Data assimilation has been developed into an effective technology that can utilize a large number of multi-source unconventional data. It cannot only provide the initial field for the ocean numerical prediction model, but also construct the ocean reanalysis datasets and provide the design basis for the ocean observation plan. In data assimilation, the estimation of the observation error is of paramount importance, because the quality of the analysis depends on it. In general, the observation error covariance matrix is diagonal or assumed to be diagonal, which means that the observation errors are independent from one another. However, there are indeed correlations in the observation errors. A diagnostic method has been developed, which can estimate a correlated and more accurate observation error covariance matrix. The proposed method combines an ensemble square-root Kalman filter with the diagnostic method, providing an estimation of the observation error covariance matrix. In order to test the performance of the method, the numerical experiments are performed with the Lorenz 96 model and a Shallow water model. The more accurate observation error covariance matrix can be obtained to use in ensemble square-root Kalman filter by using the new method. We could find using the estimated correlated observation error in the data assimilation improves the analysis.
The circulation induced by the wind and the North Brazil Undercurrent (NBU) in and surrounding the Japaratuba submarine canyon on the continental shelf of the basin of Sergipe and Alagoas is described using numerical modeling. The numerical simulations were implemented to determine the canyon influence in the local hydrodynamics and in the volume flow normal to the coast, considering several different scenarios, including a homogeneous and stratified fields of temperature and salinity. Northeast and East winds favor an upward flow in the canyon, while Southeast and South winds privilege subsidence. Winds parallel to the coast cause greater volume flow in the canyon section: 40° winds (relative to true the North, parallel to the coast) caused the highest upward flow, while winds from 215° to 220° caused the highest subsidence. On the other hand, the NBU favors subsidence motion and seems to predominate over the wind forcing.
Mangroves and coral reefs are among the major ecosystems of tropical and subtropical coastlines. The Andaman group of islands, situated at the juncture of Bay of Bengal and Indian Ocean, are one of the richest coastal ecosystems of India in terms of biodiversity. Since the tsunami waves of 2004 affected this region severely, the outer fringes as well as inland areas of these islands faced extensive ecological degradation. Mayabunder is one such place of this region, where corals and mangroves had experienced both natural and anthropogenic threat. Considering the notable vulnerability of this coastal environment, the present study aimed to assess the transformations of the coral and mangrove ecosystems at Mayabunder both in pre-tsunami and post-tsunami periods till the present year using multi-temporal satellite imageries and geospatial techniques. Results showed that the areal coverage of healthy living coral reefs was reduced by 466.56 ha (10.42 %) from 1990 to 2000. Afterwards, the coupled ecosystem had experienced serious degradation again during the 2000−2010 phase. The areal coverage of dense mangroves decreased by 47.37%, whereas the area of dead coral covers showed a significant rise of 55.52%. However, partial restoration of both mangroves as well as healthy corals had also been observed here in recent years. It was raised from the extensive field visits and feedbacks from local inhabitants that this restoration initiative could become more effective if a participatory mode of management is adopted.
Pampus argenteus (Perciformes: Stromateidae) is widely distributed along the coast of China, Indian Ocean, Arabian Gulf and North Sea. Due to overfishing and environmental degradation, its resources reduced year after year. Thus, new management strategies are urgently needed for the sustainable growth and utilization of this species. Characterization of the genetic variation of this fish species is essential for conserving the genetic resource and restraining the population decline. Therefore, it is necessary to have a clear understanding of the intraspecific genetic diversity and population structure of the species. In this study, we assess the genetic diversity and population structure of P. argenteus by using microsatellites. We genotyped 240 P. argenteus individuals from eight wild populations collected from Shidao (SD), Lianyungang (LYG), Lvsi (LS), Zhoushan (ZS), Dongtou (DT), Xiapu (XP), Haikou (HK), and Beibuwan (BBW) along the coast of China using fifteen polymorphic microsatellites. A total of 139 alleles were determined at 15 loci across the eight populations, and a relatively high level of genetic diversity was observed, with observed heterozygosity (Ho) and expected heterozygosity (He) ranging from 0.100 to 1.000, and from 0.669 to 0.934 per locus-location combination, respectively. LS had the highest average allele (number of alleles, A=15.200), and HK the lowest (A=13.000). Hos of P. argenteus are less than Hes, indicating lack of heterozygote within populations. Analysis of molecular variance (AMOVA) showed that most variation (95.66%) occurred within populations, suggesting that this is the main source of total variance. This study will provide useful information for conservation and sustainable exploitation of this important fishery resource.
