Parameter estimation in a three-dimensional marine ecosystem model using the adjoint technique

2008 ◽  
Vol 74 (1-2) ◽  
pp. 443-452 ◽  
Author(s):  
Qiang Zhao ◽  
Xianqing Lu
Keyword(s):  
Parameter Estimation ◽  
Marine Ecosystem ◽  
Three Dimensional ◽  
Ecosystem Model ◽  
Marine Ecosystem Model

scholarly journals Ecological ReGional Ocean Model with vertically resolved sediments (ERGOM SED 1.0): coupling benthic and pelagic biogeochemistry of the south-western Baltic Sea

2019 ◽  
Vol 12 (1) ◽  
pp. 275-320 ◽  
Author(s):  
Hagen Radtke ◽  
Marko Lipka ◽  
Dennis Bunke ◽  
Claudia Morys ◽  
Jana Woelfel ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Marine Ecosystem ◽  
Nutrient Recycling ◽  
Three Dimensional ◽  
Ecosystem Model ◽  
Ocean Model ◽  
Ecosystem Models ◽  
Predictive Capacity ◽  
Sediment Types ◽  
Marine Ecosystem Model

Abstract. Sediments play an important role in organic matter mineralisation and nutrient recycling, especially in shallow marine systems. Marine ecosystem models, however, often only include a coarse representation of processes beneath the sea floor. While these parameterisations may give a reasonable description of the present ecosystem state, they lack predictive capacity for possible future changes, which can only be obtained from mechanistic modelling. This paper describes an integrated benthic–pelagic ecosystem model developed for the German Exclusive Economic Zone (EEZ) in the western Baltic Sea. The model is a hybrid of two existing models: the pelagic part of the marine ecosystem model ERGOM and an early diagenetic model by Reed et al. (2011). The latter one was extended to include the carbon cycle, a determination of precipitation and dissolution reactions which accounts for salinity differences, an explicit description of the adsorption of clay minerals, and an alternative pyrite formation pathway. We present a one-dimensional application of the model to seven sites with different sediment types. The model was calibrated with observed pore water profiles and validated with results of sediment composition, bioturbation rates and bentho-pelagic fluxes gathered by in situ incubations of sediments (benthic chambers). The model results generally give a reasonable fit to the observations, even if some deviations are observed, e.g. an overestimation of sulfide concentrations in the sandy sediments. We therefore consider it a good first step towards a three-dimensional representation of sedimentary processes in coupled pelagic–benthic ecosystem models of the Baltic Sea.

scholarly journals An Ensemble Kalman Filter with a complex marine ecosystem model: hindcasting phytoplankton in the Cretan Sea

2003 ◽  
Vol 21 (1) ◽  
pp. 399-411 ◽  
Author(s):  
J. I. Allen ◽  
M. Eknes ◽  
G. Evensen
Keyword(s):  
Data Assimilation ◽  
Marine Ecosystem ◽  
Three Dimensional ◽  
Ecosystem Model ◽  
Sequential Data ◽  
Model Errors ◽  
In Situ Data ◽  
Marine Ecosystem Model ◽  
Cretan Sea

Abstract. The purpose of this paper is to examine the use of a complex ecosystem model along with near real-time in situ data and a sequential data assimilation method for state estimation. The ecosystem model used is the European Regional Seas Ecosystem Model (ERSEM; Baretta et al., 1995) and the assimilation method chosen is the Ensemble Kalman Filer (EnKF). Previously, it has been shown that this method captures the nonlinear error evolution in time and is capable of both tracking the observations and providing realistic error estimates for the estimated state. This system has been used to assimilate long time series of in situ chlorophyll taken from a data buoy in the Cretan Sea. The assimilation of this data using the EnKF method results in a marked improvement in the ability of ERSEM to hindcast chlorophyll. The sensitivity of this system to the type of data used for assimilation, the frequency of assimilation, ensemble size and model errors is discussed. The predictability window of the EnKF appears to be at least 2 days. This is an indication that the methodology might be suitable for future operational data assimilation systems using more complex three-dimensional models. Key words. Oceanography: general (numerical modelling; ocean prediction) – Oceanography: biological and chemical (plankton)

scholarly journals Skillful prediction of tropical Pacific fisheries provided by Atlantic Niños

2021 ◽  
Author(s):  
Iñigo Gómara ◽  
Belén Rodríguez-Fonseca ◽  
Elsa Mohino ◽  
Teresa Losada ◽  
Irene Polo ◽  
...  
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Marine Ecosystem ◽  
Ecosystem Model ◽  
Tropical Pacific ◽  
Equatorial Atlantic ◽  
Climate Conditions ◽  
Marine Food Web ◽  
Marine Ecosystem Model ◽  
The Tropical Pacific

AbstractTropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Niño Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, owing to observational data scarcity and bias-related issues in earth system models, little is known about the importance of these precursors for marine ecosystem prediction. With recently released reanalysis-nudged global marine ecosystem simulations, these constraints can be sidestepped, allowing full examination of tropical Pacific ecosystem predictability. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic Sea Surface Temperatures (SSTs) constitute a superlative predictability source for tropical Pacific marine yields, which can be forecasted over large-scale areas up to 2 years in advance. A detailed physical-biological mechanism is proposed whereby Atlantic SSTs modulate upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific.

Estimation of the Parameters in a Dynamical Marine Ecosystem Model Based on the Adjoint Assimilation

2013 ◽  
Vol 321-324 ◽  
pp. 2419-2423
Author(s):  
Xiao Yan Li ◽  
Chun Hui Wang ◽  
Xian Qing Lv
Keyword(s):  
Marine Ecosystem ◽  
Absolute Error ◽  
Ecosystem Model ◽  
Global Scale ◽  
Time Step ◽  
Marine Ecosystem Model ◽  
Maximum Uptake Rate ◽  
Influence Radius ◽  
Adjoint Assimilation ◽  
Spatially Varying

By utilizing spatial biological parameterizations, the adjoint variational method was applied to a 3D marine ecosystem model (NPZD-type) and its adjoint model which were built on global scale based on climatological environment and data. When the spatially varying Vm (maximum uptake rate of nutrient by phytoplankton) was estimated alone, we discussed how would the distribution schemes of spatial parameterization and influence radius affected the results. The reduced cost function (RCF), the mean absolute error (MAE) of phytoplankton in the surface layer, and the relative error (RE) of Vm between given and simulated values decreased obviously. The influence of time step was studied then and we found that the assimilation recovery would not be more successful with a smaller time step of 3 hours compared with 6 hours.

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