Temporal-spatial cross-correlation analysis of non-stationary near-surface wind speed time series

2017 ◽  
Vol 24 (3) ◽  
pp. 692-698 ◽  
Author(s):  
Ming Zeng ◽  
Jing-hai Li ◽  
Qing-hao Meng ◽  
Xiao-nei Zhang
2021 ◽  
Author(s):  
Eduardo Utrabo-Carazo ◽  
Cesar Azorin-Molina ◽  
Enric Aguilar ◽  
Manola Brunet

<p>Conventional time series analysis of observed near-surface wind speed (SWS) have focused both on mean values and on the sign, magnitude and statistical significance of trends. Specifically, a decrease in the SWS has been detected in continental surfaces of the planet's mid-latitudes from 1979 to 2010 approximately, the so-called <em>stilling</em> phenomenon; and an increase from 2010 until now, the <em>reversal</em> phenomenon. However, although various hypotheses have been proposed in the scientific literature, the mechanisms behind these phenomena and what evolution this parameter will follow in the future are still understudied, mainly because the response of a variable dependent on atmospheric circulation, such as wind speed, to a warming climate is uncertain. This study aims to use spectral analysis (Fourier and wavelet) to determine the most significant frequency modes associated with the SWS time series in the Iberian Peninsula (IP), for both mean wind speed and daily peak wind gusts, as well as its temporal evolution for 1961-2019. Subsequently, this study will also attempt to relate these modes to those corresponding to various modes of ocean-atmosphere variability such as the El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) or, due to the influence of sudden stratospheric warming (SSW) in the European troposphere, the polar vortex. The ultimate goal will be to explore possible sources of predictability in the medium-long term for SWS across the IP, which would have direct applications in areas such as: wind-power generation, agriculture, air quality, insurance and fishing industries, among many others socioeconomic and environmental issues. </p>


2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.


Urban Climate ◽  
2020 ◽  
Vol 34 ◽  
pp. 100703
Author(s):  
Yonghong Liu ◽  
Yongming Xu ◽  
Fangmin Zhang ◽  
Wenjun Shu

Sign in / Sign up

Export Citation Format

Share Document