scholarly journals Deliverable D12 – Distributed Wind Data Catalog Development Guide and Instruction Manual

2021 ◽  
Author(s):  
Danielle Preziuso ◽  
Anna Maria Sempreviva ◽  
Alice Orrell
Keyword(s):  
Wind Data ◽  
Instruction Manual

scholarly journals Evaluation of HRCLDAS and ERA5 Datasets for Near-Surface Wind over Hainan Island and South China Sea

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 766
Author(s):  
Yi Jiang ◽  
Shuai Han ◽  
Chunxiang Shi ◽  
Tao Gao ◽  
Honghui Zhen ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Surface Wind ◽  
Hainan Island ◽  
The South China Sea ◽  
Wind Data ◽  
The South ◽  
Near Surface ◽  
China Sea

Near-surface wind data are particularly important for Hainan Island and the South China Sea, and there is a wide range of wind data sources. A detailed understanding of the reliability of these datasets can help us to carry out related research. In this study, the hourly near-surface wind data from the High-Resolution China Meteorological Administration (CMA) Land Data Assimilation System (HRCLDAS) and the fifth-generation ECMWF atmospheric reanalysis data (ERA5) were evaluated by comparison with the ground automatic meteorological observation data for Hainan Island and the South China Sea. The results are as follows: (1) the HRCLDAS and ERA5 near-surface wind data trend was basically the same as the observation data trend, but there was a smaller bias, smaller root-mean-square errors, and higher correlation coefficients between the near-surface wind data from HRCLDAS and the observations; (2) the quality of HRCLDAS and ERA5 near-surface wind data was better over the islands of the South China Sea than over Hainan Island land. However, over the coastal areas of Hainan Island and island stations near Sansha, the quality of the HRCLDAS near-surface wind data was better than that of ERA5; (3) the quality of HRCLDAS near-surface wind data was better than that of ERA5 over different types of landforms. The deviation of ERA5 and HRCLDAS wind speed was the largest along the coast, and the quality of the ERA5 wind direction data was poorest over the mountains, whereas that of HRCLDAS was poorest over hilly areas; (4) the accuracy of HRCLDAS at all wind levels was higher than that of ERA5. ERA5 significantly overestimated low-grade winds and underestimated high-grade winds. The accuracy of HRCLDAS wind ratings over the islands of the South China Sea was significantly higher than that over Hainan Island land, especially for the higher wind ratings; and (5) in the typhoon process, the simulation of wind by HRCLDAS was closer to the observations, and its simulation of higher wind speeds was more accurate than the ERA5 simulations.

scholarly journals Offshore Wind Energy Resource Assessment across the Territory of Oman: A Spatial-Temporal Data Analysis

2021 ◽  
Vol 13 (5) ◽  
pp. 2862
Author(s):  
Amer Al-Hinai ◽  
Yassine Charabi ◽  
Seyed H. Aghay Kaboli
Keyword(s):  
Data Analysis ◽  
Wind Energy ◽  
Wind Turbines ◽  
Energy Resource ◽  
Wind Farms ◽  
Offshore Wind ◽  
Wind Data ◽  
Offshore Wind Energy ◽  
Offshore Wind Turbines ◽  
Wind Potential

Despite the long shoreline of Oman, the wind energy industry is still confined to onshore due to the lack of knowledge about offshore wind potential. A spatial-temporal wind data analysis is performed in this research to find the locations in Oman’s territorial seas with the highest potential for offshore wind energy. Thus, wind data are statistically analyzed for assessing wind characteristics. Statistical analysis of wind data include the wind power density, and Weibull scale and shape factors. In addition, there is an estimation of the possible energy production and capacity factor by three commercial offshore wind turbines suitable for 80 up to a 110 m hub height. The findings show that offshore wind turbines can produce at least 1.34 times more energy than land-based and nearshore wind turbines. Additionally, offshore wind turbines generate more power in the Omani peak electricity demand during the summer. Thus, offshore wind turbines have great advantages over land-based wind turbines in Oman. Overall, this work provides guidance on the deployment and production of offshore wind energy in Oman. A thorough study using bankable wind data along with various logistical considerations would still be required to turn offshore wind potential into real wind farms in Oman.

scholarly journals A Field Measurement Based Wind Characteristics Analysis of a Typhoon in Near-Ground Boundary Layer

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 873
Author(s):  
Dandan Xia ◽  
Liming Dai ◽  
Li Lin ◽  
Huaifeng Wang ◽  
Haitao Hu
Keyword(s):  
Turbulence Intensity ◽  
Field Measurement ◽  
Three Dimensional ◽  
Wind Data ◽  
Statistical Characteristics ◽  
Gust Factor ◽  
Characteristics Analysis ◽  
Wind Characteristics ◽  
The Mean ◽  
The Relationship

The field measurement was conducted to observe the wind field data of West Pacific typhoon “Maria” in this research. With the application of ultrasonic anemometers installed in different heights (10 m, 80 m, 100 m) of the tower, the three dimensional wind speed data of typhoon “Maria” was acquired. In addition, vane-type anemometers were installed to validate the accuracy of the wind data from ultrasonic anemometers. Wind characteristics such as the mean wind profile, turbulence intensity, integral length scale, and wind spectrum are studied in detail using the collected wind data. The relationship between the gust factor and turbulence intensity was also studied and compared with the existing literature to demonstrate the characteristics of Maria. The statistical characteristics of the turbulence intensity and gust factor are presented. The corresponding conclusion remarks are expected to provide a useful reference for designing wind-resistant buildings and structures.

scholarly journals Climatic Analysis of Wind Patterns to Enhance Sailors’ Performance during Races

Climate ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 80
Author(s):  
Pietro Masino ◽  
Roberto Bellasio ◽  
Roberto Bianconi ◽  
Angelo Besana ◽  
Alessandro Pezzoli
Keyword(s):  
Support Service ◽  
Sport Performance ◽  
Meteorological Conditions ◽  
Meteorological Variables ◽  
Wind Data ◽  
Weather Research And Forecasting ◽  
Innovative Method ◽  
Combined Use ◽  
The Impact ◽  
Wind Patterns

The impact of environmental and meteorological conditions when dealing with sport performance has been demonstrated by several studies carried out in recent years. Among the meteorological variables with the greatest effect are temperature, humidity, precipitation, and wind direction and speed. This research focused on analyzing and forecasting the wind patterns occurring in Enoshima Bay (Japan). In particular, the objective of this study was to provide support and guidance to sailors in the preparation of the race strategy, thanks to an in-depth knowledge of these meteorological variables. To do this, an innovative method was used. First, through the combined use of Weather Research and Forecasting (WRF) and CALMET models, a simulation was performed, in order to reconstruct an offshore database of a recent 10-year period (2009–2018) over the race area, inside the bay. Subsequently, the verification of hind-cast was performed: the wind data measured at sea were compared with the data extracted from the CALMET database to verify the validity of the model. The verification was performed through three statistical indexes: BIAS, MAE, and PCC. The analysis showed mixed results, depending on the examined pattern, but made it possible to identify the days that best simulated the reality. Then, the wind data from the selected days were summarized and collected in plots, tables, and maps to design a decision support service (DSS), in order to provide athletes with the necessary information in a simple and effective way. In conclusion, we state that the application of this method extends beyond the sports field. Indeed, the study of wind patterns may be necessary in the design of actions to contrast and adapt to climate change, particularly in coastal areas.

Sign in / Sign up

Export Citation Format

Share Document