Spatiotemporal variation of upper-air and surface wind speed and its influencing factors in northwestern China during 1980–2012

2017 ◽  
Vol 133 (3-4) ◽  
pp. 1303-1314 ◽  
Author(s):  
Jili Zheng ◽  
Baofu Li ◽  
Yaning Chen ◽  
Zhongsheng Chen ◽  
Lishu Lian
2019 ◽  
Vol 32 (21) ◽  
pp. 7421-7435 ◽  
Author(s):  
Zhengtai Zhang ◽  
Kaicun Wang ◽  
Deliang Chen ◽  
Jianping Li ◽  
Robert Dickinson

Abstract During 1973–2014, a reduction trend in the observed surface wind speed (10 m) in the Northern Hemisphere lands has been widely reported; this reduction is referred to as “global stilling.” The primary determining factors of global stilling include atmospheric circulation, turbulent friction, and surface friction when ignoring the vertical influencing factors. Most of the existing studies on the attribution of global stilling do not take changing surface friction into account. In addition, there are other changes in the climate system, such as aerosol loading, which could have an impact on atmospheric circulation, but are not included in the majority of current models either. Here, we developed a novel approach based on modeled winds calculated from sea level pressure observations and applied the method to approximately 4000 weather stations in the Northern Hemisphere lands from 1973 to 2014 to attribute the stilling in the three factors. In our methods, we neglected the vertical influencing factors on surface wind speed but took the aerosols’ changes on atmospheric circulation and gradual urbanization effect on surface wind speed into account. We found that atmospheric circulation has dictated the monthly variation in surface wind speed during the past four decades. However, the increased surface friction dominates the long-term declining trend of wind stilling. Our studies had uncertainties while neglecting the influence of vertical factors on surface wind stilling, despite most of the existing studies showing their effect was minor compared to the three factors explored in our study.


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.


2020 ◽  
Vol 12 (2) ◽  
pp. 155-164
Author(s):  
He Fang ◽  
William Perrie ◽  
Gaofeng Fan ◽  
Tao Xie ◽  
Jingsong Yang

2008 ◽  
Vol 25 (7) ◽  
pp. 1218-1227 ◽  
Author(s):  
Ming-Huei Chang ◽  
Ren-Chieh Lien ◽  
Yiing Jang Yang ◽  
Tswen Yung Tang ◽  
Joe Wang

Abstract Surface signatures and interior properties of large-amplitude nonlinear internal waves (NLIWs) in the South China Sea (SCS) were measured during a period of weak northeast wind (∼2 m s−1) using shipboard marine radar, an acoustic Doppler current profiler (ADCP), a conductivity–temperature–depth (CTD) profiler, and an echo sounder. In the northern SCS, large-amplitude NLIWs propagating principally westward appear at the tidal periodicity, and their magnitudes are modulated at the spring–neap tidal cycle. The surface scattering strength measured by the marine radar is positively correlated with the local wind speed when NLIWs are absent. When NLIWs approach, the surface scattering strength within the convergence zone is enhanced. The sea surface scattering induced by NLIWs is equivalent to that of a ∼6 m s−1 surface wind speed (i.e., 3 times greater than the actual surface wind speed). The horizontal spatial structure of the enhanced sea surface scattering strength predicts the horizontal spatial structure of the NLIW. The observed average half-amplitude full width of NLIWs λη/2 is 1.09 ± 0.2 km; the average half-amplitude full width of the enhanced scattering strength λI/2 is ∼0.57 λη/2. The average half-amplitude full width of the enhanced horizontal velocity convergence of NLIWs λ∂xu/2 is approximately equal to λI/2. The peak of the enhanced surface scattering leads the center of NLIWs by ∼0.46 λη/2. NLIW horizontal velocity convergence is positively correlated with the enhancement of the surface scattering strength. NLIW amplitude is positively correlated with the spatial integration of the enhancement of the surface scattering strength within the convergence zone of NLIWs. Empirical formulas are obtained for estimating the horizontal velocity convergence and the amplitude of NLIWs using radar measurements of surface scattering strength. The enhancement of the scattering strength exhibits strong asymmetry; the scattering strength observed from behind the propagating NLIW is 24% less than that observed ahead, presumably caused by the skewness and the breaking of surface waves induced by NLIWs. Above the center of NLIWs, the surface scattering strength is enhanced slightly, associated with isotropic surface waves presumably induced or modified by NLIWs. This analysis concludes that in low-wind conditions remote sensing measurements may provide useful predictions of horizontal velocity convergences, amplitudes, and spatial structures of NLIWs. Further applications and modification of the presented empirical formulas in different conditions of wind speed, surface waves, and NLIWs or with other remote sensing methods are encouraged.


2014 ◽  
Vol 119 (2) ◽  
pp. 584-593 ◽  
Author(s):  
Marion Benetti ◽  
Gilles Reverdin ◽  
Catherine Pierre ◽  
Liliane Merlivat ◽  
Camille Risi ◽  
...  

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