Towards the estimation of DOC from space in the open ocean

2020 ◽  
Author(s):  
Ana Gabriela Bonelli ◽  
Hubert Loisel ◽  
Vincent Vantrepotte ◽  
Daniel Jorge ◽  
Antoine Mangin ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Temporal Dynamics ◽  
Open Ocean ◽  
Colored Dissolved Organic Matter ◽  
Ocean Water ◽  
Chl A ◽  
First Results ◽  
Spatio Temporal ◽  
Input Variables ◽  
Global Carbon

<p>The Dissolved Organic Carbon (DOC) represents the largest pool of organic carbon and the most active carbon compartment in the ocean. Describing the spatio-temporal dynamics of the oceanic DOC in response to variation in the physical of biological forcings is therefore crucial for better understanding the global carbon cycle. The DOC distribution and its temporal dynamics is however currently not well known.</p><p>In the recent years several works have demonstrated the possibility to assess from space the DOC distribution in the coastal ocean thanks to direct relationships between DOC and the optical properties of colored dissolved organic matter (CDOM). Such CDOM-DOC relationships are not applicable for the open ocean water due making more complex the DOC estimation from space in the latter environments. Here we present first results documenting an alternative method for estimating DOC from satellite imagery which rely on the use of a neural network which combines different physical and biogeochemical input variables (SST, SSS, PAR, aCDOM and Chl-a).</p>

scholarly journals Interannual variability of alongshore spring bloom dynamics in a coastal sea caused by the differential influence of hydrodynamics and light climate

2010 ◽  
Vol 7 (1) ◽  
pp. 371-386 ◽  
Author(s):  
G. Brandt ◽  
K. W. Wirtz
Keyword(s):  
Spring Bloom ◽  
Temporal Dynamics ◽  
Physical Factors ◽  
Light Climate ◽  
Measuring Device ◽  
Chl A ◽  
Southern Bight ◽  
Coastal Sea ◽  
Tracking Model ◽  
Spatio Temporal

Abstract. Timing and spatial distribution of phytoplankton blooms in coastal oceans are highly variable. The interactions of various biological and physical factors leading to the observed variability are complex and remain poorly understood. We present an example for distinct differences in the spatio-temporal chlorophyll a (CHL-a) distribution on an interannual scale, integrating high-frequency data from an autonomous measuring device (FerryBox), which operated on an alongshore route in the coastal German Bight (North Sea). While in one year the distribution of CHL-a was spatially homogeneous (2004), a bloom only developed in one part of the transect in the following spring period (2005). We use a one-dimensional Lagrangian particle tracking model, which operates along the mean current direction, combined with a NPZ-model to identify the mechanisms controlling the observed interannual bloom variability on the alongshore transect. Our results clearly indicate that in 2004 the local light climate determined the spatial and temporal dynamics of the spring bloom. In contrast, the import of a water mass with elevated CHL-a concentrations from the adjacent Southern Bight triggered the spring bloom in 2005. The inflow event did, however, not last long enough to spread the bloom into the eastern part of the study area, where high turbidity prevented local phytoplankton growth. The model identifies two interacting mechanisms, light climate and hydrodynamics, that controlled the alongshore dynamics. Especially the occurrence of a pronounced spring bloom despite unfavourable light conditions in 2005 underlines the need to carefully consider hydrodynamics to understand the dynamics of the plankton community in coastal environments.

scholarly journals Seasonal variations in concentration and composition of dissolved organic carbon in Tokyo Bay

2014 ◽  
Vol 11 (7) ◽  
pp. 10203-10228 ◽  
Author(s):  
A. Kubo ◽  
M. Yamamoto-Kawai ◽  
J. Kanda
Keyword(s):  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
River Water ◽  
Seasonal Variations ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Open Ocean ◽  
Tokyo Bay ◽  
Chl A

Abstract. Concentrations of recalcitrant and bioavailable dissolved organic carbon (DOC) and their seasonal variations were investigated at three stations in Tokyo Bay, Japan, and in two freshwater sources flowing into the bay to evaluate the significance of DOC degradation for the carbon budget in coastal waters and carbon export to the open ocean. Recalcitrant DOC (RDOC) was differentiated from bioavailable DOC (BDOC) as a remnant of DOC after 150 days of bottle incubation. On average, RDOC accounted for 78% of the total DOC in Shibaura sewage treatment plant (STP) effluent, 67% in the upper Arakawa River water, 66% in the lower Arakawa River water, and 78% in surface bay water. RDOC concentrations were higher than BDOC at all stations. In freshwater environments, RDOC concentrations were almost constant throughout the year. In the bay, RDOC was higher during spring and summer than during autumn and winter. The relative abundance of RDOC in the bay derived from phytoplankton, terrestrial, and open oceanic waters was estimated to be 9%, 33%, and 58%, respectively, by multiple regression analysis of RDOC, salinity, and chl a. In addition, comparison with previous data from 1972 revealed that concentrations of RDOC and BDOC have decreased by 33% and 74% at freshwater sites and 39% and 76% at Tokyo Bay, while the ratio of RDOC to DOC has increased. The change in DOC concentration and composition was probably due to increased amounts of sewage treatment plant effluent entering the system. Tokyo Bay exported DOC, mostly RDOC, to the open ocean because of remineralization of BDOC.

scholarly journals Technical Note: Cost-efficient approaches to measure carbon dioxide (CO<sub>2</sub>) fluxes and concentrations in terrestrial and aquatic environments using mini loggers

2015 ◽  
Vol 12 (3) ◽  
pp. 2357-2380 ◽  
Author(s):  
D. Bastviken ◽  
I. Sundgren ◽  
S. Natchimuthu ◽  
H. Reyier ◽  
M. Gålfalk
Keyword(s):  
Temporal Dynamics ◽  
Co2 Flux ◽  
Technical Note ◽  
Aquatic Environments ◽  
Co2 Fluxes ◽  
Stream Network ◽  
Co2 Concentrations ◽  
Direct Measurements ◽  
Spatio Temporal ◽  
Global Carbon

Abstract. Fluxes of CO2 are important for our understanding of the global carbon cycle and greenhouse gas balances. Several significant CO2 fluxes in nature may still be neglected as illustrated by recent findings of high CO2 emissions from aquatic environments, previously not recognized in global carbon balances. Therefore it is important to develop convenient and affordable ways to measure CO2 in many types of environments. At present, direct measurements of CO2 fluxes from soils or waters, or CO2 concentrations in surface water, are typically labour intensive or require costly equipment. We here present an approach with measurement units based on small inexpensive CO2 loggers, originally made for indoor air quality monitoring, that were tested and adapted for field use. Measurements of soil–atmosphere and lake–atmosphere fluxes, as well as of spatio-temporal dynamics of water CO2 concentrations (expressed as the equivalent partial pressure, pCO2aq) in lakes and a stream network are provided as examples. Results from all these examples indicate that this approach can provide a cost- and labor efficient alternative for direct measurements and monitoring of CO2 flux and pCO2aq in terrestrial and aquatic environments.

scholarly journals Intelligent Drought Tracking for its Use in Machine Learning: Implementation and First Results

10.29007/klgg ◽  
2018 ◽  
Author(s):  
Vitali Diaz ◽  
Gerald A. Corzo Perez ◽  
Henny A.J. Van Lanen ◽  
Dimitri Solomatine
Keyword(s):  
Machine Learning ◽  
Temporal Dynamics ◽  
Temporal Analysis ◽  
Drought Monitoring ◽  
Grid Data ◽  
Drought Prediction ◽  
Documented Information ◽  
First Results ◽  
Spatio Temporal ◽  
Over Time

Due to the underlying characteristics of drought, monitoring of its spatio-temporal development is difficult. Last decades, drought monitoring have been increasingly developed, however, including its spatio-temporal dynamics is still a challenge. This study proposes a method to monitor drought by tracking its spatial extent. A methodology to build drought trajectories is introduced, which is put in the framework of machine learning (ML) for drought prediction. Steps for trajectories calculation are (1) spatial areas computation, (2) centroids localization, and (3) centroids linkage. The spatio- temporal analysis performed here follows the Contiguous Drought Area (CDA) analysis. The methodology is illustrated using grid data from the Standardized Precipitation Evaporation Index (SPEI) Global Drought Monitor over India (1901-2013), as an example. Results show regions where drought with considerable coverage tend to occur, and suggest possible concurrent routes. Tracks of six of the most severe reported droughts were analysed. In all of them, areas overlap considerably over time, which suggest that drought remains in the same region for a period of time. Years with the largest drought areas were 2000 and 2002, which coincide with documented information presented. Further research is under development to setup the ML model to predict the track of drought.

Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: implications for ecosystem-based fisheries management

2020 ◽  
Vol 637 ◽  
pp. 117-140 ◽  
Author(s):  
DW McGowan ◽  
ED Goldstein ◽  
ML Arimitsu ◽  
AL Deary ◽  
O Ormseth ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Gulf Of Alaska ◽  
Data Series ◽  
Limited Information ◽  
Important Species ◽  
Multiple Data ◽  
Spatial And Temporal Dynamics ◽  
Spawning Areas ◽  
Spatio Temporal

Pacific capelin Mallotus catervarius are planktivorous small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, limited information is available on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affect their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially indexed data from multiple independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicate that the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.

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