interactions among meteorological systems leading to the formation of convective storms.For the null echo region,the usual correlation technique produces zero or a very small magnitude of motion vectors.To mitigate these constraints,MTREC uses the tracking radar echoes by correlation(TREC) technique with a large "box" to determine the systematic movement driven by steering wind,and MTREC applies the TREC technique with a small "box" to estimate small-scale internal motion vectors.Eventually,the MTREC vectors are obtained by synthesizing the systematic motion and the small-scale internal motion.Performance of the MTREC technique was compared with TREC technique using case studies:the Khanun typhoon on 11 September 2005 observed by Wenzhou radar and a squall-line system on 23 June 2011 detected by Beijing radar.The results demonstrate that more spatially smoothed and continuous vector fields can be generated by the MTREC technique,which leads to improvements in tracking the entire radar reflectivity pattern.The new multi-scale tracking scheme was applied to study its impact on the performance of quantitative precipitation nowcasting.The location and intensity of heavy precipitation at a 1-h lead time was more consistent with quantitative precipitation estimates using radar and rain gauges. 相似文献
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基于江西及其周边地区的雷达组合反射率拼图,将二维Boussinesq(水平无辐散)质量连续方程约束至江西地区的TREC风场,得到改善后的TREC风场(COTREC风场),并基于COTREC风矢量开展了江西地区雷达回波的外推。个例分析表明,经过二维无辐散连续方程约束后,COTREC风中的噪声和不一致得到了显著的平滑,其风速水平梯度和风向切变都显著减小。基于COTREC风外推的雷达回波在形态上也得到了明显的改善,其外推回波中由风场的噪声或不一致引起的异常失真回波明显减少。为了进一步评估TREC和COTREC方法的外推表现,对2018年7月1—31日江西地区有明显降水的287个时次的雷达回波分别进行了1 h和2 h外推。结果表明:相对于TREC方法,COTREC方法在1 h和2 h的外推时间上均能改善外推回波的精度,其外推回波与实况的相关系数和TS评分均较TREC方法高。 相似文献
66.
基于江西省及周边16部新一代多普勒天气雷达拼图资料,利用交叉相关跟踪法(TREC)计算江西地区雷达回波的移动矢量(TREC风),并对求解的TREC风进行异常值更正和空洞补齐等质量控制,最后利用后向外推法对江西地区2017年6月29日09:54的雷达回波进行2 h内的外推。结果表明,TREC方法能较好地获得江西地区未来2 h内的雷达回波位置和空间结构,且在0—1 h的外推回波非常接近实况。通过对2018年6月1—9日201个天气过程0—2 h外推的TS评分统计表明,基于该方法外推的2 h内的雷达回波精度都较高(TS评分0.3),但TS评分随外推时间的增长而快速降低,当外推时间为30 min时TS评分高达0.61,外推时间增至60 min时TS评分降至0.48,外推时间延长至120 min时TS评分进一步减至0.31。 相似文献
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Design of an offshore wind turbine requires estimation of loads on its rotor, tower and supporting structure. These loads are obtained by time-domain simulations of the coupled aero-servo-hydro-elastic model of the wind turbine. Accuracy of predicted loads depends on assumptions made in the simulation models employed, both for the turbine and for the input wind and wave conditions. Currently, waves are simulated using a linear irregular wave theory that is not appropriate for nonlinear waves, which are even more pronounced in shallow water depths where wind farms are typically sited. The present study investigates the use of irregular nonlinear (second-order) waves for estimating loads on the support structure (monopile) of an offshore wind turbine. We present the theory for the irregular nonlinear model and incorporate it in the commonly used wind turbine simulation software, FAST, which had been developed by National Renewable Energy Laboratory (NREL), but which had the modeling capability only for irregular linear waves. We use an efficient algorithm for computation of nonlinear wave elevation and kinematics, so that a large number of time-domain simulations, which are required for prediction of long-term loads using statistical extrapolation, can easily be performed. To illustrate the influence of the alternative wave models, we compute loads at the base of the monopile of the NREL 5MW baseline wind turbine model using linear and nonlinear irregular wave models. We show that for a given environmental condition (i.e., the mean wind speed and the significant wave height), extreme loads are larger when computed using the nonlinear wave model. We finally compute long-term loads, which are required for a design load case according to the International Electrotechnical Commission guidelines, using the inverse first-order reliability method. We discuss a convergence criteria that may be used to predict accurate 20-year loads and discuss wind versus wave dominance in the load prediction. We show that 20-year long-term loads can be significantly higher when the nonlinear wave model is used. 相似文献
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