Bridging observations, theory and numerical simulation of the ocean using machine learning
Progress within physical oceanography has been concurrent with the increasing
sophistication of tools available for its study. The incorporation of machine learning (ML) …
sophistication of tools available for its study. The incorporation of machine learning (ML) …
Machine learning application in water quality using satellite data
N Hassan, CS Woo - IOP Conference Series: Earth and …, 2021 - iopscience.iop.org
Monitoring water quality is a critical aspect of environmental sustainability. Poor water
quality has an impact not just on aquatic life but also on the ecosystem. The purpose of this …
quality has an impact not just on aquatic life but also on the ecosystem. The purpose of this …
Mapping algal bloom dynamics in small reservoirs using Sentinel-2 imagery in Google Earth Engine
Freshwater algal blooms have caused ecological damage and public health concerns
throughout the world. Monitoring such blooms via in situ sampling is both costly and time …
throughout the world. Monitoring such blooms via in situ sampling is both costly and time …
Downscaling of ocean fields by fusion of heterogeneous observations using deep learning algorithms
S Thiria, C Sorror, T Archambault, A Charantonis… - Ocean Modelling, 2023 - Elsevier
We present a deep learning method to downscale low-resolution geophysical fields by
merging them with high-resolution data. The downscaling was performed using an …
merging them with high-resolution data. The downscaling was performed using an …
Annual variations in phytoplankton biomass driven by small-scale physical processes
Phytoplankton biomass exhibits substantial year-to-year changes, and understanding these
changes is crucial to fisheries management and projecting future climate. These annual …
changes is crucial to fisheries management and projecting future climate. These annual …
Recent Trends in SST, Chl‐a, Productivity and Wind Stress in Upwelling and Open Ocean Areas in the Upper Eastern North Atlantic Subtropical Gyre
JP Siemer, F Machín, A González‐Vega… - Journal of …, 2021 - Wiley Online Library
The global upper ocean has been warming during the last decades accompanied with a
chlorophyll‐a (Chl‐a) and productivity decrease. Whereas subtropical gyres show similar …
chlorophyll‐a (Chl‐a) and productivity decrease. Whereas subtropical gyres show similar …
Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
G Basterretxea, JS Font-Muñoz… - Ocean …, 2023 - os.copernicus.org
We examine 20 years of monthly global ocean color data and modeling outputs of nutrients
using self-organizing map (SOM) analysis to identify characteristic spatial and temporal …
using self-organizing map (SOM) analysis to identify characteristic spatial and temporal …
Attribution and predictability of climate‐driven variability in global ocean color
For over two decades, satellite ocean color missions have revealed spatio‐temporal
variations in marine chlorophyll. Seasonal cycles and interannual changes of the physical …
variations in marine chlorophyll. Seasonal cycles and interannual changes of the physical …
Decreasing surface chlorophyll in the tropical ocean as an indicator of anthropogenic greenhouse effect during 1998–2020
F Tian, RH Zhang - Environmental Research Letters, 2023 - iopscience.iop.org
Available satellite data reveal a decreasing trend in surface chlorophyll (SChl) over the
entire tropical ocean until 2020. Where contributions by internal variability and external …
entire tropical ocean until 2020. Where contributions by internal variability and external …
A Multi-Mode Convolutional Neural Network to reconstruct satellite-derived chlorophyll-a time series in the global ocean from physical drivers
Time series of satellite-derived chlorophyll-a concentration (Chl, a proxy of phytoplankton
biomass), continuously generated since 1997, are still too short to investigate the low …
biomass), continuously generated since 1997, are still too short to investigate the low …