A regression-based statistical correction of mesoscale simulations for near-surface wind speed using remotely sensed surface observations

2012 ◽  
Vol 48 (4) ◽  
pp. 449-456 ◽  
Author(s):  
Do-Yong Kim ◽  
Jin-Young Kim ◽  
Jae-Jin Kim
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Remotely Sensed ◽  
Near Surface ◽  
Statistical Correction ◽  
Mesoscale Simulations ◽  
Surface Observations

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

scholarly journals An experimental 2DVAR retrieval using AMSR2

2019 ◽  
Author(s):  
David Ian Duncan ◽  
Patrick Eriksson ◽  
Simon Pfreundschuh
Keyword(s):  
Wind Speed ◽  
Spatial Resolution ◽  
Spatial Scales ◽  
Surface Wind ◽  
Optimal Estimation ◽  
Surface Wind Speed ◽  
Model Errors ◽  
Near Surface ◽  
Noise Characteristics ◽  
Microwave Imager

Abstract. A two-dimensional variational retrieval (2DVAR) is presented for a passive microwave imager. The overlapping antenna patterns of all frequencies from the Advanced Microwave Scanning Radiometer-2 (AMSR2) are explicitly simulated to attempt retrieval of near surface wind speed and surface skin temperature at finer spatial scales than individual antenna beams. This is achieved, with the effective spatial resolution of retrieved parameters shown by analysis of 2DVAR averaging kernels. Sea surface temperature retrievals achieve about 30 km resolution, with wind speed retrievals at about 10 km resolution. It is argued that multi-dimensional optimal estimation permits greater use of total information content from microwave sensors than other methods, with no compromises on target resolution needed; instead, various targets are retrieved at the highest possible spatial resolution, driven by the channels' sensitivities. All AMSR2 channels can be simulated within near their published noise characteristics for observed clear-sky scenes, though calibration and emissivity model errors are key challenges. This experimental retrieval shows the feasibility of 2DVAR for cloud-free retrievals, and opens the possibility of standalone 3DVAR retrievals of water vapour and hydrometeor fields from microwave imagers in the future. The results have implications for future satellite missions and sensor design, as spatial oversampling can somewhat mitigate the need for larger antennas in the push for higher spatial resolution.

scholarly journals Projected changes in global terrestrial near-surface wind speed in 1.5–4.0 ℃ global warming levels

2021 ◽  
Author(s):  
Jinlin Zha ◽  
Cheng Shen ◽  
Zhibo Li ◽  
Jian Wu ◽  
Deming Zhao ◽  
...  
Keyword(s):  
Global Warming ◽  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Projected Changes
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