Characterization of Tropical Cyclone Intensity Using the HY-2B Scatterometer Wind Data

Liu, Siqi; Lin, Wenming; Portabella, Marcos; Wang, Zhixiong

doi:10.3390/rs14041035

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…The ECMWF operational forecasts are used for the HSCAT wind retrieval algorithm, and the direction ambiguity removal is achieved by the 2D‐Var method. The wind retrieval of a Ku‐band scatterometer is more sensitive to rain effect due to the shorter wavelength compared to a C‐band scatterometer (Liu et al., 2022). HSCAT winds were not assimilated into the ECMWF OSEs for the 2nd reprocessed Aeolus FM‐B data set.…”

Section: Datamentioning

confidence: 99%

The Contribution of Aeolus Wind Observations to ECMWF Sea Surface Wind Forecasts

Zuo,

Stoffelen,

Rennie

et al. 2024

JGR Atmospheres

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Aeolus is the first satellite mission focusing on wind profile detection from near the surface to about 30 km in height on a global scale. This study evaluates the contribution of Aeolus winds to sea surface wind forecasts geographically by further analyzing the Observing System Experiments from the European Centre for Medium‐Range Weather Forecasts (ECMWF) with scatterometer winds from the meteorological operational satellites (assimilated into the model) and the Haiyang‐2B satellite (not assimilated into the model). The findings indicate that Aeolus has the ability to reduce the root‐mean‐square difference between scatterometer winds and background forecasts (short‐range) by about 0.05%–0.16% on average for climatic regions, except for the meridional wind component in the tropics. Also, Aeolus can generally reduce zonal biases of the background forecasts, while its beneficial impact on meridional biases mainly occurs in the Northern Hemisphere extratropics and tropics. For medium‐range forecast assessments, as the forecast step extends up to day 5, the positive impact of Aeolus on sea surface wind forecasts becomes more evident and is even greater than 3%, especially for extratropical ocean regions in the Southern Hemisphere. Furthermore, the impact of Aeolus shows seasonal variation, with a substantial positive impact from September 2019 to February 2020 and a negative impact mainly in March, April, and May 2020.

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Section: Datamentioning

confidence: 99%

The Contribution of Aeolus Wind Observations to ECMWF Sea Surface Wind Forecasts

Zuo,

Stoffelen,

Rennie

et al. 2024

JGR Atmospheres

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“…An enhancement in forecasting skill was achieved, indicating the effectiveness of the HY-2B data for NWP. HY-2B scatterometer data have also been applied to typhoon location and characterization intensity in some studies, showing that the radial extent of 17 m/s winds can well characterize the cyclone intensity and actual path [13,14].…”

Section: Introductionmentioning

confidence: 99%

Study of Quality Control Methods Utilizing IRMCD for HY-2B Data Assimilation Application

Hu,

Zhang,

et al. 2024

Atmosphere

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Quality control (QC) of HaiYang-2B (HY-2B) satellite data is mainly based on the observation process, which remains uncertain for data assimilation (DA). The data in operation have not been widely used in numerical weather prediction. To ensure HY-2B data meet the theoretical assumptions for DA applications, the iterated reweighted minimum covariance determinant (IRMCD) QC method was studied in HY-2B data based on the typhoon “Chanba”. The statistical results showed that most of the outliers were eliminated, and the observation increment distribution of the HY-2B data after QC (QCed) was closer to a Gaussian distribution than the raw data. The kurtosis and skewness of the QCed data were much closer to zero. The QCed track demonstrated the lowest accumulated error and the best intensity in typhoon assimilation, and the QCed intensity was closest to the observation during the nearshore enhancement, exhibiting the strongest intensity among the experiment. Further analysis revealed that the improvement was accompanied by a significant reduction in vertical wind shear during the nearshore enhancement of the typhoon. The QCed moisture flux divergence and vertical velocity in the upper layer increased significantly, which promoted the upward transport of momentum in the lower layers and contributed to the maintenance of the typhoon’s barotropic structure. Compared with the assimilation of raw data, the effective removal of outliers using the IRMCD algorithm significantly improved the simulation results for typhoons.

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“…They proposed a marine calibration based on the operating window to assess the consistency of CSCAT radar backscatter. In previous studies, the HY-2 series satellite Ku-band scatterometer was utilized by some researchers [39,40] for cross-calibration of backscatter measurements. Furthermore, scatterometer wind data from the HY-2B satellite were employed to characterize the intensity of tropical cyclones.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of HY-2C and CFOSAT Satellite Retrieval Offshore Wind Energy Using Weather Research and Forecasting (WRF) Simulations

Li,

Wan,

Duan

et al. 2023

Remote Sensing

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This study simulated the spatial distribution of wind speeds and wind energy density by using the WRF model, and we used the WRF-simulated results to evaluate the sea surface wind speeds retrieved from the HY-2C and CFOSAT satellite-borne microwave scatterometers over the Yellow Sea region. The main conclusions were as follows: (1) The combination of the MRF boundary layer parameterization scheme, the MM5 near-surface parameterization scheme, and the Global Data Assimilation System (GDAS) initial field demonstrated the best performance in simulating the 10 m wind speed in the Yellow Sea region, with a root-mean-square error (RMSE) of 1.57, bias of 1.24 m/s, and mean absolute percentage error (MAPE) of 17%. (2) The MAPE of the HY-2C inversion data was 9%, while the CFOSAT inversion data had an MAPE of 6%. The sea surface wind speeds derived from the HY-2C and CFOSAT satellite scatterometer inversions demonstrated high accuracy and applicability in this region. (3) The wind speed was found to increase with altitude over the Yellow Sea, with higher wind speeds observed in the southern region compared to the northern region. The wind power density increased with altitude, and the wind power density in the southern area of the Yellow Sea was higher than in the northern region. (4) The CFOSAT satellite inversion products were in good agreement with the WRF simulation results under low wind speed conditions. In contrast, the HY-2C satellite inversion products showed better agreement under moderate wind speed conditions. Under high wind speed conditions, both satellite inversion products exhibited minor deviations, but the HY-2C product had an overall overestimation, while the CFOSAT product remained within the range of −1 to 1 m/s. (6) The wind power density increased with the satellite-inverted 10 m wind speed. When the 10 m wind speed was less than 9 m/s, the wind power density exhibited a roughly cubic trend of increase. However, when the 10 m wind speed exceeded 9 m/s, the wind power density no longer increased with the rise in 10 m wind speed. These findings provide valuable insights into wind energy resources in the Yellow Sea region and demonstrate the effectiveness of satellite scatterometer inversions for wind speed estimation. The results have implications for renewable energy planning and management in the area.

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Characterization of Tropical Cyclone Intensity Using the HY-2B Scatterometer Wind Data

Cited by 8 publications

References 29 publications

The Contribution of Aeolus Wind Observations to ECMWF Sea Surface Wind Forecasts

The Contribution of Aeolus Wind Observations to ECMWF Sea Surface Wind Forecasts

Study of Quality Control Methods Utilizing IRMCD for HY-2B Data Assimilation Application

Evaluation of HY-2C and CFOSAT Satellite Retrieval Offshore Wind Energy Using Weather Research and Forecasting (WRF) Simulations

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