Oceanic Environmental Factors Research Articles

A training strategy for enhancing prediction accuracy of high magnitude oceanic environmental factors based on deep learning model

Oceanic environmental factors have marked impacts on marine ecosystems and economic development. Variations in high-magnitude oceanic environmental factors often lead to marine disasters and ecological crises. Previous studies have demonstrated the success of deep learning in marine environmental prediction tasks; however, limited research has specifically targeted high-magnitude oceanic environmental factors. Here, we propose a deep-learning model training strategy that enhances the model's attention to high-magnitude oceanic environmental factors by incorporating an adaptive weight matrix, thereby improving prediction accuracy. We evaluated the proposed training strategy for two prediction tasks: time-series and physics-based predictions. Compared to the baseline model, the prediction error for high-magnitude oceanic environmental factors was reduced by up to 56.93 % using this training strategy, and the stability of the model performance in medium-to long-term forecasts was enhanced. In addition, the suitability of the strategy across diverse scenarios was examined by assessing its robustness and computational overhead. This study provides new insights for more accurate prediction of oceanic environmental factors.

Applying Adaptive Neuro-Fuzzy Inference System to Improve Typhoon Intensity Forecast in the Northwest Pacific

Typhoon intensity forecast is an important issue. The objective of this study is to construct a 5-day 12-hourly typhoon intensity forecast model based on the adaptive neuro-fuzzy inference systems (ANFIS) to improve the typhoon intensity forecast in the Northwest Pacific. It analyzed the improvement of the ANFIS typhoon intensity forecast model by comparing it with the MLR model when only the atmospheric factor or both atmospheric and oceanic factors are considered. This study collected the SHIPS (Statistical Hurricane Intensity Prediction Scheme) developmental data of typhoons in the Northwest Pacific before landing from 2000 to 2012. The input factors of the ANFIS model were simplified by the stepwise regression procedure (SRP). Subtractive clustering (SC) was used to determine the number of ANFIS rules and to reduce model complexity. Model Index (MI) was taken as the clustering standard of SC to determine the network architecture of the ANFIS typhoon intensity forecast model. The simulated results show that the MI could effectively determine the radius of influence of SC. The typhoon intensity forecast was significantly improved after oceanic environmental factors were added. The improvement of RMSE of ANFIS was the highest at 84 h; the improvement of ANFIS on the underestimated ratio was primarily positive. The Typhoon Songda case study shows that the maximum bias of ANFIS is greatly improved, at 60 h of the lead time, and the improvement percentage of maximum bias is the highest (39%). Overall, the ANFIS model could effectively improve the MLR model in typhoon intensity forecast.

Quantification of the impact of environmental factors on chlorophyll in the open ocean

Many previous studies of the impact of oceanic environmental factors on chlorophyll (CHL) in a specific region focused on sea surface temperature (SST), mixed-layer depth (MLD), or wind stress (WS) alone. In this study, relationship between CHL and all those environmental factors (SST, MLD, and WS) in the open ocean was quantified for five regions within the subtropical gyres and the variation trend of 13-year (2003–2015) was analyzed using satellite observations and Argo measurements. The correlation analysis results show that MLD was correlated positively with CHL, SST was correlated negatively with CHL, and the correlation between CHL and WS was either positive or negative. Based on the significance of the correlations, models representing the relationships were established using the multiple linear regression and analyzed, showing that the environmental factors were the major determinants of CHL change. The regression coefficients show that both SST and MLD have remarkable effect on CHL. Our derived models could be used to diagnose the past changes, understand present variability, and predict the future state of CHL changes based on environmental factors, and help us understand the dynamics of CHL variation in the open ocean.

Characteristics of environmental factors contributing to ALOS-2 PALSAR wind speed errors

ABSTRACT Environmental factors affecting the errors in wind speed estimates were investigated using the Advanced Land Observing Satellite-2 Phased Array L-band Synthetic Aperture Radar-2 (ALOS-2 PALSAR-2) data for the period from 1 November 2014 to 30 November 2017. In total, 45 ALOS-2 PALSAR-2 Stripmap Fine mode images with horizontal dual-polarization were collected, and the wind speeds were calculated using the L-band Geophysical Model Function (GMF) in 2009. Validation of the SAR-derived wind speeds to in-situ wind, converted to the 10-m neutral wind, resulted in the root-mean-square error of 2.11 ms−1, bias error of −1.16 m s−1, and standard deviation of 1.78 m s−1. Investigation of the wind speed errors revealed the contributions of diverse oceanic environmental factors such as the ship and its side-lobe effect that is negligible at a distance of more than 200% of the ship radius, v-shaped ship wakes are accompanied by the Kelvin waves and turbulent wakes caused by ship movement. The sand ridge, formed due to the interaction of shallow bathymetry and tidal currents, contributed to the wind speed errors of more than 50%. The internal waves caused prominent wind speed errors of more than 100%. The atmospheric gravity waves, generated by the orographic effect, caused wind speed fluctuations up to 13.4 m s−1. This study addressed the importance of understanding the factors that affect the normalized radar cross-section of the SAR image in order to correctly retrieve wind speeds from SAR data.

Double Entropy Joint Distribution Function and Its Application in Calculation of Design Wave Height.

Wave height and wave period are important oceanic environmental factors that are used to describe the randomness of a wave. Within the field of ocean engineering, the calculation of design wave height is of great significance. In this paper, a periodic maximum entropy distribution function with four undetermined parameters is derived by means of coordinate transformation and solving conditional variational problems. A double entropy joint distribution function of wave height and wave period is also derived. The function is derived from the maximum entropy wave height function and the maximum entropy periodic function, with the help of structures of the Copula function. The double entropy joint distribution function of wave height and wave period is not limited by weak nonlinearity, nor by normal stochastic process and narrow spectrum. Besides, it can fit the observed data more carefully and be more widely applicable to nonlinear waves in various cases, owing to the many undetermined parameters it contains. The engineering cases show that the recurrence level derived from the double entropy joint distribution function is higher than that from the extreme value distribution using the single variables of wave height or wave period. It is also higher than that from the traditional joint distribution function of wave height and wave period.

Monthly variability of Luzon Strait tropical cyclone intensification over the Northern South China Sea in recent decades

A number of tropical cyclones (TCs) in the western North Pacific (WNP) pass through Luzon Strait (LS) into the South China Sea (SCS) from June to November every year. The monthly variability of the ratio of TC intensity change, Rtc, shows that majority of the LSTCs achieve their lifetime maximum intensity (LMI) over the northern SCS (WNP) during August–September (June–July and October–November). Furthermore, compared to August, LSTCs in September are more easily intensified, suggesting that atmospheric and/or oceanic environments over the northern SCS in September are more favorable for TC development. The monthly-averaged oceanic and atmospheric environmental factors, including sea surface temperature, upper-ocean warm layer depth, vertical wind shear, relative humidity and large-scale low-level vorticity, are compared. The comparison between August and September is mainly studied because of the higher LSTCs frequency in these 2 months. The intensification tendency of LSTCs in September is primarily attributed to the relative thick upper-ocean warm layer and weak vertical wind shear. The transition of East Asian summer monsoon to winter monsoon tends to provide more favorable environmental conditions in September than in August for TC intensification in the northern SCS.

Environmental factor analysis of cholera in China using remote sensing and geographical information systems.

Cholera is one of a number of infectious diseases that appears to be influenced by climate, geography and other natural environments. This study analysed the environmental factors of the spatial distribution of cholera in China. It shows that temperature, precipitation, elevation, and distance to the coastline have significant impact on the distribution of cholera. It also reveals the oceanic environmental factors associated with cholera in Zhejiang, which is a coastal province of China, using both remote sensing (RS) and geographical information systems (GIS). The analysis has validated the correlation between indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local number of cholera cases based on 8-year monthly data from 2001 to 2008. The results show the number of cholera cases has been strongly affected by the variables of SST, SSH and OCC. Utilizing this information, a cholera prediction model has been established based on the oceanic and climatic environmental factors. The model indicates that RS and GIS have great potential for designing an early warning system for cholera.

Detection of the Hebei Spirit oil spill on SAR imagery and its temporal evolution in a coastal region of the Yellow Sea

To investigate the evolution of a disastrous oil spill from a vessel collision, known as the Hebei Spirit accident, off the coast of Korea in the Yellow Sea on 6 December 2007, oil slicks were identified from Synthetic Aperture Radar (SAR) images using a neural network (NN) and an adaptive threshold method. The results from the two objective methods showed good agreement, enough for the estimation of the extent of oil patches and their trajectories, with the exception of negligible errors at the boundaries. Quantitative analyses showed that the detected oil slicks moved southward, corresponding to the prevailing wind and tidal currents, and gradually dissipated during the spill, except for an extraordinary rapid decrease in onshore regions at the initial stage. The initial dissipation of the spilt oil was induced by tidal mixing in the tidal front zone. The spatial and temporal variations of the oil slicks confirmed the influence of atmospheric and oceanic environmental factors. The overall horizontal migration of the oil spills detected from consecutive SAR images was mainly driven by Ekman drift during the winter monsoon rather than the tidal residual current.

지상용 열적외선 센서의 항공기 탑재를 통한 연안 해수표층온도 추출

The Sea Surface Temperature (SST) is one of the most important oceanic environmental factors in determining the change of marine environments and ecological activities. Satellite thermal infrared images can be effective for understanding the global trend of sea surface temperature due to large scale. However, their low spatial resolution caused some limitations in some areas where complicated and refined coastal shapes due to many islands are present as in the Korean Peninsula. The coastal ocean is also very important because human activities interact with the environmental change of coastal area and most aqua farming is distributed in the coastal ocean. Thus, low-cost airborne thermal infrared remote sensing with high resolution capability is considered for verifying its possibility to extract SST and to monitor the changes of coastal environment. In this study, an airborne thermal infrared system was implemented using a low-cost and ground-based thermal infrared camera (FLIR), and more than 8 airborne acquisitions were carried out in the western coast of the Korean Peninsula during the periods between May 23, 2012 and December 7, 2013. The acquired thermal infrared images were radiometrically calibrated using an atmospheric radiative transfer model with a support from a temperature-humidity sensor, and geometrically calibrated using GPS and IMU sensors. In particular, the airborne sea surface temperature acquired in June 25, 2013 was compared and verified with satellite SST as well as ship-borne thermal infrared and in-situ SST data. As a result, the airborne thermal infrared sensor extracted SST with an accuracy of 1oC.

INFLUENCE OF THE MARINE ENVIRONMENT VARIABILITY ON THE YELLOWFIN TUNA (THUNNUS ALBACARES) CATCH RATE BY THE TAIWANESE LONGLINE FISHERY IN THE ARABIAN SEA, WITH SPECIAL REFERENCE TO THE HIGH CATCH IN 2004

In this study, we collected Taiwanese longline (LL) fishery data and environment variables during the period of 19982004 to investigate the relationship between LL catch data of yellowfin tuna (YFT) and oceanic environmental factors using a principal component analysis (PCA). Results of the PCA showed that monthly variations in catch per unit effort (CPUE) values were significantly correlated with the sea surface temperature (SST), subsurface temperature at 105 m, thermocline depth (horizontal) gradient magnitude, chlorophyll-a concentration, and fish size. April and May were the warmest months of the year in terms of the SST, and the thermocline was generally deep. After July, a drop in the temperature below the preferred temperature range for YFT is probably the reason that the CPUE subsequently decreased in the period of 1998-2003. It was suggested that the CPUE by age at a given time was significantly affected by chlorophyll-a concentrations 1-3 months prior to that time. The lower thermocline depth gradient magnitude enhanced the aggregation density of YFT in 2004 which showed that the high catch and high CPUE of the YFT fishery increased from the western to the eastern Arabian Sea.

Causative Mechanism of the Continental Margin Polymetallic Nodules from the South China Sea and its Resource Effects

Polymetallic nodules are one of the most important sedimentary mineral resources in the ocean, in which iron, manganese, copper, cobalt, nickel and other metals are rich, and rare earth elements are rich, too. The samples are collected from the northwest continental margin of South China Sea (SCS). Their model show the similar appearance to the oceanic nodules which collected from the Pacific and Indian Ocean. They are big, regular shape and clear layers. But their geochemical characteristics show distinct difference with oceanic nodules.The samples formed by multiple millimeter-thick layers of Fe and Mn oxyhydroxides surrounding the nucleus composed of plastic marl and sediment. Massive, laminated, detrital and mottled to dendritic textural features were developed by the Fe and Mn oxyhydroxide layers.Based on the detailed study of the geochemistry and growth rate, the nodules may represent new-type ones which grow fastly in high sediment rates environment from the northwest continental margin of the SCS. The reason of the fast growth may be affected by the environmental fluctuations and the change of terrigenous sediments. Elements correlation of Mn-Fe-(Cu+Ni) suggests that the origin of the sample may be of hydrogenic. It may be show that these nodules are dominative of the special environment of the marginal sea which includes the geographical condition and the oceanic environmental factors. The average content of Rare Earth Elements (REEs) in these samples are much higher than those recorded in Earth’ crust and sedimentary rocks. The enrichment of rare earth elements is controlled by iron and manganese oxides and clay minerals in nodules, which could absorb rare earth elements from seawater and terrigenous sediment. Ce elements are highly enriched, making polymetallic nodules become the first used rare earth elements in oceanic mineral development.

Ocean variations associated with fishing conditions for yellowfin tuna (Thunnus albacares) in the equatorial Atlantic Ocean

Abstract Lan, K-W., Lee, M-A., Lu, H-J., Shieh, W-J., Lin, W-K., and Kao, S-C. 2011. Ocean variations associated with fishing conditions for yellowfin tuna (Thunnus albacares) in the equatorial Atlantic Ocean. – ICES Journal of Marine Science, 68: 1063–1071. In this study, the Taiwanese longline (LL) fishery data were divided into two types: regular LL and deep LL. Furthermore, we collected environmental variables, such as sea surface temperature (SST), subsurface temperature, chlorophyll a concentration, net primary productivity, windspeed, and the north tropical Atlantic SST index (NTA) during the period 1998–2007 to investigate the relationship between LL catch data and oceanic environmental factors using principal component analysis (PCA). After the daily LL was separated into two types of LL, the results indicated that the deep LL was the major fishery catching yellowfin tuna (YFT) in the equatorial Atlantic Ocean. In 2003–2005, especially in 2005, the monthly catch by deep LL was double those of other years. The spatial distribution of the nominal catch per unit effort (cpue) by deep LL showed the maximum aggregation of YFT in waters with temperature above 24–25°C. The YFT mainly aggregated in the equatorial Atlantic, extending east in the first and second quarters of the year. In the third quarter of the year, the SST decreased off West Africa and the YFT migrated westwards to 15°W. Results of PCA indicated that higher subsurface water temperatures resulted in a deeper thermocline and caused a higher cpue of YFT, but the influence of NTA on the cpue of YFT seemed to be insignificant.

Lipidomics of Aiptasia pallida and Symbiodinium: a model system for investigating the molecular basis of coral symbiosis

Changing oceanic environmental factors disrupt the symbiotic relationship between cnidarians and a photosynthetic dinoflagellate symbiont, leading to expulsion of the symbiont from the cnidarian and endangering fragile coral ecosystems. The symbiosis between the anemone Aiptasia pallida and Symbiodinium is a model system for studying the molecular changes that occur during the establishment, maintenance and disruption of symbiosis. The symbiont resides in a specialized membrane component called the symbiosome membrane indicating dramatic changes to the lipidome of the anemone and symbiont. We have undertaken a comprehensive characterization of the lipid composition of the anemone, and symbiont at all stages of the symbiotic relationship. Lipids from the aposymbiotic symbiont, aposymbiotic anemone, and symbiotic anemone and symbiont were extracted and analyzed using liquid chromatography electrospray ionization mass spectrometry. Preliminary results based on exact mass and collision‐induced decomposition mass spectrometry reveal the presence of glycerophospholipids, phosphatidylethanolamine, phosphatidylserine, and phosphatidylcholine and interestingly, several molecular ions do not correspond to any known lipid molecular species. Lipidomic changes will be correlated to transcriptomic changes known to occur at the various stages of symbiosis.