Scaling Analysis of the China France Oceanography Satellite Along‐Track Wind and Wave Data

Gao, Yang; Schmitt, François G; Hu, Jianyu; Huang, Yongxiang

doi:10.1029/2020jc017119

Cited by 5 publications

(3 citation statements)

References 75 publications

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“…Sand and dust storms (SDSs) not only are common meteorological hazards accompanying the occurrence of acid rain (Yin et al, 1996;Terada et al, 2002) and impacts on the marine biological system (Zhuang et al, 1992;Jickells et al, 2005) but have also caused harm to human health (Hefflin et al, 1994;Goudie, 2009) and led to serious air pollution (Chang et al, 1996;Borbély-Kiss et al, 2004). These phenomena can damage infrastructure, telecommunication and crops; affect transportation through reduced visibility; and cause tremendous economic losses (UNESCAPReport, 2018).…”

Section: Introductionmentioning

confidence: 99%

High-frequency observation during sand and dust storms at the Qingtu Lake Observatory

Huang

Wang

et al. 2021

Earth Syst. Sci. Data

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Abstract. Partially due to global climate change, sand and dust storms (SDSs) have occurred more and more frequently, yet a detailed measurement of SDS events at different heights is still lacking. Here we provide a high-frequency observation from the Qingtu Lake Observation Array (QLOA), China. The wind and dust information were measured simultaneously at different wall-normal heights during the SDS process. The datasets span the period from 17 March to 9 June 2016. The wind speed and direction are recorded by a sonic anemometer with a sampling frequency of 50 Hz, while particulate matter with a diameter of 10 µm or less (PM10) is sampled simultaneously by a dust monitor with a sampling frequency of 1 Hz. The wall-normal array had 11 sonic anemometers and monitors spaced logarithmically from z=0.9 to 30 m, where the spacing is about 2 m between the sonic anemometer and dust monitor at the same height. Based on its nonstationary feature, an SDS event can be divided into three stages, i.e., ascending, stabilizing and descending stages, in which the dynamic mechanism of the wind and dust fields might be different. This is preliminarily characterized by the classical Fourier power analysis. Temporal evolution of the scaling exponent from Fourier power analysis suggests a value slightly below the classical Kolmogorov value of -5/3 for the three-dimensional homogeneous and isotropic turbulence. During the stabilizing stage, the collected PM10 shows a very intermittent pattern, which can be further linked with the burst events in the turbulent atmospheric boundary layer. This dataset is valuable for a better understanding of SDS dynamics and is publicly available in a Zenodo repository at https://doi.org/10.5281/zenodo.5034196 (Li et al., 2021a).

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Section: Introductionmentioning

confidence: 99%

High-frequency observation during sand and dust storms at the Qingtu Lake Observatory

Huang

Wang

et al. 2021

Earth Syst. Sci. Data

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“…In the same year, Pierson and Marks (1952) performed a spectral analysis of the wave data, considering frequencies (or wavenumbers), the direction and height of the waves. After that, spectral analysis has been widely used to study the wind-wave relation, using data from field observations, remote sensing, laboratory, and numerical experiments (Wen, 1960;Pierson and Moskowitz, 1964;Wu, 1968;Hasselmann et al, 1973;Carter, 1982;Zhang et al, 2009;Rusu et al, 2014;Gao et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Probability-based wind-wave relation

Gao

Schmitt²,

Hu³

et al. 2023

Front. Mar. Sci.

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In a fully developed sea, the significant wave height (Hs) and wind speed (U10) are conventionally related to a pure quadratic equation. This relation is often violated, since in the field the measured local Hs is often contaminated by the swell, which is propagated from distant places. Therefore, a swell partition is required before the establishment of the wind-wave relation. The Spectra Energy Partition (SEP) is regarded as the best way to isolate the swell and the wind wave relation: it is based on the identification of a separation frequency in the ocean wave spectrum. However, for most field observations, the wave spectra information is unavailable, and thus the SEP is inapplicable. This work proposes a probability-based algorithm to identify the averaged swell without knowing the wave spectrum a priori. The local wind-wave relation is established by either a linear or an energy-conserved decomposition. We also find that the local wind-wave relation is a power-law when the wind speed U10 is above 4 m/s. The proposed method is first validated by applying the SEP method to buoy collected wave spectra data. The global pattern of the swell and the local wind waves is retrieved by applying the proposed method to a 17-year wind and wave database from the JASON satellite. Strong seasonal and spatial variations are obtained. Finally, a prediction model based on the empirical wind-wave relation is shown to successfully retrieve the wave field when the wind field is available.

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“…Compared with other in-orbit scatterometers, a wind vector cell (WVC) of CSCAT is generally viewed 2-8 times by its new rotating fan-beam observation geometry, which opens up opportunities to improve the quality of retrieved surface wind field. The current wind inversion method of CSCAT is adapted from the well-developed pencil-beam scatterometer (Gao et al, 2021;Li et al, 2021;Liu et al, 2020;Xu et al, 2019;Yun et al, 2021;Zhao et al, 2021).…”

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confidence: 99%

Validation of the CFOSAT Scatterometer Data With Buoy Observations and Tests of Operational Application to Extreme Weather Forecasts in Taiwan Strait

Zhu

Chen

et al. 2022

Earth and Space Science

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The China‐France Oceanography Satellite (CFOSAT) launched in 2018 is equipped with the Chinese Scatterometer (CSCAT), which is designed to measure high‐precision sea surface wind fields in the global ocean. This study aims to validate the CFOSAT wind fields with moored buoy‐measured ground truth data from August 2019 to July 2021. The test area was chosen as the Taiwan Strait, which is an important navigation channel and rich fishery grounds in the East Asia. It is also a high wind speed area particularly during typhoons and cold air passages. Thus, the accurate wind forecasts are crucially needed to avoid capsizing and casualties. The validation results give the correlation coefficient (R2) of 0.92, the root mean square error (RMSE) of 1.75 m s−1, and the absolute deviation (AD) of 1.10 m s−1 for the wind speeds, and R2 of 0.96, the RMSE of 21.87°, and the AD of 1.17° for the wind directions. During cold air passages, the AD of wind speeds decreases to 1.03 m s−1, which is smaller than 1.17 m s−1 during typhoons. Using the CFOSAT wind as historical observation data for refining of forecast work was tested by model output statistics revised method. The test results show that the refined forecast results of wind fields are improved up to 4%–17%. Thus, the validation and test results obtained in this study indicate that updating satellite winds would have great contributions to refined forecasting of local sea surface winds.

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Scaling Analysis of the China France Oceanography Satellite Along‐Track Wind and Wave Data

Cited by 5 publications

References 75 publications

High-frequency observation during sand and dust storms at the Qingtu Lake Observatory

High-frequency observation during sand and dust storms at the Qingtu Lake Observatory

Probability-based wind-wave relation

Validation of the CFOSAT Scatterometer Data With Buoy Observations and Tests of Operational Application to Extreme Weather Forecasts in Taiwan Strait

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