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首页> 外文期刊>Journal of atmospheric and solar-terrestrial physics >Fit of wind speed and temperature profiles in the low atmosphere from rass sodar data
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Fit of wind speed and temperature profiles in the low atmosphere from rass sodar data

机译:来自rass sodar数据的低气压下的风速和温度曲线拟合

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摘要

Analysis of wind speed and temperature is important to describe momentum and heat exchanges and for wind energy applications. A near 20-month database from a Radio Acoustic Sounding System (RASS) sodar located on a plateau in Northern Spain was used. Autocorrelation functions calculated for wind speed and temperature at 40 and 200 m revealed that only the daily cycle is relevant for wind speed, whereas both yearly and daily cycles are for temperature. Cross correlations, calculated between 40 and 400 m (in 20 m steps), have shown a thermal lag of about 30 min at certain levels. Three filters (weighted moving average, moving median, and statistically based) were used with a time interval of about 2 h to eliminate noise, resulting in similar behaviour for filtered data. Wind speed and temperature profiles were fitted to simple two parameter expressions (linear, logarithmic, and power-law). Although the highest number of fits at the 1% significance level is for linear profiles, comparison of profiles showed that power-law profiles have the highest correlation coefficients for wind speed and linear profiles for temperature. The number of satisfactory fits increased when a filter was used. Hourly evolution of profiles was also studied and linear profiles were satisfactory for wind speed during the day. Autocorrelations of the two parameters used in the three fitting profiles were calculated and also modelled with a harmonic equation. No cyclic pattern was observed for wind speed profile parameters, although it was for temperature profile parameters. Finally, a weighted moving average filter and a robust calculation with 13 close in time profiles made the cycles of both parameters more noticeable.
机译:风速和温度的分析对于描述动量和热交换以及用于风能应用非常重要。使用了位于西班牙北部高原的无线电声探系统(RASS)声雷达的近20个月的数据库。针对40和200 m处的风速和温度计算的自相关函数表明,只有每日周期与风速有关,而年度和每日周期都与温度有关。在40到400 m之间(以20 m为步长)计算出的互相关表明,在某些水平下,热滞后约为30分钟。使用三个过滤器(加权移动平均值,移动中值和基于统计的过滤器),间隔约2小时以消除噪声,从而使过滤后的数据具有相似的行为。风速和温度曲线适合简单的两个参数表达式(线性,对数和幂律)。尽管在1%显着性水平上拟合的最高数量是线性轮廓,但轮廓比较显示,幂律轮廓的风速相关系数最高,而温度的线性相关系数最高。当使用过滤器时,令人满意的配合次数增加。还研究了廓线的每小时变化,并且线性廓线对于白天的风速是令人满意的。计算了三个拟合轮廓中使用的两个参数的自相关,并用谐波方程建模。尽管是温度曲线参数,但没有观察到风速曲线参数的循环模式。最终,加权移动平均滤波器和具有13个时间接近的轮廓的稳健计算使这两个参数的周期更加引人注目。

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