scholarly journals Distribution of soil selenium and its relationship with parent rocks in Chengmai County, Hainan Island, China

2021 ◽  
pp. 105147
Author(s):  
Gong Jingjing ◽  
Yang Jianzhou ◽  
Wu Hui ◽  
Fu Yangang ◽  
Gao Jianweng ◽  
...  
Keyword(s):  
Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 766
Author(s):  
Yi Jiang ◽  
Shuai Han ◽  
Chunxiang Shi ◽  
Tao Gao ◽  
Honghui Zhen ◽  
...  

Near-surface wind data are particularly important for Hainan Island and the South China Sea, and there is a wide range of wind data sources. A detailed understanding of the reliability of these datasets can help us to carry out related research. In this study, the hourly near-surface wind data from the High-Resolution China Meteorological Administration (CMA) Land Data Assimilation System (HRCLDAS) and the fifth-generation ECMWF atmospheric reanalysis data (ERA5) were evaluated by comparison with the ground automatic meteorological observation data for Hainan Island and the South China Sea. The results are as follows: (1) the HRCLDAS and ERA5 near-surface wind data trend was basically the same as the observation data trend, but there was a smaller bias, smaller root-mean-square errors, and higher correlation coefficients between the near-surface wind data from HRCLDAS and the observations; (2) the quality of HRCLDAS and ERA5 near-surface wind data was better over the islands of the South China Sea than over Hainan Island land. However, over the coastal areas of Hainan Island and island stations near Sansha, the quality of the HRCLDAS near-surface wind data was better than that of ERA5; (3) the quality of HRCLDAS near-surface wind data was better than that of ERA5 over different types of landforms. The deviation of ERA5 and HRCLDAS wind speed was the largest along the coast, and the quality of the ERA5 wind direction data was poorest over the mountains, whereas that of HRCLDAS was poorest over hilly areas; (4) the accuracy of HRCLDAS at all wind levels was higher than that of ERA5. ERA5 significantly overestimated low-grade winds and underestimated high-grade winds. The accuracy of HRCLDAS wind ratings over the islands of the South China Sea was significantly higher than that over Hainan Island land, especially for the higher wind ratings; and (5) in the typhoon process, the simulation of wind by HRCLDAS was closer to the observations, and its simulation of higher wind speeds was more accurate than the ERA5 simulations.


2021 ◽  
Vol 9 (3) ◽  
pp. 324
Author(s):  
Manli Zheng ◽  
Lingling Xie ◽  
Quanan Zheng ◽  
Mingming Li ◽  
Fajin Chen ◽  
...  

Using cruise observations before and after the typhoon Chebi in August 2013 and those without the typhoon in July 2012, this study investigates variations in current structure, nutrient distribution, and transports disturbed by a typhoon in a typical coastal upwelling zone east of Hainan Island in the northwestern South China Sea. The results show that along-shore northeastward flow dominates the coastal ocean with a volume transport of 0.64 × 106 m3/s in the case without the typhoon. The flow reversed southwestward, with its volume transport halved before the typhoon passage. After the typhoon passage, the flow returned back northeastward except the upper layer in waters deeper than 50 m and the total volume transport decreased to 0.10 × 106 m3/s. For the cross-shelf component, the flow kept shoreward, while transports crossing the 50 m isobath decreased from 0.25, 0.12 to 0.06 × 106 m3/s in the case without the typhoon as well as before and after typhoon passage, respectively. For the along-shore/cross-shelf nutrient transports, SiO32− has the largest value of 866.13/632.74 μmol/s per unit area, NO3− half of that, and PO43− and NO2− one order smaller in the offshore water without the typhoon. The values dramatically decreased to about one-third for SiO32−, NO3−, and PO43− after the typhoon, but changed little for NO2−. The disturbed wind field and associated Ekman flow and upwelling process may explain the variations in the current and nutrient transports after the typhoon.


2021 ◽  
Vol 35 (3) ◽  
pp. 774-786
Author(s):  
Jiankun Bai ◽  
Yuchen Meng ◽  
Ruikun Gou ◽  
Jiacheng Lyu ◽  
Zheng Dai ◽  
...  

2021 ◽  
Vol 13 (15) ◽  
pp. 2920
Author(s):  
Tingting Huang ◽  
Chenghui Ding ◽  
Weibiao Li ◽  
Yilun Chen

Continuous observations from geostationary satellites can show the morphology of precipitation cloud systems in quasi-real-time, but there are still large deviations in the inversion of precipitation. We used binary-connected area recognition technology to identify meso-β-scale rain clusters over Hainan Island from 1 June 2000 to 31 December 2018, based on Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM data. We defined and statistically analyzed the parameters of rain clusters to reveal the typical morphological and precipitation characteristics of rain clusters, and to explore the relationship between the parameters and rainfall intensity of rain clusters. We found that the area and long axis of rain clusters over land were larger than those over the ocean, and that continental rain clusters were usually square in shape. Rain clusters with a larger area and longer axis were concentrated on the northern side of the mountains on Hainan Island and the intensity of rain was larger on the northern and eastern sides of the mountains. The variation of continental rain clusters over time was more dramatic than the variation of oceanic clusters. The area and long axis of rain clusters was larger between 14:00 and 21:00 from April to September and the long axis of the oceanic rain clusters increased in winter. There were clear positive correlations between the area, long axis and shape of the rain clusters and the maximum rain rate. The area and long axis of continental rain clusters had a higher correlation with the rain rate than those of oceanic clusters. The establishment of a relationship between the morphology of rain clusters and precipitation helps us to understand the laws of precipitation and improve the prediction of precipitation in this region.


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