Evaluation of Blended Wind Products and Their Implications for Offshore Wind Power Estimation

Author:

Wang Xiaochun1ORCID,Lee Tong2ORCID,Mears Carl3ORCID

Affiliation:

1. Joint Institute for Regional Earth System Science and Engineering, University of California at Los Angeles, Los Angeles, CA 90095, USA

2. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA

3. Remote Sensing Systems, Santa Rosa, CA 95401, USA

Abstract

The Cross-Calibrated Multi-Platform (CCMP) wind analysis is a satellite-based blended wind product produced using a two-dimensional variational method. The current version available publicly is Version 2 (CCMP2.0), which includes buoy winds in addition to satellite winds. Version 3 of the product (CCMP3.0) is being produced with several improvements in analysis algorithms, without including buoy winds. Here, we compare CCMP3.0 with a special version of CCMP2.0 that did not include buoy winds, so both versions are independent of buoy measurements. We evaluate them using wind data from buoys around the coasts of the United States and discuss the implications for the wind power industry and offshore wind farms. CCMP2.0 uses ERA-Interim 10 m winds as the background to fill observational gaps. CCMP3.0 uses ERA5 10 m neutral winds as the background. Because ERA5 winds are biased towards lower values at higher wind conditions, CCMP3.0 corrected this bias by matching ERA5 wind speeds with satellite scatterometer wind speeds using a histogram matching method. Our evaluation indicates that CCMP3.0 has better agreement with the independent buoy winds, primarily for higher winds (>10 m/s). This is reflected by the higher correlation and lower root-mean-squared differences of CCMP3.0 versus buoy winds, especially for higher wind conditions. For the U.S. coastal region (within 200 km), the mean wind speed of CCMP3.0 is enhanced by 1–2%, and the wind speed standard deviation is enhanced by around 3–5%. These changes in wind speed and its standard deviation from CCMP2.0 to CCMP3.0 cause an 8–12% increase in wind power density. The wind power density along the U.S. coastal region is also correlated with various climate indices depending on locations, providing a useful approach for predicting wind power on subseasonal to interannual timescales.

Funder

Ocean Vector Wind Science Team of the National Aeronautics and Space Administration

NASA

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Sea Surface Wind Speed Estimation From the Combination of Satellite Scatterometer and Radiometer Parameters;Journal of Geophysical Research: Machine Learning and Computation;2024-07-05

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