This paper is particularly relevant to investigations into the spread of organisms that remain close to shore over timescales of days-to-weeks, e.g., the spread of marine non-native species and pathogenetic parasites, but is equally relevant to simulations tracking the dispersal of eDNA or coastal pollutants such as oil and plastics.
This paper develops a coupling between SWAN and Thetis models to account for wave–current interactions occurring by the co-existence of wave and current flows. The different grids and time-steps employed by the model components allow greater flexibility. The two models run consecutively, and communicate internally to exchange the necessary parameters. These are the significant wave height, mean wave direction, mean wavelength and percentage of wave-breaking calculated by SWAN necessary for calculating radiation stress and wave roller effects, while Thetis provides water elevation and current velocity fields.
Monitoring the ocean carbon cycle is key to improved understanding. Satellites play a major role in our global carbon monitoring system. To make full use of satellite observations for ocean carbon monitoring the remote-sensing community needs to work closely with in-situ data experts, physical and biogeochemical modellers, Earth system scientists, climate scientists and marine policy experts.
With AI-driven labor market transformations being affected by economic troubles and other factors, this article explores the strategies leaders are using to help workers navigate these changes. Specifically, leaders are stepping up investing in at least four strategies to prepare workers for the prevailing disruption and empower them to successfully navigate the change while ensuring healthy work cultures and compelling work opportunities for all.
This study proposes a deep learning model based on a convolutional neural network, which can effectively fuse atmospheric information (wind field) and station water level information and can effectively forecast the station water level and also have a good response to the anomalous water level increase brought by storm surge.
The survey presented here was conducted to better understand public perceptions of climate change, human impacts and the value and management of marine and coastal ecosystems.
This paper synthesized current knowledge of mesoscale eddies and their impacts on the marine ecosystem across the North Pacific and its marginal Seas, across the CCS region , the northeastern North Pacific and the Bering Sea, the western boundary of the North Pacific and marginal seas, and the extratropical open North Pacific. How climate change will modify mesoscale processes remains a key open challenge.
This paper based on three implemented Regional Climate Models (RCMs), namely CMCC-CCLM, CNRM-ALADIN52, and GUF-CCLM-NEMO, for RCP4.5 and RCP8.5 scenarios of the 21st century. Atmospheric modelling datasets cover the Reference (1971–2000) and Future (2071–2100) Periods of climate projections. The results produced within this study can be used for investigations in specific locations of the Mediterranean basin within integrated hydrologic/hydrodynamic modelling under projected climate change conditions during the 21st century.
This paper show the mathematical and theoretical background of the machine learning algorithm used in this work, the LSTM. The data used are described and the methodology of framework is presented. It shows the predictions results based on LSTM and comparisons with ERA5 and buoy observations.
The Internet of Things (IoT) has revolutionized the traditional healthcare systems into intelligent system by allowing remote access and continuous monitoring of patient data. Specifically, first a novel scalable blockchain architecture is proposed to ensure data integrity and secure data transmission by leveraging Zero Knowledge Proof (ZKP) mechanism. Then, BDSDT integrates with the off-chain storage InterPlanetary File System (IPFS) to address difficulties with data storage costs and with an Ethereum smart contract to address data security issues.
