Evidence map›Paper›PMID 34577330›Full record

ArticleSensors (Basel, Switzerland)2021

Significant Wave Height Estimation from Joint CYGNSS DDMA and LES Observations.

Shuai Yang, Shuanggen Jin, Yan Jia, Mingda Ye

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shuai YangShanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China.ORCID 0000-0001-7317-8684
Shuanggen JinShanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China.ORCID 0000-0002-5108-4828
Yan JiaDepartment of Surveying and Geoinformatics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Mingda YeShanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China.ORCID 0000-0002-5864-2458

Funding

Jiangsu Province Distinguished Professor Project No. R2018T20National Natural Science Foundation of China No.41761134092Shanghai Leading Talent Project No. E056061Startup Foundation for Intro-duking Talent of NUIST No.2243141801036Strategic Priority Research Program Project of the Chinese Academy of Sciences No. XDA23040100
6 · The paper itself

Abstract

The significant wave height (SWH) of oceans is the main parameter in describing the sea state, which has been widely used in the establishment of ocean process models and the field of navigation and transportation. However, traditional methods such as satellite radar altimeters and buoys cannot achieve SWH estimations with high spatial and temporal resolution. Recently, the spaceborne Global Navigation Satellite System reflectometry (GNSS-R) has provided an opportunity to estimate SWH with a rapid global coverage and high temporal resolution observations, particularly with the Cyclone Global Navigation Satellite System (CYGNSS) mission. In this paper, SWH was estimated using the polynomial function relationship between SWH from ERA5 and Delay-Doppler Map Average (DDMA) as well as Leading Edge Slope (LES) from CYGNSS data. Then, the SWH estimated from CYGNSS data was validated by ERA-Interim data, AVISO data, and buoy data. The results showed that the average correlation coefficient of CYGNSS SWH was 0.945, and the average RMSE was 0.257 m when compared to the ERA-Interim SWH data. The RMSE was 0.423 m and the correlation coefficient was 0.849 when compared with the AVISO SWH. The correlation coefficient with the buoy data was 0.907, and the RMSE was 0.247 m. This method can provide suitable SWH estimation data for ocean dynamics research and ocean environment prediction.

Indexed as

Cyclonic StormsOceans and SeasRadarCYGNSSDDMAGNSS-RLESSWH

Identifiers

PMID34577330
PMCPMC8471590

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