Restoration of Sea Surface Temperature Satellite Images Using a Partially Occluded Training Set

2018 ◽  
Author(s):  
Satoki Shibata ◽  
Masaaki Iiyama ◽  
Atsushi Hashimoto ◽  
Michihiko Minoh
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Images ◽  
Sea Surface ◽  
Training Set ◽  
Partially Occluded

scholarly journals CO2 flux behavior in the maritorium of San Andres Islands on 2019

Respuestas ◽  
2020 ◽  
Vol 25 (3) ◽  
Author(s):  
Juan Guillermo Popayán-Hernández ◽  
Orlando Zúñiga-Escobar
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Images ◽  
Co2 Flux ◽  
Sea Surface ◽  
Remote Sensors ◽  
Partial Pressures ◽  
Thermodynamic Relationship ◽  
San Andres

This document estimated the behavior of the CO2 flux in the San Andrés Islas maritime for the first half of 2019. This behavior was established based on the thermodynamic relationship between the sea surface temperature, the partial pressures of CO2 in the atmosphere and the water column, this from data derived from remote sensors. The satellite data were derived from the MODIS aqua sensors and the MERRA model for sea surface temperature and wind speed respectively. Satellite images were obtained from NASA databases, subsequently processed and specialized in ArcGis 10.1. Finally, the behavior of the CO2 flux is shown for the San Andrés Islas maritime, finding that it does not have a tendency to capture CO2, so acidification processes are discarded for the selected study period.

Computing advective velocities from satellite images of sea surface temperature

1992 ◽  
Vol 30 (1) ◽  
pp. 166-176 ◽  
Author(s):  
Q.X. Wu ◽  
D. Pairman ◽  
S.J. McNeill ◽  
E.J. Barnes
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Images ◽  
Sea Surface

scholarly journals Sensitivity to species selection indicates the effect of nuisance variables on marine microfossil transfer functions

2018 ◽  
Author(s):  
Lukas Jonkers ◽  
Michal Kučera
Keyword(s):  
Transfer Function ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Transfer Functions ◽  
Planktonic Foraminifera ◽  
Sea Surface ◽  
Species Selection ◽  
Training Set ◽  
Function Models ◽  
Transfer Function Models

Abstract. The species composition of many groups of marine plankton appears well predicted by sea surface temperature (SST). Consequently, fossil plankton assemblages have been widely used to reconstruct past SST. Most applications of this approach make use of the highest possible taxonomic resolution. However, not all species are sensitive to temperature and their distribution may be governed by other parameters. There are thus reasons to question the merit of including information all species, both for transfer function performance and for its effect on reconstructions. Here we investigate the effect of species selection on planktonic foraminifera transfer functions. We assess species importance for transfer function models using a random forest technique and evaluate the performance of models with increasing number of species. Irrespective of using models that use the entire training set (weighted averaging) or models that use only a subset of the training set (modern analogue technique), we find that the majority of foraminifera species does not carry useful information for temperature reconstruction. Less than one third of the species in the training set is required to provide a temperature estimate with a prediction error comparable to a transfer function that uses all species in the training set. However, species selection matters for paleotemperature estimates. We find that transfer function models with different number of species but with the same error may yield different reconstructions of sea surface temperature when applied on the same fossil assemblages. This ambiguity in the reconstructions implies that fossil assemblage change reflects a combination of temperature and other environmental factors. The contribution of the additional factors is site and time specific, indicating ecological and geological complexity in the formation of the sedimentary assemblages. The possibility of obtaining multiple different reconstructions from a single sediment record presents a previously unrecognised source of uncertainty for sea surface temperature estimates based on planktonic foraminifera assemblages. This uncertainty can be evaluated by determining the sensitivity of the reconstructions to species pruning.

scholarly journals Optimization of Sea Surface Current Retrieval Using a Maximum Cross-Correlation Technique on Modeled Sea Surface Temperature

2017 ◽  
Vol 34 (10) ◽  
pp. 2245-2255 ◽  
Author(s):  
Céline Heuzé ◽  
Gisela K. Carvajal ◽  
Leif E. B. Eriksson
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Western Europe ◽  
Satellite Images ◽  
Cross Correlation ◽  
Surface Current ◽  
Sea Surface ◽  
Time Interval ◽  
Correlation Technique ◽  
Ocean Surface Current

AbstractUsing sea surface temperature from satellite images to retrieve sea surface currents is not a new idea, but so far its operational near-real-time implementation has not been possible. Validation studies are too region specific or uncertain, sometimes because of the satellite images themselves. Moreover, the sensitivity of the most common retrieval method, the maximum cross correlation, to the parameters that have to be set is unknown. Using model outputs instead of satellite images, biases induced by this method are assessed here, for four different seas of western Europe, and the best of nine settings and eight temporal resolutions are determined. The regions with strong currents return the most accurate results when tracking a 20-km pattern between two images separated by 6–9 h. The regions with weak currents favor a smaller pattern and a shorter time interval, although their main problem is not inaccurate results but missing results: where the velocity is too low to be picked by the retrieval. The results are not impaired by the restrictions imposed by ocean surface current dynamics and available satellite technology, indicating that automated sea surface current retrieval from sea surface temperature images is feasible, for pollution confinement, search and rescue, and even for more energy-efficient and comfortable ship navigation.

Sign in / Sign up

Export Citation Format

Share Document