• JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
 
  Bookmark and Share
 
 
Master's Dissertation
DOI
https://doi.org/10.11606/D.21.2020.tde-31032020-113434
Document
Author
Full name
Thais Marina Fernandes
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2019
Supervisor
Committee
Sato, Olga Tiemi (President)
Oliveira, Eduardo Negri de
Souza, Ronald Buss de
Title in Portuguese
Detecção da água modal subtropical do Atlântico Sul através de dados de satélite
Keywords in Portuguese
Água modal
água modal subtropical do Atlântico Sul
altímetro
Abstract in Portuguese
Águas modais são fenômenos oceânicos caracterizadas por camadas com propriedades praticamente homogêneas, observado através de baixos valores de vorticidade potencial (VP). Para o estudo de regiões com formação de Água Modal Subtropical do Atlântico Sul (AMSTAS) utilizamos os conjuntos de dados de perfiladores Argo, de temperatura da superfície do mar (TSM) de satélite do projeto Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) e altura da superfície do mar (ASM) e anomalia da superfície do mar (AASM) de altímetro do serviço Copernicus Marine Environment Monitoring Service (CMEMS), entre 2002 e 2017, na região compreendida na faixa de 25°S a 45°S. Sobre dados Argo, utilizamos a metodologia de Sato e Polito, 2014 para determinar perfis com água modal, utilizando critérios de temperatura potencial (13°C - 17°C), salinidade (35 - 36), VP (< 1.5x10-10m-1.s-1) e gradiente vertical de temperatura menores do que (dT\dz =0,015°C.m-1). Em seguida, determinamos ASM Argo, utilizando as rotinas GSW (The Gibbs-SeaWater Oceanography), do projeto TEOS-10. Os dados de TSM OSTIA foram selecionados a partir de pontos e datas Argo, respeitando o raio de busca de 0,03°. Já os dados de altímetro, foram selecionados da mesma maneira, mas seguindo o raio de busca 0,13°. Analisamos os dados de TSM Argo e OSTIA encontramos que, uma correlação fraca entre os dados e o coeficiente de determinação baixo, sugerindo que a escola do modelo linear para representar a relação entre os conjuntos de dados, não foi. Para os dados de ASM Argo encontramos séries com baixa variabilidade, onde podemos ver a formação e o afundamento dos perfis com água modal. Além disso, encontramos ciclo estáveis mostrando o aumento de ASM no verão e diminuição no inverno. Esses resultados se repetem quando utilizamos a AASM também. Esses resultados não se repetem para os dados sem água modal. Já para os dados de AASM do altímetro, se comparar os dados totais (com e sem água modal), notamos que nos meses de formação, o que prevalece é o sinal da AASM da água modal, mostrando que, mesmo quando temos dados de AASM de satélite para a região total, no período de formação, o sinal da água modal é o que prevalece. Ou seja, durante os meses de formação, podemos detectar o sinal de AASM da água modal, utilizando altímetros.
Title in English
Detection of subtropical modal water of the South Atlantic, through satellite data
Keywords in English
altimeter
Modal water
South Atlantic subtropical modal water
Abstract in English
Mode water is an oceanic phenomena which is characterized by nearly homogeneous properties in its layers. This peculiarity can be observed throughout low vertical temperature and salinity gradients, and shallow values of potential vorticity (PV). Thus, to study the regions of the South Atlantic Subtropical Mode Water (SASMW) formation, Argo profilers data sets were used. Satellite data of Sea Surface Temperature (SST) from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) were adopted, whilst the Sea Surface Height (SSH) and Anomaly Sea Surface Height (ASSH) data set were taken from the altimeter of teh service Copernicus Marine Environment Monitoring Service(CMEMS), which controls all the data set, between 2002 and 2017, within the range of 25°S a 45°S for the South Atlantic region. For the Argo inputs, Sato and Polito, 2014, methodology were applied to determine the modal water profiles, where the criteria as potential temperature 13°C -17°C, salinity (35 - 36), potential vorticity (< 1.5x10-10m-1.s-1) and vertical temperature gradient < 0,015 °C m-1 were used. Furthermore, for Argo data, dynamic height was generated through the GSW (The Gibbs Sea Water Oceanography) routines, from the Thermodynamic Equation of Seawater (TEOS-10) project. The SST OSTIA data were selected from Argo dates and points, taking into account the radius search of 0,03°. Additionally, the altimeter data was obtained with the same method, but with the radius search of 0,13°. We analyzed the SST Argo and OSTIA data and found that a weak correlation between the data and the low coefficient of determination, suggesting that the linear model school to represent the relationship between data sets was not. For ASM Argo data we find series with low variability, where we can see the formation and sinking of the profiles with modal water. In addition, we found stable cycle showing the increase in ASM in summer and decrease in winter. These results are repeated when we use ASSM as well. These results are not repeated for data without modal water. For the altimeter ASSH data, if we compare the total data (with and without modal water), we note that in the months of formation, what prevails is the ASSH signal of modal water, showing that even when we have data from ASSH of satellite to the total region, during the formation period, the modal water signal is what prevails.
 
WARNING - Viewing this document is conditioned on your acceptance of the following terms of use:
This document is only for private use for research and teaching activities. Reproduction for commercial use is forbidden. This rights cover the whole data about this document as well as its contents. Any uses or copies of this document in whole or in part must include the author's name.
Publishing Date
2020-04-02
 
WARNING: Learn what derived works are clicking here.
All rights of the thesis/dissertation are from the authors
CeTI-SC/STI
Digital Library of Theses and Dissertations of USP. Copyright © 2001-2020. All rights reserved.