Technical development of operational in-situ marine monitoring and research on its key generic technologies in China

In China,operational in-situ marine monitoring is the primary means of directly obtaining hydrological,meteorological,and oceanographic environmental parameters across sea areas,and it is essential for applications such as forecast of marine environment,prevention and mitigation of disaster,exploitation of marine resources,marine environmental protection,and management of transportation safety.In this paper,we summarise the composition,development courses,and present operational status of three systems of operational in-situ marine monitoring,namely coastal marine automated network station,ocean data buoy and voluntary observing ship measuring and reporting system.Additionally,we discuss the technical development in these in-situ systems and achievements in the key generic technologies along with future development trends.

The Potential Vertical Distribution of Bigeye Tuna (Thunnus obesus) and Its Influence on the Spatial Distribution of CPUEs in the Tropical Atlantic Ocean

Understanding the potential vertical distribution of bigeye tuna(Thunnus obesus) is necessary to understand the catch rate fluctuations and the stock assessment of bigeye tuna. To characterize the potential vertical distribution of this fish while foraging and determine the influences of the distribution on longline efficiency in the tropical Atlantic Ocean, the catch per unit effort(CPUE) data were compiled from the International Commission for the Conservation of Atlantic Tunas and the Argo buoy data were downloaded from the Argo data center. The raw Argo buoy data were processed by data mining methods. The CPUE was standardized by support vector machine before analysis. We assumed the depths with the upper and lower limits of the optimum water temperatures of 15℃ and 9℃ as the preferred swimming depth, while the lower limit of the temperature(12℃) associated with the highest hooking rate as the preferred foraging depth(D12) of bigeye tuna during the daytime in the Atlantic Ocean. The preferred swimming depth and foraging depth range in the daytime were assessed by plotting the isobath based on Argo buoy data. The preferred swimming depth and vertical structure of the water column were identified to investigate the spatial effects on the CPUE by using a generalized additive model(GAM). The empirical cumulative distribution function was used to assess the relationship between the spatial distribution of CPUE and the depth of 12℃ isolines and thermocline. The results indicate that 1) the preferred swimming depth of bigeye tuna in the tropical Atlantic is from 100 m to 400 m and displays spatial variation;2) the preferred foraging depth of bigeye tuna is between 190 and 300 m and below the thermocline;3) the number of CPUEs peaks at a relative depth of 30 –50 m(difference between the 12℃ isolines and the lower boundary of the thermocline);and 4) most CPUEs are within the lower depth boundary of the thermocline levels(LDBT) which is from 160 m to 230 m. GAM analysis indicates that the general relationship between the nominal CPUE and LDBT is characterized by a dome shape and peaks at approximately 190 m. The oceanographic features influence the habitat of tropical pelagic fish and fisheries. Argo buoy data can be an important tool to describe the habitat of oceanic fish. Our results provide new insights into how oceanographic features influence the habitat of tropical pelagic fish and fisheries and how fisheries exploit these fish using a new tool(Argo profile data).

Evaluation of NOAA/AVHRR Sea Surface Temperature at Full HRPT Resolution in the Northwest Pacific Ocean

The National Oceanic and Atmospheric Administration(NOAA)Polar Orbiting Environmental Satellites(POES)High Resolution Picture Transmission(HRPT)data in the Northwest Pacific Ocean has been acquired through the SeaSpace ground station located at the Ocean University of China since October 2000,and these data have been processed by the TeraScan system.The sea surface temperature(SST)products in the Northwest Pacific Ocean derived from Advanced Very High Resolution Radiometer(AVHRR)are evaluated.We compared the SST products with the buoy SSTs during the stable operational period of each satellite.There are a total of 33715 and 71819 matchups acquired for daytime and nighttime,respectively,between the NOAA/AVHRR SSTs and buoy SSTs.For each satellite,the biases and standard deviations at daytime are smaller than those at nighttime.The monthly biases at daytime generally oscillate around 0℃,except for NOAA-15.By contrast,the monthly biases at nighttime mostly oscillate around−0.5℃.Both daytime and nighttime biases exhibit seasonal oscillations for all satellites.The seasonal biases of the SST difference at daytime between each satellite and buoy are mostly within±0.25℃,except for the negative bias of−0.58℃in May for NOAA-18.The seasonal biases of the SST difference at nighttime are mostly around−0.5℃,and NOAA-16 has a lower bias,i.e.,−0.86℃,in April.These results indicate that the accuracy of the SST products is inconsistent for each satellite during different periods.It is suggested that the NOAA/AVHRR data should be reprocessed to provide highly accurate SST products.

Optimized Numerical Model Based Assessment of Wave Power Potential of Marmara Sea

Marmara Sea, located between Black Sea and Aegean Sea, is an important sea for ocean engineering activities. In this study, wave power potential of Marmara Sea was investigated using the third generation spectral wind-wave model MIKE 21 SW with unstructured mesh. Wind data was obtained from ECMWF ERA-Interim re-analyses wind dataset at 10 m with a spatial resolution of 0.1? for the period of 1994 to 2014. The numerical model was calibrated with measured wave data from a buoy station located in Marmara Sea. Mesh optimization was also performed to obtain the most suitable mesh structure for the study area. This study is the first that dealt with the determination of wave energy potential of Marmara Sea. The numerical model results are presented in terms of monthly, seasonal and annual average of wave power flux(k W m^(-1)). The maximum wave power flux is 1.13 kW m^(-1) and occurs in November. The overall annual mean wave power flux during 1994–2014 is found to be 0.27 kW m^(-1) in the offshore regions.