Intercomparison of Oceansat-2 and ASCAT Winds with In Situ Buoy Observations and Short-Term Numerical Forecasts

Rani, S. Indira; Gupta, M. Das; Sharma, Priti; Prasad, V. S.

doi:10.1080/07055900.2013.869191

Cited by 16 publications

(8 citation statements)

References 25 publications

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“…Bentamy et al (2000) intercompared ERS-2 and QuikSCAT winds, revealing that QuikSCAT wind vector estimates compared well with ERS-2 wind products. Rani et al (2014) compared Oceansat-2 and ASCAT winds with buoy observations, showing that ASCAT winds were slightly more accurate than those of OSCAT.…”

Section: Introductionmentioning

confidence: 95%

“…There are two observation swaths, both about 500-km wide. Current ASCAT wind products are provided at two spatial resolutions over the global oceans, 12.5 km and 25 km (Bentamy et al, 2008;Rani et al, 2014). More information on the ASCAT instrument is available from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) website (http://www.eumetsat.int).…”

Section: Introductionmentioning

confidence: 99%

“…The sensor covers a continuous swath of 1 400 km for the inner beam and 1 840 km for the outer beam. The aim is to provide global ocean coverage and wind vector retrieval with a revisit time of two days (Rani et al, 2014). Currently, two types of wind products with different spatial resolutions are produced, 25 km and 50 km.…”

Section: Introductionmentioning

confidence: 99%

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Validation and intercomparison of HY-2A/MetOp-A/Oceansat-2 scatterometer wind products

Chen

2015

Chin. J. Ocean. Limnol.

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Sea surface winds are of great signifi cance in scientifi c research. In the last few years, three series of scatterometers were launched to measure these winds, including the Advanced Scatterometer (ASCAT) aboard Meteorological Operational Satellite A (MetOp-A) and MetOp-B, Oceansat-2 Scatterometer (OSCAT), and HY-2A Scatterometer (HY-2A SCAT). Based on buoy wind data, validation and intercomparison of these scatterometers were performed. Scatterometer-derived wind and buoy wind data were collected only if the spatial difference was less than 0.1 degree and temporal difference less than 5 min. After discarding wind direction data outside fi ve times the standard deviation, ASCAT wind products showed high accuracy in both wind speed and direction, with root-mean-square error (RMSE) 0.86 m/s and 17.97 degrees, respectively. HY-2A SCAT nearly meets the mission requirement, with RMSE for wind speed 1.23 m/s and 22.85 degrees for wind direction. OSCAT had poor performance when compared with the others. RMSE for wind speed was 1.54 m/s and 39.86 degrees for wind direction, which greatly exceeds the mission requirement of 20 degrees. In addition, the RMSE for wind direction shows a high-low pattern on buoy wind speed. However, a wind speed range from 14 to 15 m/s was found to be abnormal, and the reason remains unclear. There was no systematic dependency of both wind speed and direction residuals on buoy wind speed and cross-track location of the wind vector cells across the entire range. No seasonal variation was found for any scatterometer.

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

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Validation and intercomparison of HY-2A/MetOp-A/Oceansat-2 scatterometer wind products

Chen

2015

Chin. J. Ocean. Limnol.

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“…At National Centre for Medium Range Weather Forecast (NCMRWF), the OSCAT and ASCAT surface wind vectors are validated against the in-situ buoy observations and as well as against the NWP short range forecasts (Rani et al (2014), Rani and Das Gupta (2013)). These studies have shown that ASCAT wind quality is good and comparable to other scatterometer winds.…”

Section: Validation Of Scatterometer Winds At Ncmrwfmentioning

confidence: 99%

Assimilation of ASCAT winds using 4DVAR: an impact study

et al. 2016

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Sea surface wind vectors from Advanced Scatterometer (ASCAT) onboard MetOP satellites are pivotal inputs to NWP models, especially during cyclone period. NCMRWF regularly receives these winds from NOAA through ftp and routinely assimilates in the operational global models. The impact of ASCAT winds in the NCMRWF Unified Model (NCUM) assimilation and forecast system during the cyclone Chapala period from 28 October 2015 to 4 November 2015 is studied. Before assimilating, these winds are validated against in-situ observations from buoy platforms over the North Indian Ocean (NIO). It is found that the errors in the ASCAT winds are well within the limit of mission goal (<2m/s). After the successful validation, numerical experiments are designed in such a way that 10-day forecasts are generated from two different initial conditions. In the control run (CTL), ASCAT winds are removed from the Observation Processing System (OPS) and Variational Assimilation (VAR) systems of NCUM, while in the experiment run (AST) ASCAT winds are included in both OPS and VAR. Forecasts from both the runs are analysed to see the movement and intensification of the cyclonic system in due course. The results show that the experiments with ASCAT winds improved the track and intensity of the NIO cyclonic system.

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“…Although the model can obtain the results of ocean wave parameters of long-term sequences, it is affected by multiple conditions, such as initial condition settings, observation data assimilation and water depth. Field observations mainly consist of sea state measurements from buoys [2]. Buoys are recognized as more accurate means in the field observation of ocean waves; however, buoy locations are sparse, and the data records at each position may be discontinuous [3].…”

Section: Introductionmentioning

confidence: 99%

Research on a Method for Simulating Multiview Ocean Wave Synchronization Data by Networked SAR Satellites

Wan

Zhang

Dai

et al. 2019

JMSE

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It is expected that the problem of the azimuth cutoff wavelength in single-satellite synthetic aperture radar (SAR) observations can be solved by means of the cooperative observation of networked SAR satellites. Multiview SAR wave synchronization data are required in the process. However, most of the current orbiting satellites are geosynchronous orbit satellites; the simultaneous observation by multiple SARs in the same sea area cannot be achieved, and multiview synchronization data cannot be obtained. Therefore, this paper studies the simulation of the multiview SAR wave synchronization data. Ocean wave spectra were simulated by using the Pierson Moskowitz (PM) spectrum. The Monte Carlo method was used to simulate two-dimensional (2D) ocean surfaces at different wind speeds. The two-scale electromagnetic scattering model was used to calculate the ocean surface backscattering coefficient, and the time-domain echo algorithm was used to generate echo signals. The echo signals were processed by the Range-Doppler (RD) imaging algorithm to obtain ocean SAR data. Based on the obtained single-SAR wave data, networked satellites consisting of three SARs were simulated, and the SAR wave data were synchronized. The results show that when SARs are used to observe the same sea area from different observation directions, the clarity of the wave fringes in the SAR images are different. For different azimuth angles, the degrees of azimuth cutoff are different. These results reflect the influences of different degrees of azimuth cutoff on SAR images. The simulated wave synchronization data can be used as the basic data source for subsequent azimuth cutoff wavelength compensation.

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Intercomparison of Oceansat-2 and ASCAT Winds with In Situ Buoy Observations and Short-Term Numerical Forecasts

Cited by 16 publications

References 25 publications

Validation and intercomparison of HY-2A/MetOp-A/Oceansat-2 scatterometer wind products

Validation and intercomparison of HY-2A/MetOp-A/Oceansat-2 scatterometer wind products

Assimilation of ASCAT winds using 4DVAR: an impact study

Research on a Method for Simulating Multiview Ocean Wave Synchronization Data by Networked SAR Satellites

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