Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Oliveira, Marilia Mitidieri Fernandes de; Pereira, G. C.; Oliveira, Jorge; Ebecken, Nelson F. F.

doi:10.1007/s10661-011-2470-3

Cited by 3 publications

(8 citation statements)

References 28 publications

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“…This study is a continuity of the research developed by the Federal University of Rio de Janeiro (COPPE/ UFRJ)-Civil Engineering Program in remote monitoring systems of environmental impacts in coastal regions in order to develop trophic dynamic models to be used in the National Plan and Regional Coastal Management or in any other aquatic system. Biological and chemical distribution and meteo-oceanography patterns have been verified by [21].…”

mentioning

confidence: 87%

Multivariate Analysis of Extreme Physical, Biological and Chemical Patterns in the Dynamics of Aquatic Ecosystem

Oliveira¹,

Pereira²,

Ebecken³

et al. 2015

JEP

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This study is a part of the research in monitoring systems of environmental impacts in coastal regions in order to develop trophic dynamic models to be used in the aquatic systems management. Meteorological influences in the variability of the nutrients, larvae concentration, dissolved oxygen (DO) and chlorophyll a were investigated in a region where upwelling occurs. Extreme seasonal variations of reanalysis, QuikSCAT, and surface stations from the southeast coast of Brazil, as well as, surface seawater data collected in Anjos Bay, Arraial do Cabo city northeast of Rio de Janeiro state, are analyzed. Seasonality and correlations are applied to verify the relationship between them, considering minimum values of sea surface temperature (SST) and sea level variation and maximum values of the other variables. Principal Component Analysis (PCA) and Hierarquical Cluster Analysis (HCA) are applied to verify spatial and temporal variances and to describe more clearly the structure of the local ecosystem. The seasonality of northeasterly extreme wind stress follows the seasonal pattern expected for the study area with peaks during spring. The SST has a well-defined seasonal pattern with maximum peaks from February to July and minimum peaks from September to January. Chlorophyll a presents higher seasonal peak in February, being in accordance with DO; both are related to the maximum primary productivity. Correlations of the physical variables (local and remote) with nutrients and larvae present a relatively similar pattern around 0.5, showing these variables have a reasonable interaction with the meteorological forcing. PCA shows a strong variability in pressure data around 0.9, which may be related to the seasonal variations in South Atlantic subtropical anticyclone (SASA) and consequently to the occurrence of upwelling in the region. HCA shows the twenty-five parameters into two big clusters * Corresponding author.M. M. F. de Oliveira et al. 886with predominance of biotic variables in one side and abiotic ones at the other. The degree of refinement of similarities allowed a division into six clusters of samples, giving the most satisfactory results at forming distinct clusters with more accurate regarding physical and biological elements.

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mentioning

confidence: 87%

Multivariate Analysis of Extreme Physical, Biological and Chemical Patterns in the Dynamics of Aquatic Ecosystem

Oliveira¹,

Pereira²,

Ebecken³

et al. 2015

JEP

View full text Add to dashboard Cite

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“…This study is part of the research developed by the Federal University of Rio de Janeiro-Civil Engineering Program in remote monitoring systems of environmental impacts in coastal regions in order to develop trophic dynamic models to be used in the National Plan and Regional Coastal Management or in any other aquatic system. To continue the study of biological and chemical distribution and meteo-oceanography patterns [16], we have also verified the relations between them and tidal influence in the Arraial do Cabo region. This place is known for its active wind induced shelf upwelling [17].…”

Section: Introductionmentioning

confidence: 92%

“…In order to investigate the sea level dynamic in Arraial do Cabo and its influence in the variability of the studied variables, we verified the spatial and temporal meteorological systems related to the sea level variations. This research is a continuity of [16], in which we used the same study area with the local points from satellite data, surface weather station, tide gauge station and sample water harvest in Anjos Bay.…”

Section: Study Areamentioning

confidence: 99%

“…This study area is under influence by the South Atlan-The mean surface circulation of the South Atlantic (Adapted from [16]). Ocean is dominated by a closed system known as the South Atlantic subtropical gyre that is composed of several ocean currents and on the western boundary of this gyre it has the Brazil Current (BC) [22].…”

Section: Study Areamentioning

confidence: 99%

“…The Coastal Water (CW) has the thermohaline characteristics varying according to the annual cycle of river runoff and mixture with offshore waters [33]. The Environment National Council (CONAMA) Resolution 357/2005 that provides the classification of water bodies and environmental guidelines for its framework determines limits for the levels of several chemicals components, including nitrogenous nutrients [16]. We have used temperature and salinity data provided by the Admiral Paulo Moreira Institute of Sea Studies-IEAPM and the water mass thermohaline indices are presented in Table 1.…”

Section: Water Masses In the Southeastern Brazilian Shelfmentioning

confidence: 99%

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Effects of Sea Level Variation on Biological and Chemical Concentrations in a Coastal Upwelling Ecosystem

Oliveira¹,

Pereira²,

Oliveira³

et al. 2013

JEP

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Oscillations in sea level due to meteorological forces related to wind and pressure affect the regular tides and modify the sea level conditions, mainly in restricted waters such as bays. Investigations surrounding these variations and the biological and chemical response are important for monitoring coastal regions mainly where upwelling shelf systems occur. A spatial and temporal database from Quick Scatterometer satellite vector wind, surface stations from the Southeast coast of Brazil and surface seawater data collected in Anjos Bay, Arraial do Cabo city, northeast of Rio de Janeiro State were used to investigate the meteorological influences in the variability of the dissolved oxygen, nutrients, meroplankton larvae and chlorophyll-a concentrations. Multivariate statistical approaches such as Principal Component Analysis (PCA) and Clustering Analysis (CA) were applied to verify spatial and temporal variances. A correlation matrix was also verified for different water masses in order to identify the relationship between the above parameters. A seasonal variability of the meteorological residual presents a well-defined pattern with maximum peaks in autumn/winter and minimum during spring/summer with negative values, period of occurrence of upwelling in this region. This lowering of the sea level is in accordance with the increasing of nutrients and meroplankton larvae for the same period. CA showed six groups and an importance of the zonal and meridional wind variability, including these variables in a single cluster. PCA retained eight components, explaining 64.10% of the total variance of data set. Some clusters and loadings have the same variables, showing the importance of the sea-air interaction.

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Extreme climatic characteristics near the coastline of the southeast region of Brazil in the last 40 years

Oliveira

Fernandes

et al. 2021

Theor Appl Climatol

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The southeastern Brazilian coast is a vulnerable region to the development of severe storms, mainly caused by the passage of cold fronts and extratropical cyclones. In the last decades, there has been an increase in the occurrence of subtropical cyclones. This study investigates trends and climatic variations, analyzing surface meteoceanographic series at six grid points from the reanalysis databases of ERA-Interim and ERA5 (European Center for Medium-Range Weather Forecasts-ECMWF) from 1979 to 2018 over the ocean region bounded, approximately, at 18°S, 25°S and 37ºW, 45ºW (between the states of Espírito Santo, Rio de Janeiro and São Paulo). Non-parametric statistical tests and the generalized extreme value distribution are employed for annual, seasonal and daily maxima/minima. The numbers of occurrence of extreme values, as well as the extremal index are also estimated in order to better understand the behavior of extremes. Annual maximum sea-surface temperature anomalies of the ERA-Interim databases show very low negative values, mainly at the beginning of measurements (between 1979 and 1982), leading to high positive trend values. The results are compared to the updated data from ERA5 which have anomalies that are more homogeneous with positive trends but without statistical significance. The other meteorological series of the ERA-Interim does not present discrepancies. Only the maximum anomalies of air temperature have significant annual and seasonal positive trends at grid points near the coast of Rio de Janeiro and São Paulo. Despite that the analyses for pressure and wind speed anomalies do not indicate significant trends, they present increases in the interdecadal pattern of the numbers of occurrence of extreme percentiles for almost every grid point. Return levels for 10, 25, 50, 75, and 100 years are estimated at each grid point and many maximum/minimum peaks are close to the return levels for 100-year return periods. The extremal index suggests average cluster sizes associated with no predominance of clustering for the extreme percentiles, which represents weak dependence between the exceedances. These results characterize some independence between extreme meteorological events such as the event that has been taking place in the region. The occurrence of maximum daily wind speed peaks calculated in austral spring, whose values exceeded the previous ones, is identified at three grid points near the southeast Brazilian coast, caused by the passage of the subtropical cyclone "Deni," which occurred in November 2016.

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Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Cited by 3 publications

References 28 publications

Multivariate Analysis of Extreme Physical, Biological and Chemical Patterns in the Dynamics of Aquatic Ecosystem

Multivariate Analysis of Extreme Physical, Biological and Chemical Patterns in the Dynamics of Aquatic Ecosystem

Effects of Sea Level Variation on Biological and Chemical Concentrations in a Coastal Upwelling Ecosystem

Extreme climatic characteristics near the coastline of the southeast region of Brazil in the last 40 years

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