Comparison of horizontal wind observed by wind profiler radars with ERA5 reanalysis data in Anhui, China

Abstract

The wind pro ler radar network at Anhui province in China was completely constructed for improving warning capacity of meteorological disasters in 2019. In order to verify its proper performance, vertical pro les of horizontal winds were compared with ERA5 reanalysis data during the period January to December in 2021. The wind pro ler radars behave good capability in measuring the atmospheric wind with high data collection rates (> 80%). Furthermore, data availabilities of WPRs decrease with the increase of altitudes and they are mostly greater than 90% below 3km in day without precipitation, indicating that the annual mean of the effective detection height is about 2-3km with maximum value (4-6km) in summer and minimum value (around 2km) in winter. More importantly, the WPRs shows excellent agreement with the ERA5 zonal (correlation coe cients > 0.89 and standard deviations < 2.57m/s) and meridional winds (correlation coe cients > 0.76 and standard deviations < 3.26 m/s) in most stations. Also, the biases show a broadly Gaussian character in zonal winds and meridional winds and they are all close to zero. The differences of horizontal wind between wind pro ler radars and ERA5 present a function of altitude. Normally, not only zonal winds but also meridional winds at low level can performance better than those at upper level. Meanwhile, due to the difference of atmospheric turbulent between day and night, statistical parameters of comparison during day time behave better than those at night. The result shows that the wind pro ler radar network at Anhui is capable of providing good quality wind data in PBL for numerical model and weather processes studies in future.

Assessment of Wind and Solar Power Potential and Their Temporal Complementarity in China’s Northwestern Provinces: Insights from ERA5 Reanalysis

“…Characterized by a spatiotemporal resolution of 0.1 • (approximately 10 km) and 1 h, this dataset integrates 240 surface variables, including parameters such as temperature, pressure, wind speed, and radiation. In distinct areas within China, such as Anhui [40] and the southeastern coast [41], the efficacy of the ERA5-land dataset in mimicking observations had been previously confirmed, particularly in its capacity to reflect wind speed and radiation spatiotemporal distribution dynamics. However, the validation of this dataset had yet to be executed for the northwestern provinces under examination.…”

Application of WRF-LES on the Simulation of Seasonal Characteristics of Atmospheric Boundary Layer Structure in Taklamakan Desert

“…All observation data were converted to the coordinated universal time (UTC) for consistency with the model output. With high spatio-temporal resolution and global data assimilation, ERA5 meets the analysis requirements and is widely used for model verification [25][26][27]. ERA5 reanalysis data were used to evaluate model performance over continuous time periods [28].…”

“…A large eddy simulation (LES) embedded in a nested WRF v4.5.1 model system was implemented in this study with five nested domains. The outer three mesoscale domains employed a conventional 1D PBL scheme to parameterize sub-grid turbulence, while the With high spatio-temporal resolution and global data assimilation, ERA5 meets the analysis requirements and is widely used for model verification [25][26][27]. ERA5 reanalysis data were used to evaluate model performance over continuous time periods [28].…”

Wind Energy Resources at Antarctic Stations Based on ERA5

“…The wind field data selected for this study is the ERA5 reanalysis dataset, which covers the whole globe, including 10 m wind field data from 1940 to present, with a spatial resolution of 0.25 • and a temporal resolution of 1 h. Previous studies have investigated the accuracy of ERA5 in simulating wind speed. ERA5 has problems with poor simulation quality in mountainous areas, overestimating low-level wind speeds, and underestimating high-level wind speeds [14,[17][18][19]. However, it still accurately reproduces wind speed distribution and describes overall wind characteristics [18][19][20][21][22].…”