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Journal articles on the topic 'Cfosat'

Author: Grafiati

Published: 20 April 2024

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1

Xu, Jingwei, Huanping Wu, Ying Xu, et al. "Validation of Nadir SWH and Its Variance Characteristics from CFOSAT in China’s Offshore Waters." Remote Sensing 15, no. 4 (2023): 1005. http://dx.doi.org/10.3390/rs15041005.

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The offshore waters of China are a typical monsoon−affected area where the significant wave height (SWH) is strongly influenced by the different seasonal mean flow in winter and summer. However, limited in situ validations of the SWH have been performed on the China–France Oceanography Satellite (CFOSAT) in these waters. This study focused on validating CFOSAT nadir SWH data with SWH data from in situ buoy observations for China’s offshore waters and the Haiyang−2B (HY−2B) satellite, from July 2019 to December 2021. The validation against the buoy data showed that the relative absolute error h

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2

Li, Songlin, Huaming Yu, Kejian Wu, Xunqiang Yin, Shuyan Lang, and Jiacheng Ye. "Validation of the Ocean Wave Spectrum from the Remote Sensing Data of the Chinese–French Oceanography Satellite." Remote Sensing 15, no. 16 (2023): 3918. http://dx.doi.org/10.3390/rs15163918.

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Since the launch of CFOSAT on 29 October 2018, more than three years of observational data of ocean wave spectra with a frequency range of 0.02–0.26 Hz and a horizontal resolution of 70–90 km have been obtained. This study compares wave spectra retrieved from 6°, 8°, and 10° incidence angle beams and their combination provided by CFOSAT with corresponding data from 98 buoys from the National Data Buoy Center (NDBC) in order to validate the remote sensing wave spectral accuracy from 1 January 2020 to 31 December 2022. The correlation coefficient of frequency spectra (Rs) between CFOSAT and buoy

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3

Ye, Haijun, Junmin Li, Bo Li, et al. "Evaluation of CFOSAT Scatterometer Wind Data in Global Oceans." Remote Sensing 13, no. 10 (2021): 1926. http://dx.doi.org/10.3390/rs13101926.

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The China-France Oceanography SATellite (CFOSAT), launched on 29 October 2018, is a joint mission developed by China and France. To evaluate the CFOSAT wind product, L2B swath data with a spatial resolution of 25 × 25 km were compared with in situ measurements between December 2018 and December 2020. The in situ measurements were collected from 217 buoys. All buoy winds were adjusted to 10 m height using a simple logarithmic correction method. The temporal and spatial separations between the CFOSAT and in situ measurements were restricted to less than 30 min and 0.25°. The results indicate tha

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4

DONG Xiaolong, ZHU Di, LIN Wenming, et al. "Orbit Performances Validation for CFOSAT Scatterometer." Chinese Journal of Space Science 40, no. 3 (2020): 425. http://dx.doi.org/10.11728/cjss2020.03.425.

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5

Li, Zhen, Anton Verhoef, and Ad Stoffelen. "Bayesian Sea Ice Detection Algorithm for CFOSAT." Remote Sensing 14, no. 15 (2022): 3569. http://dx.doi.org/10.3390/rs14153569.

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This paper describes the adaptation of the Bayesian sea ice detection algorithm for the rotating fan-beam scatterometer CSCAT onboard the China–France Oceanography Satellite (CFOSAT). The algorithm was originally developed and applied for fixed fan-beam and rotating pencil-beam scatterometers. It is based on the probability of the wind and ice backscatter distances from the measurements to their corresponding geophysical model functions (GMFs). The new rotating Ku-band fan-beam design introduces very diverse geometry distributions across the swath, which leads to three main adaptations of the

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6

Zhao, Xiaokang, Wenming Lin, Marcos Portabella, Zhixiong Wang, and Yijun He. "Effects of rain on CFOSAT scatterometer measurements." Remote Sensing of Environment 274 (June 2022): 113015. http://dx.doi.org/10.1016/j.rse.2022.113015.

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7

Li, Bo, Junmin Li, Shilin Tang, Ping Shi, Wuyang Chen, and Junliang Liu. "Evaluation of CFOSAT Wave Height Data with In Situ Observations in the South China Sea." Remote Sensing 15, no. 4 (2023): 898. http://dx.doi.org/10.3390/rs15040898.

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The wave spectrometer operated by the China–France Oceanography Satellite (CFOSAT) can provide global ocean wave observation data. Although a lot of work on calibration and verification has been carried out in the open oceans dominated by swells, the quality of the data in the relatively enclosed sea area with complex terrain still lacks sufficient examination. The objective of this study is to assess the performance of the significant wave height data of the CFOSAT in the South China Sea (SCS), a unique sea area characterized by semi-enclosed basin and multi-reef terrain, and to recognize the

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8

Li, Zheng, Bingcheng Wan, Zexia Duan, Yuanhong He, Yingxin Yu, and Huansang Chen. "Evaluation of HY-2C and CFOSAT Satellite Retrieval Offshore Wind Energy Using Weather Research and Forecasting (WRF) Simulations." Remote Sensing 15, no. 17 (2023): 4172. http://dx.doi.org/10.3390/rs15174172.

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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

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9

Li, Bo, Junmin Li, Junliang Liu, et al. "Calibration Experiments of CFOSAT Wavelength in the Southern South China Sea by Artificial Neural Networks." Remote Sensing 14, no. 3 (2022): 773. http://dx.doi.org/10.3390/rs14030773.

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The wave data measured by CFOSAT (China France Oceanography Satellite) have been validated mainly based on numerical model outputs and altimetry products on a global scale. It is still necessary to further calibrate the data for specific regions, e.g., the southern South China Sea. This study analyses the practicability of calibrating the dominant wavelength by using artificial neural networks and mean impact value analysis based on two sets of buoy data with a 2-year observation period and contemporaneous ERA5 reanalysis data. The artificial neural network modeling experiments are repeated 10

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10

Shao, Weizeng, Tao Jiang, Yu Zhang, Jian Shi, and Weili Wang. "Cyclonic Wave Simulations Based on WAVEWATCH-III Using a Sea Surface Drag Coefficient Derived from CFOSAT SWIM Data." Atmosphere 12, no. 12 (2021): 1610. http://dx.doi.org/10.3390/atmos12121610.

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It is well known that numerical models are powerful methods for wave simulation of typhoons, where the sea surface drag coefficient is sensitive to strong winds. With the development of remote sensing techniques, typhoon data (i.e., wind and waves) have been captured by optical and microwave satellites such as the Chinese-French Oceanography SATellite (CFOSAT). In particular, wind and wave spectra data can be simultaneously measured by the Surface Wave Investigation and Monitoring (SWIM) onboard CFOSAT. In this study, existing parameterizations for the drag coefficient are implemented for typh

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11

Mou, Xiaoheng, Wenming Lin, and Yijun He. "Towards a Consistent Wind Data Record for the CFOSAT Scatterometer." Remote Sensing 15, no. 8 (2023): 2081. http://dx.doi.org/10.3390/rs15082081.

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Since launch, the Ku-band rotating fan-beam scatterometer onboard the China–France Oceanography Satellite (CFOSAT) has provided valuable sea surface wind measurements for more than four years. The performance of CFOSAT scatterometer (CSCAT)-derived wind vectors is generally good in terms of root-mean-square error, while the absolute calibration error remains an issue in the current CSCAT product. In this paper, the temporal variation in CSCAT winds is overviewed by analyzing the collocated CSCAT and numerical weather prediction (NWP) model winds. Then, the reasons for the inconsistency of CSCA

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12

Jiang, Haoyu, Yuhao Song, Alexey Mironov, Zheng Yang, Ying Xu, and Jianqiang Liu. "Accurate mean wave period from SWIM instrument on-board CFOSAT." Remote Sensing of Environment 280 (October 2022): 113149. http://dx.doi.org/10.1016/j.rse.2022.113149.

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13

Zhang, Kuo, Xiaolong Dong, Di Zhu, Risheng Yun, Binghua Wang, and Miaomiao Yu. "An Improved Method of Noise Subtraction for the CFOSAT Scatterometer." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (2021): 7506–15. http://dx.doi.org/10.1109/jstars.2021.3093559.

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14

Liu, Jianqiang, Wenming Lin, Xiaolong Dong, et al. "First Results From the Rotating Fan Beam Scatterometer Onboard CFOSAT." IEEE Transactions on Geoscience and Remote Sensing 58, no. 12 (2020): 8793–806. http://dx.doi.org/10.1109/tgrs.2020.2990708.

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15

ZHAO, Xiaokang, Wenming LIN, Zhixiong WANG, and Yijun HE. "Effects of Sea Surface Temperature on the CFOSAT Scatterometer Measurements." Chinese Journal of Space Science 42 (2023): 1. http://dx.doi.org/10.11728/cjss2023.01.220216017.

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16

Liang, Guozhou, Jungang Yang, and Jichao Wang. "Accuracy Evaluation of CFOSAT SWIM L2 Products Based on NDBC Buoy and Jason-3 Altimeter Data." Remote Sensing 13, no. 5 (2021): 887. http://dx.doi.org/10.3390/rs13050887.

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Chinese-French Oceanography Satellite (CFOSAT), the first satellite which can observe global ocean wave and wind synchronously, was successfully launched On 29 October 2018. The CFOSAT carries SWIM that can observe ocean wave on a global scale. Based on National Data Buoy Center (NDBC) buoys and Jason-3 altimeter data, this study evaluated the accuracy of L2 level products of CFOSAT SWIM from August 2019 to September 2020. The results show that the accuracy of the nadir Significant Wave Height (SWH) data of the SWIM wave spectrometer is good. Compared with the data of the NDBC buoys and Jason-

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17

Zhai, Xiaochun, Zhixiong Wang, Zhaojun Zheng, et al. "Sea Ice Monitoring with CFOSAT Scatterometer Measurements Using Random Forest Classifier." Remote Sensing 13, no. 22 (2021): 4686. http://dx.doi.org/10.3390/rs13224686.

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The Ku-band scatterometer called CSCAT onboard the Chinese–French Oceanography Satellite (CFOSAT) is the first spaceborne rotating fan-beam scatterometer (RFSCAT). This paper performs sea ice monitoring with the CSCAT backscatter measurements in polar areas. The CSCAT measurements have the characteristics of diverse incidence and azimuth angles and separation between open water and sea ice. Hence, five microwave feature parameters, which show different sensitivity to ice or water, are defined and derived from the CSCAT measurements firstly. Then the random forest classifier is selected for sea

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18

Hauser, Danièle. "Observations du vent de surface et des vagues à partir de CFOSAT." La Météorologie, no. 104 (2019): 2. http://dx.doi.org/10.4267/2042/69775.

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19

Lin, Wenming, Xiaolong Dong, Marcos Portabella, et al. "A Perspective on the Performance of the CFOSAT Rotating Fan-Beam Scatterometer." IEEE Transactions on Geoscience and Remote Sensing 57, no. 2 (2019): 627–39. http://dx.doi.org/10.1109/tgrs.2018.2858852.

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20

Yurovskaya, Maria, Vladimir Kudryavtsev, Alexey Mironov, Alexis Mouche, Fabrice Collard, and Bertrand Chapron. "Surface Wave Developments under Tropical Cyclone Goni (2020): Multi-Satellite Observations and Parametric Model Comparisons." Remote Sensing 14, no. 9 (2022): 2032. http://dx.doi.org/10.3390/rs14092032.

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Over the Philippine Sea, the tropical cyclone (TC) Goni reaches category 5 on 29–31 October 2020. Multi-satellite observations, including CFOSAT SWIM/SCAT and Sentinel-1 SAR data, are jointly analyzed to assess the performances of a parametric model. Recently developed to provide a fast estimation of surface wave developments under rapidly evolving TCs, this full 2D parametric model (KYCM) and its simplified self-similar solutions (TC-wave geophysical model function (TCW GMF)) are thoroughly compared with satellite observations. TCW GMF provides immediate first-guess estimates, at any location

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21

WANG, Yihui, Xingou XU, and Ying XU. "Comparisons on One-dimensional Ocean Wave Spectrum Models Based on SWIM/CFOSAT Observations." Chinese Journal of Space Science 43, no. 6 (2023): 1. http://dx.doi.org/10.11728/cjss2023.06.2023-0068.

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22

Quan, Meixuan, Jie Zhang, and Rui Zhang. "A Novel Rain Identification and Rain Intensity Classification Method for the CFOSAT Scatterometer." Remote Sensing 16, no. 5 (2024): 887. http://dx.doi.org/10.3390/rs16050887.

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The China–France oceanography satellite scatterometer (CSCAT) is a rotating fan-beam scanning observation scatterometer operating in the Ku-band, and its product quality is affected by rain contamination. The multiple azimuthal NRCS measurements provided by CSCAT L2A, the retrieved wind speed and wind direction provided by CSCAT L2B, as well as the rain data provided by GPM, are used to construct a new rain identification and rain intensity classification model for CSCAT. The EXtreme Gradient Boosting (XGBoost) model, optimized by the Dung Beetle Optimizer (DBO) algorithm, is developed and eva

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23

Liu, Meijie, Ran Yan, Jie Zhang, et al. "Arctic Sea Ice Classification Based on CFOSAT SWIM Data at Multiple Small Incidence Angles." Remote Sensing 14, no. 1 (2021): 91. http://dx.doi.org/10.3390/rs14010091.

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Sea ice type is the key parameter of Arctic sea ice monitoring. Microwave remote sensors with medium incidence and normal incidence modes are the primary detection methods for sea ice types. The Surface Wave Investigation and Monitoring instrument (SWIM) on the China-France Oceanography Satellite (CFOSAT) is a new type of sensor with a small incidence angle detection mode that is different from traditional remote sensors. The method of sea ice detection using SWIM data is also under development. The research reported here concerns ice classification using SWIM data in the Arctic from October 2

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24

Sun, Meng, Jianting Du, Yongzeng Yang, and Xunqiang Yin. "Evaluation of Assimilation in the MASNUM Wave Model Based on Jason-3 and CFOSAT." Remote Sensing 13, no. 19 (2021): 3833. http://dx.doi.org/10.3390/rs13193833.

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Accurate numerical simulation of ocean waves is one of the most important measures to ensure shipping safety, offshore engineering construction, etc. The use of wave observations from satellite is an efficient way to correct model results. The goal of this paper is to assess the performance of assimilation in the MASNUM wave model for the Indian Ocean. The assimilation technique is based on Ensemble Adjusted Kalman Filter, with a variable ensemble constructed by the dynamic sampling method rather than ensemble members of wave model. Observations of significant wave height from satellites Jason

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25

Zhang, Kuo, Xiaolong Dong, Di Zhu, and Risheng Yun. "Estimation and Correction of Geolocation Errors of the CFOSAT Scatterometer Using Coastline Backscatter Coefficients." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (2021): 53–61. http://dx.doi.org/10.1109/jstars.2020.3035238.

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26

Zhu, Jintai, Xiaolong Dong, Wenming Lin, and Di Zhu. "A Preliminary Study of the Calibration for the Rotating Fan-Beam Scatterometer on CFOSAT." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8, no. 2 (2015): 460–70. http://dx.doi.org/10.1109/jstars.2014.2333241.

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27

Xu, Ying, Jianqiang Liu, Lingling Xie, et al. "China-France Oceanography Satellite (CFOSAT) simultaneously observes the typhoon-induced wind and wave fields." Acta Oceanologica Sinica 38, no. 11 (2019): 158–61. http://dx.doi.org/10.1007/s13131-019-1506-3.

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28

DONG, Ying, and Wenming LIN. "Analysis of Sea Surface Backscatter Coefficient Errors and Its Effects for the CFOSAT Scatterometer." Chinese Journal of Space Science 44, no. 2 (2024): 1. http://dx.doi.org/10.11728/cjss2024.02.2023-0144.

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29

Zhai, Xiaochun, Rui Xu, Zhixiong Wang, et al. "Classification of Arctic Sea Ice Type in CFOSAT Scatterometer Measurements Using a Random Forest Classifier." Remote Sensing 15, no. 5 (2023): 1310. http://dx.doi.org/10.3390/rs15051310.

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The Ku-band scatterometer called CSCAT onboard the Chinese–French Oceanography Satellite (CFOSAT) is the first spaceborne rotating fan-beam scatterometer (RFSCAT). A new algorithm for classification of Arctic sea ice types on CSCAT measurement data using a random forest classifier is presented. The random forest classifier is trained on the National Snow and Ice Data Center (NSIDC) weekly sea ice age and sea ice concentration product. Five feature parameters, including the mean value of horizontal and vertical polarization backscatter coefficient, the standard deviation of horizontal and verti

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30

SHIMURA, Tomoya, Yukino NISHIMURA, Nobuhito MORI, et al. "MULTI PERSPECTIVE OBSERVATION OF TYPHOON WAVES IN 2021 - COMPARISON AMONG GPS WAVE BUOYS, CFOSAT, AND MODEL -." Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering) 78, no. 2 (2022): I_397—I_402. http://dx.doi.org/10.2208/kaigan.78.2_i_397.

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31

Xu, Ming, and Li Huang. "An analytic algorithm for global coverage of the revisiting orbit and its application to the CFOSAT satellite." Astrophysics and Space Science 352, no. 2 (2014): 497–502. http://dx.doi.org/10.1007/s10509-014-1939-2.

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32

Karaev, V. Yu, M. A. Panfilova, M. S. Ryabkova, Yu A. Titchenko, E. M. Meshkov, and X. Li. "Retrieval of the two-dimensional slope field by the SWIM spectrometer of the CFOSAT satellite: discussion of the algorithm." Russian Journal of Earth Sciences 21, no. 6 (2021): 1–9. http://dx.doi.org/10.2205/2021es000784.

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33

HUANG, Bingqing, Xiaoming LI, and Qiongqiong CAI. "Retrieval of ocean wave spectra from Sentinel-1 SAR data and comparison with the CFOSAT/SWIM data in the Arctic ocean." National Remote Sensing Bulletin 27, no. 4 (2023): 881–90. http://dx.doi.org/10.11834/jrs.20211210.

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34

Wang, Jin, Brandon J. Bethel, Changming Dong, Chunhui Li, and Yuhan Cao. "Numerical Simulation and Observational Data Analysis of Mesoscale Eddy Effects on Surface Waves in the South China Sea." Remote Sensing 14, no. 6 (2022): 1463. http://dx.doi.org/10.3390/rs14061463.

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Surface current velocities of mesoscale eddies have a unique annular structure, which can inevitably influence surface wave properties and energy distribution. Sensitivity experiments of ideal mesoscale eddies on waves were carried out by the Simulating WAves Nearshore (SWAN) wave model to investigate these influences. In addition, China–France Oceanography SATellite Surface Wave Investigation and Monitoring (CFOSAT-SWIM) observational data of a large warm-cored eddy in the South China Sea (SCS) during the period of October–November 2019 were used to validate the influence of mesoscale eddies

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35

Gibert, Ferran, Jacqueline Boutin, Wolfgang Dierking, et al. "Results of the Dragon 4 Project on New Ocean Remote Sensing Data for Operational Applications." Remote Sensing 13, no. 14 (2021): 2847. http://dx.doi.org/10.3390/rs13142847.

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This paper provides an overview of the Dragon 4 project dealing with operational monitoring of sea ice and sea surface salinity (SSS) and new product developments for altimetry data. To improve sea ice thickness retrieval, a new method was developed to match the Cryosat-2 radar waveform. Additionally, an automated sea ice drift detection scheme was developed and tested on Sentinel-1 data, and the sea ice drifty capability of Gaofen-4 geostationary optical data was evaluated. A second topic included implementation and validation of a prototype of a Fully-Focussed SAR processor adapted for Senti

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36

Xue, Sihan, Lingsheng Meng, Xupu Geng, Haiyang Sun, Deanna Edwing, and Xiao-Hai Yan. "Retrieving Ocean Surface Winds and Waves from Augmented Dual-Polarization Sentinel-1 SAR Data Using Deep Convolutional Residual Networks." Atmosphere 14, no. 8 (2023): 1272. http://dx.doi.org/10.3390/atmos14081272.

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Sea surface winds and waves are very important phenomena that exist in the air–sea boundary layer. With the advent of climate change, cascade effects are bringing more attention to these phenomena as warmer sea surface temperatures bring about stronger winds, thereby altering global wave conditions. Synthetic aperture radar (SAR) is a powerful sensor for high-resolution surface wind and wave observations and has accumulated large quantities of data. Furthermore, deep learning methods have been increasingly utilized in geoscience, especially the inversion of ocean information from SAR imagery.

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37

Xu, Changjing, Zhixiong Wang, Xiaochun Zhai, Wenming Lin, and Yijun He. "SVM-Based Sea Ice Extent Retrieval Using Multisource Scatterometer Measurements." Remote Sensing 15, no. 6 (2023): 1630. http://dx.doi.org/10.3390/rs15061630.

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This study aims to explore the joint usage of multisource scatterometer measurements in polar sea water and ice discrimination. All radar backscatter measurements from current operating satellite scatterometers are considered, including the C-band ASCAT scatterometer on board the MetOp series satellites, the Ku-band scatterometer on board the HY-2B satellite (HSCAT), and the Ku-band scatterometer on board the CFOSAT satellite (CSCAT). By performing seven experiments that use the same support vector machine (SVM) classifier method but with different input data, we find that the SVM model with a

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38

McInnes, Kathleen L., John L. McBride, and Lance M. Leslie. "Cold Fronts over Southeastern Australia: Their Representation in an Operational Numerical Weather Prediction Model." Weather and Forecasting 9, no. 3 (1994): 384–409. http://dx.doi.org/10.1175/1520-0434(1994)009<0384:cfosat>2.0.co;2.

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39

Xu, Xingou, Xiaolong Dong, and Yu Xie. "On-Board Wind Scatterometry." Remote Sensing 12, no. 7 (2020): 1216. http://dx.doi.org/10.3390/rs12071216.

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Real-time (RT) ocean surface wind can make key improvements to disaster alarmingand safety of maritime navigation to avoid loss in property and human lives. Wind scatterometry is a well-acquainted way of obtaining good quality ocean surface winds, and it has been in application for decades. Existing wind-obtaining chains employ ground stations for receiving observations and can, at best, provide products in around 30 minutes for limited regions. In recent years, a satellite information-obtaining and transmission network is the new trend of Earth observation. In this research, on-board wind ret

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40

Li, Zhen, Ad Stoffelen, and Anton Verhoef. "A generalized simulation capability for rotating- beam scatterometers." Atmospheric Measurement Techniques 12, no. 7 (2019): 3573–94. http://dx.doi.org/10.5194/amt-12-3573-2019.

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Abstract. Rotating-beam wind scatterometers exist in two types: rotating fan-beam and rotating pencil-beam. In our study, a generic simulation frame is established and verified to assess the wind retrieval skill of the three different scatterometers: SCAT on CFOSAT (China France Oceanography SATellite), WindRad (Chinese Wind Radar) on FY-3E, and SeaWinds on QuikSCAT. Besides the comparison of the so-called first rank solution retrieval skill of the input wind field, other figures of merit (FoMs) are applied to statistically characterize the associated wind retrieval performance from three aspe

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41

Zhang, Yunfeng, Yiming Wang, Yonggang Ji, and Ming Li. "Unambiguous Wind Direction Estimation Method for Shipborne HFSWR Based on Wind Direction Interval Limitation." Remote Sensing 15, no. 11 (2023): 2952. http://dx.doi.org/10.3390/rs15112952.

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Due to its maneuverability and agility, the shipborne high-frequency surface wave radar (HFSWR) provides a new way of monitoring large-area marine dynamics and environment information. However, wind direction ambiguity is problematic when using monostatic shipborne HFSWR for wind direction inversion. In this article, an unambiguous wind direction measurement method based on wind direction interval limitation is proposed. The two first-order spectral wind direction estimation methods are first presented using the relationship between the normalized amplitude differences or ratios of the broaden

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42

Yao, Ru, Weizeng Shao, Youguang Zhang, Meng Wei, Song Hu, and Juncheng Zuo. "Feasibility of Wave Simulation in Typhoon Using WAVEWATCH-III Forced by Remote-Sensed Wind." Journal of Marine Science and Engineering 11, no. 10 (2023): 2010. http://dx.doi.org/10.3390/jmse11102010.

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The purpose of our work was to assess the feasibility of hindcasting waves using WAVEWATCH-III (WW3) in a typhoon by assembling winds from multiple remote-sensed products. During the typhoon season in 2021–2022, the swath wind products in the Western Pacific Ocean were collected from scatterometers and radiometers. Cyclonic winds with a spatial resolution of 0.125° at intervals of 6 h were obtained by assembling the remote-sensed winds from those satellites. The maximum wind speeds, Vmax, were verified using the reanalysis data from the National Hurricane Center (NHC), yielding a root-mean-squ

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43

Chen, Hua-Pin, I.-Chyn Wey, Liang-Yen Chen, Cheng-Yueh Wu, and San-Fu Wang. "Design and Verification of a New Universal Active Filter Based on the Current Feedback Operational Amplifier and Commercial AD844 Integrated Circuit." Sensors 23, no. 19 (2023): 8258. http://dx.doi.org/10.3390/s23198258.

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This paper presents a triple-input and four-output type voltage-mode universal active filter based on three current-feedback operational amplifiers (CFOAs). The filter employs three CFOAs, two grounded capacitors, and six resistors. The filter structure has three high-input and three low-output impedances that simultaneously provide band-reject, high-pass, low-pass, and band-pass filtering functions with single-input and four-output type and also implements an all-pass filtering function by connecting three input signals to one input without the use of voltage inverters or switches. The same c

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44

Gupta, S. S., D. R. Bhaskar, and R. Senani. "Synthesis of New Single CFOA-Based VCOs Incorporating the Voltage Summing Property of Analog Multipliers." ISRN Electronics 2012 (September 18, 2012): 1–8. http://dx.doi.org/10.5402/2012/463680.

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Recently, current feedback operational amplifier (CFOA) and analog multiplier-(AM-) based-voltage controlled oscillators (VCOs) have been published in the literature which require 2 CFOAs and 2 AMs for linear tuning law between control voltage and frequency of oscillation. In this paper, a family of eight new voltage-controlled oscillators (VCOs), with linear tuning laws, employing only a single CFOA in conjunction with two analog multipliers (AMs), has been derived through a systematic state-variable methodology. This has been made possible by exploiting the voltage summing property of the mu

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Abuelma’atti, Muhammad Taher, and Husain Abdullah Al-Zaher. "New Grounded-Capacitor Sinusoidal Oscillators Using the Current-Feedback-Amplifier Pole." Active and Passive Electronic Components 21, no. 1 (1998): 23–32. http://dx.doi.org/10.1155/1998/37035.

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New current-feedback-operational amplifier (CFOA)-pole-based sinusoidal oscillator circuits are presented. Each circuit uses two CFOAs, two (or three) grounded capacitors and/or resistors. Experimental results are included.

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Han, Lei, Qiyan Ji, Xiaoyan Jia, Yu Liu, Guoqing Han, and Xiayan Lin. "Significant Wave Height Prediction in the South China Sea Based on the ConvLSTM Algorithm." Journal of Marine Science and Engineering 10, no. 11 (2022): 1683. http://dx.doi.org/10.3390/jmse10111683.

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Deep learning methods have excellent prospects for application in wave forecasting research. This study employed the convolutional LSTM (ConvLSTM) algorithm to predict the South China Sea (SCS) significant wave height (SWH). Three prediction models were established to investigate the influences of setting different parameters and using multiple training data on the forecasting effects. Compared with the SWH data from the China–France Ocean Satellite (CFOSAT), the SWH of WAVEWATCH III (WWIII) from the pacific islands ocean observing system are accurate enough to be used as training data for the

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KILIÇ, RECAI. "EXPERIMENTAL STUDY OF CFOA-BASED INDUCTORLESS CHUA'S CIRCUIT." International Journal of Bifurcation and Chaos 14, no. 04 (2004): 1369–74. http://dx.doi.org/10.1142/s021812740400996x.

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The current feedback op amps (CFOAs), with some significant advantages over the conventional op amps, have been used instead of voltage op amps (VOAs) in new implementations of Chua's circuit. In our previous study, after providing a comparative investigation of CFOA-based realizations of Chua's circuit in the literature, we have also presented an alternative inductorless CFOA-based realization of Chua's circuit, and the circuit's chaotic behavior by Pspice simulations. In this paper, we investigate CFOA-based Chua's circuit by constructing an experimental setup, and testing the performance of

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GUPTA, S. S., D. R. BHASKAR, R. SENANI, and A. K. SINGH. "SYNTHESIS OF LINEAR VCOs: THE STATE-VARIABLE APPROACH." Journal of Circuits, Systems and Computers 20, no. 04 (2011): 587–606. http://dx.doi.org/10.1142/s0218126611007487.

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The paper presents a systematic approach of synthesizing sinusoidal linear VCOs (i.e., an oscillator providing linear tuning law of the type f0 ∝ VC between the oscillation frequency f0 and an external control voltage VC). In view of recent interest on current feedback operational amplifier (CFOA)-based oscillators, the proposed methodology has been demonstrated by deriving a class of linear VCOs employing CFOAs and analog multipliers (AM). The workability of the new VCOs has been established by experimental results of the circuits implemented with commercially available AD844 type CFOAs and A

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SAMIOTIS, P., and C. PSYCHALINOS. "DESIGN OF FILTERS WITH ONLY GROUNDED PASSIVE ELEMENTS USING DIFFERENTIAL VOLTAGE CURRENT FEEDBACK OPERATIONAL AMPLIFIERS." Journal of Circuits, Systems and Computers 19, no. 03 (2010): 573–80. http://dx.doi.org/10.1142/s021812661000630x.

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Differential Voltage Current Feedback Operational Amplifiers (DVCFOAs) and conventional CFOAs are employed as active elements for designing leapfrog filters in this work. DVCFOAs are realized by enhancing the topology of the conventional CFOA in order to have available a second high-impedance input terminal and, simultaneously, establishing a voltage at low-impedance input terminal equal to the difference between the voltages at high-impedance input terminals. A third-order leapfrog filter is realized by employing CFOAs or DVCFOAs, and the most important performance factors of the correspondin

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Hao, Mengyu, Weizeng Shao, Shaohua Shi, Xing Liu, Yuyi Hu, and Juncheng Zuo. "Validation of Surface Waves Investigation and Monitoring Data against Simulation by Simulating Waves Nearshore and Wave Retrieval from Gaofen-3 Synthetic Aperture Radar Image." Remote Sensing 15, no. 18 (2023): 4402. http://dx.doi.org/10.3390/rs15184402.

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The Chinese-French Oceanography SATellite (CFOSAT) jointly developed by the Chinese National Space Agency (CNSA) and the Centre National d’Etudes Spatiales (CNES) of France carries a wave spectrometer (Surface Waves Investigation and Monitoring, SWIM). SWIM has one nadir and five off-nadir beams to measure ocean surface waves. These near-nadir beams range from 0° to 10° at an interval of 2°. In this work, we investigated the performance of wave parameters derived from wave spectra measured by SWIM at off-nadir beams during the period 2020 to December 2022, e.g., incidence angles of 6°, 8° and

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