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  • 1
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 119 (2014): 8512–8529, doi:10.1002/2014JC010221.
    Description: Using the “interior + surface quasigeostrophic” (isQG) method, the density and horizontal velocity fields of the ocean's interior can be retrieved from surface data. This method was applied to the Simple Ocean Data Assimilation (SODA) and the Hybrid Coordinate Ocean Model (HYCOM)/Navy Coupled Ocean Data Assimilation (NCODA) reanalysis data sets. The input surface data include sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS), and a region-averaged stratification. The retrieved subsurface fields are compared with reanalysis data for three tested regions, and the results indicate that the isQG method is robust. The isQG method is particularly successful in the energetic regions like the Gulf Stream region with weak stratification, and the Kuroshio region with strong correlation between sea surface density (SSD) and SSH. It also works, though less satisfactorily, in the Agulhas leakage region. The performance of the isQG method in retrieving subsurface fields varies with season, and peaks in winter when the mixed layer is deeper and stratification is weaker. In addition, higher-resolution data may facilitate the isQG method to achieve a more successful reconstruction for the velocity retrieval. Our results suggested that the isQG method can be used to reconstruct the ocean interior from the satellite-derived SSH, SST, and SSS data in the near future.
    Description: This work was jointly supported by the MOST of China (grant 2011CB403505 & 2014CB953904), the China Special Fund for Meteorological Research in the Public Interest (NO. GYHY201406008), the Strategic Priority Research Program of the Chinese Academy of Sciences (grant XDA11010304), National Natural Science Foundation of China (grant 41376021). J. Wang is supported by the National Science Foundation (NSF) through grant OCE-1234473.
    Description: 2015-06-12
    Keywords: IsQG method ; Sea surface and interior ; Reconstruction ; Satellite remote sensing ; SODA reanalysis ; HYCOM/NCODA reanalysis
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
    Publication Date: 2019
    Description: Background: Pesticide poisoning is an important issue in rural China, and is also a major public health problem that affects the health of farmers. The purpose of this paper is to explore the epidemiology of pesticide poisoning in Jiangsu Province, and to put forward the relevant suggestions on the logical and discerning utilization of the pesticides. Methods: According to the data of the pesticide poisoning report card established by the health hazard detection information system, the cases of pesticide poisoning in Jiangsu Province from 2006 to 2018 were exported to Excel, and the database of pesticide poisoning was established. Furthermore, the imported data was screened and collected. A descriptive statistical analysis had been employed on this data utilizing SPSS 20.0. Results: Between the years 2006 and 2018, 38,513 pesticide poisoning cases were registered in Jiangsu Province, with a downward trend. Meanwhile, 77.83% of poisoning cases involved insecticide poisoning, followed by herbicide and rodenticide. The greater part of the diverse sorts of studied insecticide poisoning cases involved people aged between 30 and 59 years (57.51%). Poisoning cases caused by rodenticide accounted for a large proportion of people aged between 0 and 14 years (23.72%) in non-occupational pesticide poisoning. Regarding seasons, it was distinguished that more insecticide cases were reported in autumn (46.95% of the total number of cases). Pesticide poisoning was reported in 13 cities of Jiangsu Province, and among these, insecticide poisoning was reported mainly from the northern Jiangsu area, which was the same as rodenticide and herbicide. Conclusions: Although there is a decreased risk for pesticide poisoning among farmworkers in Jiangsu Province, the number of farmworkers with pesticide poisoning is still high. Further management of the pesticide utilization is necessary, especially insecticide. More attention ought to be paid to the protection of vulnerable groups, including children and the elderly.
    Print ISSN: 1661-7827
    Electronic ISSN: 1660-4601
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
    Published by MDPI
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  • 3
    Publication Date: 2019
    Description: Unmanned aerial vehicles (UAVs) equipped with dual-band crop-growth sensors can achieve high-throughput acquisition of crop-growth information. However, the downwash airflow field of the UAV disturbs the crop canopy during sensor measurements. To resolve this issue, we used computational fluid dynamics (CFD), numerical simulation, and three-dimensional airflow field testers to study the UAV-borne multispectral-sensor method for monitoring crop growth. The results show that when the flying height of the UAV is 1 m from the crop canopy, the generated airflow field on the surface of the crop canopy is elliptical, with a long semiaxis length of about 0.45 m and a short semiaxis of about 0.4 m. The flow-field distribution results, combined with the sensor’s field of view, indicated that the support length of the UAV-borne multispectral sensor should be 0.6 m. Wheat test results showed that the ratio vegetation index (RVI) output of the UAV-borne spectral sensor had a linear fit coefficient of determination (R2) of 0.81, and a root mean square error (RMSE) of 0.38 compared with the ASD Fieldspec2 spectrometer. Our method improves the accuracy and stability of measurement results of the UAV-borne dual-band crop-growth sensor. Rice test results showed that the RVI value measured by the UAV-borne multispectral sensor had good linearity with leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW); R2 was 0.62, 0.76, and 0.60, and RMSE was 2.28, 1.03, and 10.73, respectively. Our monitoring method could be well-applied to UAV-borne dual-band crop growth sensors.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI
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