scholarly journals Spatio-temporal behaviour of the deep chlorophyll maximum in Mediterranean Sea: Development of a stochastic model for picophytoplankton dynamics

2013 ◽  
Vol 13 ◽  
pp. 21-34 ◽  
Author(s):  
G. Denaro ◽  
D. Valenti ◽  
A. La Cognata ◽  
B. Spagnolo ◽  
A. Bonanno ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Mediterranean Sea ◽  
Deep Chlorophyll Maximum ◽  
Temporal Behaviour ◽  
Chlorophyll Maximum ◽  
Spatio Temporal

scholarly journals Deep chlorophyll maximum and nutricline in the Mediterranean Sea: emerging properties from a multi-platform assimilated biogeochemical model experiment

2021 ◽  
Author(s):  
Anna Teruzzi ◽  
Giorgio Bolzon ◽  
Laura Feudale ◽  
Gianpiero Cossarini
Keyword(s):  
Mediterranean Sea ◽  
Satellite Data ◽  
Positive Impact ◽  
Model Simulation ◽  
Eastern Mediterranean ◽  
Western Mediterranean ◽  
Biogeochemical Model ◽  
Deep Chlorophyll Maximum ◽  
Argo Data ◽  
Chlorophyll Maximum

Abstract. Data assimilation has had a positive impact on biogeochemical modelling in a number of oceanographic applications. The recent operational availability of data from BGC-Argo floats, which provide valuable insights into key vertical biogeochemical processes, can lead to further improvements in biogeochemical modelling through assimilation schemes that include float observations in addition to traditionally assimilated satellite data. In the present work, we demonstrate the feasibility of joint multi-platform assimilation in realistic biogeochemical applications by presenting the results of one-year simulations of Mediterranean Sea biogeochemistry. Different combinations of satellite chlorophyll data and BGC-Argo nitrate and chlorophyll data have been tested, and validation with respect to available independent and semi-independent (before assimilation) observations showed that assimilation of both satellite and float observations outperformed the assimilation of platforms considered individually. Moreover, the assimilation of BGC-Argo data impacted the vertical structure of nutrients and phytoplankton in terms of deep chlorophyll maximum depth and intensity and nutricline depth. The outcomes of the model simulation assimilating both satellite data and BGC-Argo data have been used to explore the basin-wide differences in vertical features associated with summer stratified conditions, describing a relatively high variability between the western and eastern Mediterranean, with thinner and shallower but intense deep chlorophyll maxima associated with steeper and narrower nutriclines in the western Mediterranean.

scholarly journals Deep chlorophyll maximum and nutricline in the Mediterranean Sea: emerging properties from a multi-platform assimilated biogeochemical model experiment

2021 ◽  
Vol 18 (23) ◽  
pp. 6147-6166
Author(s):  
Anna Teruzzi ◽  
Giorgio Bolzon ◽  
Laura Feudale ◽  
Gianpiero Cossarini
Keyword(s):  
Mediterranean Sea ◽  
Satellite Data ◽  
Model Simulation ◽  
Eastern Mediterranean ◽  
Western Mediterranean ◽  
Biogeochemical Model ◽  
Deep Chlorophyll Maximum ◽  
Argo Data ◽  
Chlorophyll Maximum ◽  
Consistent Picture

Abstract. Data assimilation has led to advancements in biogeochemical modelling and scientific understanding of the ocean. The recent operational availability of data from BGC-Argo (biogeochemical Argo) floats, which provide valuable insights into key vertical biogeochemical processes, stands to further improve biogeochemical modelling through assimilation schemes that include float observations in addition to traditionally assimilated satellite data. In the present work, we demonstrate the feasibility of joint multi-platform assimilation in realistic biogeochemical applications by presenting the results of 1-year simulations of Mediterranean Sea biogeochemistry. Different combinations of satellite chlorophyll data and BGC-Argo nitrate and chlorophyll data have been tested, and validation with respect to available independent non-assimilated and assimilated (before the assimilation) observations showed that assimilation of both satellite and float observations outperformed the assimilation of platforms considered individually. Moreover, the assimilation of BGC-Argo data impacted the vertical structure of nutrients and phytoplankton in terms of deep chlorophyll maximum depth, intensity, and nutricline depth. The outcomes of the model simulation assimilating both satellite data and BGC-Argo data provide a consistent picture of the basin-wide differences in vertical features associated with summer stratified conditions, describing a relatively high variability between the western and eastern Mediterranean, with thinner and shallower but intense deep chlorophyll maxima associated with steeper and narrower nutriclines in the western Mediterranean.

scholarly journals Dynamics of Two Picophytoplankton Groups in Mediterranean Sea: Analysis of the Deep Chlorophyll Maximum by a Stochastic Advection-Reaction-Diffusion Model

PLoS ONE ◽  
2013 ◽  
Vol 8 (6) ◽  
pp. e66765 ◽  
Author(s):  
Giovanni Denaro ◽  
Davide Valenti ◽  
Bernardo Spagnolo ◽  
Gualtiero Basilone ◽  
Salvatore Mazzola ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Diffusion Model ◽  
Reaction Diffusion ◽  
Deep Chlorophyll Maximum ◽  
Chlorophyll Maximum ◽  
Reaction Diffusion Model

A Stochastic Model for the Inheritance of the Cancer Proneness Phenotype

1987 ◽  
Vol 26 (03) ◽  
pp. 117-123
Author(s):  
P. Tautu ◽  
G. Wagner
Keyword(s):  
Stochastic Model ◽  
Gaussian Process ◽  
Covariance Function ◽  
Neoplastic Disease ◽  
Disease Phenotype ◽  
Probabilistic Representation ◽  
Temporal Behaviour ◽  
Continuous Trait ◽  
Continuous Parameter ◽  
Level Zero

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.

Deep chlorophyll maximum (DCM) in the Red Sea

2021 ◽  
Vol 14 (3) ◽  
Author(s):  
Mohideen Wafar ◽  
Mohammad Ali Qurban ◽  
Zahid Nazeer ◽  
Karuppusamy Manikandan
Keyword(s):  
Red Sea ◽  
Deep Chlorophyll Maximum ◽  
Chlorophyll Maximum
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