scholarly journals Homogenization and Assessment of Observed Near-Surface Wind Speed Trends across Sweden, 1956–2013

2016 ◽  
Vol 29 (20) ◽  
pp. 7397-7415 ◽  
Author(s):  
Lorenzo Minola ◽  
Cesar Azorin-Molina ◽  
Deliang Chen
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Surface Wind ◽  
Geostrophic Wind ◽  
Surface Wind Speed ◽  
Downward Trend ◽  
Near Surface ◽  
Speed Increase ◽  
Nao Index ◽  
Positive Tendency

Abstract Multidecadal variability of observed near-surface wind speed from 24 stations across Sweden has been analyzed for 1956–2013, with a focus on 1979–2008 (incorporating an additional 9 stations) for comparison with previous studies. Wind speed data have been subjected to a robust data processing protocol, consisting of quality control, reconstruction, and homogenization, by using geostrophic wind speed series as reference. The homogenized dataset displays a significant (at p < 0.05) downward trend for 1956–2013 (−0.06 m s−1 decade−1) and an even larger decreasing trend for 1979–2008 (−0.14 m s−1 decade−1). However, differences have been observed seasonally, with significant decreasing values in spring, summer, and autumn and a small downward trend in winter for 1956–2013. Most interestingly, a nonsignificant wind speed increase has been detected in winter for 1979–2008, which contrasts with the marked “stilling” reported for this season in much of midlatitude regions. The decreasing rate in wind speed is larger for coastal stations and in the southern part of Sweden. Decreasing trends were found at 91.7% of the stations during summer, whereas 58.3% of the stations displayed decreasing trends in winter. On the contrary, increasing trends occurred in 41.7% of the stations for winter and in only 8.3% for summer. The possible impact of the North Atlantic Oscillation (NAO) index has also been investigated, showing evidence that the small increasing trend in winter for 1979–2008 is hypothetically associated with the positive tendency of the NAO index during the last decades. These results reveal the influence of large-scale atmospheric circulation on wind speed variability across Sweden.

scholarly journals Multiple Regimes of Wind, Stratification, and Turbulence in the Stable Boundary Layer

2015 ◽  
Vol 72 (8) ◽  
pp. 3178-3198 ◽  
Author(s):  
Adam H. Monahan ◽  
Tim Rees ◽  
Yanping He ◽  
Norman McFarlane
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Cloud Cover ◽  
Large Scale ◽  
Potential Temperature ◽  
Surface Wind ◽  
Geostrophic Wind ◽  
Gradient Force ◽  
Pressure Gradient Force ◽  
Near Surface

Abstract A long time series of temporally high-resolution wind and potential temperature data from the 213-m tower at Cabauw in the Netherlands demonstrates the existence of two distinct regimes of the stably stratified nocturnal boundary layer at this location. Hidden Markov model (HMM) analysis is used to objectively characterize these regimes and classify individual observed states. The first regime is characterized by strongly stable stratification, large wind speed differences between 10 and 200 m, and relatively weak turbulence. The second is associated with near-neutral stratification, weaker wind speed differences between 10 and 200 m, and relatively strong turbulence. In this second regime, the state of the boundary layer is similar to that during the day. The occupation statistics of these regimes are shown to covary with the large-scale pressure gradient force and cloud cover such that the first regime predominates under clear skies with weak geostrophic wind speed and the second regime predominates under conditions of extensive cloud cover or large geostrophic wind speed. These regimes are not distinguished by standard measures of stability, such as the Obukhov length or the bulk Richardson number. Evidence is presented that the mechanism generating these distinct regimes is associated with a previously documented feedback resulting from the existence of an upper limit on the maximum downward heat flux that can be sustained for a given near-surface wind speed.

scholarly journals Centennial-scale variability of terrestrial near-surface wind speed over China from reanalysis

2021 ◽  
pp. 1-52
Author(s):  
Cheng Shen ◽  
Jinlin Zha ◽  
Jian Wu ◽  
Deming Zhao
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Stepwise Regression ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Wind Speeds ◽  
Ocean Atmosphere ◽  
Forward Stepwise ◽  
Strong Winds

AbstractInvestigations of variations and causes of near-surface wind speed (NWS) further understanding of the atmospheric changes and improve the ability of climate analysis and projections. NWS varies on multiple temporal scales; however, the centennial-scale variability in NWS and associated causes over China remains unknown. In this study, we employ the European Centre for Medium-Range Weather Forecasts (ECMWF) twentieth century reanalysis (ERA-20C) to study the centennial-scale changes in NWS from 1900–2010. Meanwhile, a forward stepwise regression algorithm is used to reveal the relationships between NWS and large-scale ocean-atmosphere circulations. The results show three unique periods in annual mean NWS over China from 1900–2010. The annual mean NWS displayed a decreasing trend of -0.87% decade-1 and -11.75% decade-1 from 1900–1925 and 1957–2010, respectively, which were caused by the decreases in the days with strong winds, with trends of -6.64 and -4.66 days decade-1, respectively. The annual mean NWS showed an upward trend of 55.47% decade-1 from 1926–1956, which was caused by increases in the days with moderate (0.43 days decade-1) and strong winds (23.55 days decade-1). The reconstructed wind speeds based on forward stepwise regression algorithm matched well with the original wind speeds; therefore, the decadal changes in NWS over China at centennial-scale were mainly induced by large-scale ocean-atmosphere circulations, with the total explanation power of 66%. The strongest explanation power was found in winter (74%), and the weakest explanation power was found in summer (46%).

Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Recurrence Plot ◽  
Sampling Frequency ◽  
Near Surface ◽  
Gas Leakage ◽  
Time Period ◽  
Characteristics Analysis ◽  
Quantification Analysis

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.

A preliminary study on the influence of Beijing urban spatial morphology on near-surface wind speed

Urban Climate ◽  
2020 ◽  
Vol 34 ◽  
pp. 100703
Author(s):  
Yonghong Liu ◽  
Yongming Xu ◽  
Fangmin Zhang ◽  
Wenjun Shu
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Spatial Morphology ◽  
Preliminary Study

scholarly journals Wind Speed Forecast Based on Post-Processing of Numerical Weather Predictions Using a Gradient Boosting Decision Tree Algorithm

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 738 ◽  
Author(s):  
Wenqing Xu ◽  
Like Ning ◽  
Yong Luo
Keyword(s):  
Wind Speed ◽  
Decision Tree ◽  
Wind Power ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Gradient Boosting ◽  
Post Processing ◽  
Near Surface ◽  
Wind Power Forecasting ◽  
Numerical Weather

With the large-scale development of wind energy, wind power forecasting plays a key role in power dispatching in the electric power grid, as well as in the operation and maintenance of wind farms. The most important technology for wind power forecasting is forecasting wind speed. The current mainstream methods for wind speed forecasting involve the combination of mesoscale numerical meteorological models with a post-processing system. Our work uses the WRF model to obtain the numerical weather forecast and the gradient boosting decision tree (GBDT) algorithm to improve the near-surface wind speed post-processing results of the numerical weather model. We calculate the feature importance of GBDT in order to find out which feature most affects the post-processing wind speed results. The results show that, after using about 300 features at different height and pressure layers, the GBDT algorithm can output more accurate wind speed forecasts than the original WRF results and other post-processing models like decision tree regression (DTR) and multi-layer perceptron regression (MLPR). Using GBDT, the root mean square error (RMSE) of wind speed can be reduced from 2.7–3.5 m/s in the original WRF result by 1–1.5 m/s, which is better than DTR and MLPR. While the index of agreement (IA) can be improved by 0.10–0.20, correlation coefficient be improved by 0.10–0.18, Nash–Sutcliffe efficiency coefficient (NSE) be improved by −0.06–0.6. It also can be found that the feature which most affects the GBDT results is the near-surface wind speed. Other variables, such as forecast month, forecast time, and temperature, also affect the GBDT results.

scholarly journals Uncertainty in recent near-surface wind speed trends: a global reanalysis intercomparison

2017 ◽  
Vol 12 (11) ◽  
pp. 114019 ◽  
Author(s):  
Verónica Torralba ◽  
Francisco J Doblas-Reyes ◽  
Nube Gonzalez-Reviriego
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Global Reanalysis ◽  
Reanalysis Intercomparison
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