The HY-2 satellite and its preliminary assessment

Jiang, Xingwei; Lin, Mingsen; Liu, Jianqiang; Zhang, Youguang; Xie, Xuetong; Peng, Hailong; Zhou, Wu

doi:10.1080/17538947.2012.658685

Cited by 86 publications

(34 citation statements)

References 7 publications

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“…Table 7 lists the RMSEs of the wind speed and direction at seven levels (here, 2-24 m¨s´1 is the designed valid range of the wind speed [2]). The corresponding Beaufort wind scales are also shown.…”

Section: Discussionmentioning

confidence: 99%

“…The vertical lines at 2 m¨s´1 and 20˝highlight the designed precisions of the wind speed and direction in H2SCAT, respectively [2]. Table 6 summarizes the proportion of the wind speed and direction residuals within the designed precision.…”

Section: Residual Pdf Analysis Of Different Datamentioning

confidence: 99%

“…NSOAS performs wind inversion by the maximum likelihood estimation (MLE) method and remove ambiguities by a circle median filter. The retrieval process is detailed in elsewhere, while measurements of sigma-0 flagged by land or ice were removed [2,46]. The designed accuracy in RMSE of H2SCAT mission is <2 m¨s´1 or <10% for wind speed and <20˝for wind direction, between wind speeds of 2 and 24 m¨s´1 [2].…”

Section: H2scat Level-2 Nrt Wind Vectorsmentioning

confidence: 99%

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Evaluation of HY-2A Scatterometer Wind Vectors Using Data from Buoys, ERA-Interim and ASCAT during 2012–2014

et al. 2016

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Abstract:The first Chinese operational Ku-band scatterometer on board Haiyang-2A (HY-2A), launched in August 2011, is designed for monitoring the global ocean surface wind. This study estimates the quality of the near-real-time (NRT) retrieval wind speed and wind direction from the HY-2A scatterometer for 36 months from 2012 to 2014. We employed three types of sea-surface wind data from oceanic moored buoys operated by the National Data Buoy Center (NDBC) and the Tropical Atmospheric Ocean project (TAO), the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis data (ERA-Interim), and the advanced scatterometer (ASCAT) to calculate the error statistics including mean bias, root mean square error (RMSE), and standard deviation. In addition, the rain effects on the retrieval winds were investigated using collocated Climate Prediction Center morphing method (CMORPH) precipitation data. All data were collocated with the HY-2A scatterometer wind data for comparison. The quality performances of the HY-2A NRT wind vectors data (especially the wind speeds) were satisfactory throughout the service period. The RMSEs of the HY-2A wind speeds relative to the NDBC, TAO, ERA-Interim, and ASCAT data were 1.94, 1.73, 2.25, and 1.62 m¨s´1, respectively. The corresponding RMSEs of the wind direction were 46.63˝, 43.11˝, 39.93˝, and 47.47˝, respectively. The HY-2A scatterometer overestimated low wind speeds, especially under rainy conditions. Rain exerted a diminishing effect on the wind speed retrievals with increasing wind speed, but its effect on wind direction was robust at low and moderate wind speeds. Relative to the TAO buoy data, the RMSEs without rain effect were reduced to 1.2 m¨s´1 and 39.68˝for the wind speed direction, respectively, regardless of wind speed. By investigating the objective laws between rain and the retrieval winds from HY-2A, we could improve the quality of wind retrievals through future studies.

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Section: Discussionmentioning

confidence: 99%

Section: Residual Pdf Analysis Of Different Datamentioning

confidence: 99%

Section: H2scat Level-2 Nrt Wind Vectorsmentioning

confidence: 99%

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Evaluation of HY-2A Scatterometer Wind Vectors Using Data from Buoys, ERA-Interim and ASCAT during 2012–2014

et al. 2016

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“…C HINA'S marine dynamic environment satellite HY-2A, with a nadir-looking pulse-limited radar altimeter onboard as one of its main payloads, was launched on August 16, 2011 [1], [2]. The sea surface height (SSH) product is one of the main products of the HY-2A altimeter.…”

Section: Introductionmentioning

confidence: 99%

HY-2A Altimeter Time Tag Bias Estimation Using Reconstructive Transponder

Wan

Guo

Zhao

et al. 2015

IEEE Geosci. Remote Sensing Lett.

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Independent clocks provide time tags for the precision orbit determination (POD) equipment and the radar altimeter onboard the HY-2A satellite, and a bias between POD data' time tag and corresponding range observation's time tag from the HY-2A altimeter exists. The time tag bias contributes a bias in the sea surface height observation due to the nonzero time rate of change of the HY-2A altimeter's height. A transponder for in-orbit radar altimeter calibration provides an approach to estimate the time tag bias. The altimeter receives the responding signals from the transponder and generates ranges. Pertinent reference ranges are obtained from the POD data and the transponder's coordinate. Using the ranges from the radar altimeter and the reference ranges, the time tag bias between the POD data and the altimeter observations can be estimated. During an in situ HY-2A altimeter calibration campaign using a reconstructive transponder from August 9, 2012, to July 20, 2014, 17 estimations of the altimeter's time tag bias were obtained. The preliminary results are presented in this letter.

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“…In situ measurements using ships, buoys, shore-based stations and other sources are the most accurate ways to obtain sea wind information, but they are associated with drawbacks, such as high cost and coarse spatial coverage, considering the large scale of the ocean. At present, microwave scatterometers, e.g., ASCAT-A/B [1,2], HY-2 [3], Oceansat-2 [4], the full-polarimetric radiometer on WindSat [5], radar altimeters [6,7] and Synthetic Aperture Radar (SAR), are the primary remote sensing sensors that can be used to obtain all-weather and global coverage sea wind information. Each of the abovementioned types of wind sensors has advantages, as well as drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Derivation of Sea Surface Wind Directions from TerraSAR-X Data Using the Local Gradient Method

Wang

2016

Remote Sensing

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Derivation of sea surface wind direction is a key step of sea surface wind retrieval from spaceborne Synthetic Aperture Radar (SAR) data. This technical note describes an implementation of the Local Gradient (LG) method to derive sea surface wind directions at a scale of a few kilometers from X-band spaceborne SAR TerraSAR-X (TS-X) data in wide swath mode. The 180˝ambiguity in the derived sea surface wind direction is automatically eliminated using a single reference wind direction from external data sources. Several typical cases acquired in the North Sea were presented to demonstrate the derivation of sea surface wind direction under different wind situations using this method. The derived sea surface wind direction were further compared to atmospheric model prediction results. In addition, a practical method is introduced to address ambiguity in the derived sea surface wind directions using the LG method in a typhoon case with rotating surface wind structure. By interpolating the derived wind directions at a scale of kilometers, sea surface wind speeds with a spatial resolution of 500 m are subsequently retrieved using the X-band SAR sea surface wind Geophysical Model Function (GMF). The approach accomplished by combining the LG method with the X-band GMF for deriving sea surface wind in high spatial resolution demonstrates its potential for operational service.

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The HY-2 satellite and its preliminary assessment

Cited by 86 publications

References 7 publications

Evaluation of HY-2A Scatterometer Wind Vectors Using Data from Buoys, ERA-Interim and ASCAT during 2012–2014

Evaluation of HY-2A Scatterometer Wind Vectors Using Data from Buoys, ERA-Interim and ASCAT during 2012–2014

HY-2A Altimeter Time Tag Bias Estimation Using Reconstructive Transponder

Derivation of Sea Surface Wind Directions from TerraSAR-X Data Using the Local Gradient Method

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