scholarly journals Parameter Estimation Using a Particle Method: Inferring Mixing Coefficients from Sea Level Observations

2007 ◽  
Vol 135 (3) ◽  
pp. 1006-1020 ◽  
Author(s):  
Femke C. Vossepoel ◽  
Peter Jan van Leeuwen
Keyword(s):  
Sea Level ◽  
General Circulation ◽  
Circulation Model ◽  
Particle Method ◽  
Ocean General Circulation Model ◽  
Global Ocean ◽  
High Complexity ◽  
Ensemble Size ◽  
Mixing Parameters ◽  
Mixing Coefficients

Abstract This paper presents a first attempt to estimate mixing parameters from sea level observations using a particle method based on importance sampling. The method is applied to an ensemble of 128 members of model simulations with a global ocean general circulation model of high complexity. Idealized twin experiments demonstrate that the method is able to accurately reconstruct mixing parameters from an observed mean sea level field when mixing is assumed to be spatially homogeneous. An experiment with inhomogeneous eddy coefficients fails because of the limited ensemble size. This is overcome by the introduction of local weighting, which is able to capture spatial variations in mixing qualitatively. As the sensitivity of sea level for variations in mixing is higher for low values of mixing coefficients, the method works relatively well in regions of low eddy activity.

scholarly journals FGOALS-g3 Model Datasets for CMIP6 Flux-Anomaly-Forced Model Intercomparison Project

2020 ◽  
Vol 37 (10) ◽  
pp. 1093-1101
Author(s):  
Yaqi Wang ◽  
Zipeng Yu ◽  
Pengfei Lin ◽  
Hailong Liu ◽  
Jiangbo Jin ◽  
...  
Keyword(s):  
Sea Level ◽  
Ocean Circulation ◽  
General Circulation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Global Ocean ◽  
Model Intercomparison ◽  
Ocean Heat Uptake ◽  
Intercomparison Project ◽  
Global Mean

Abstract The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) is an endorsed Model Intercomparison Project in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The goal of FAFMIP is to investigate the spread in the atmosphere-ocean general circulation model projections of ocean climate change forced by increased CO2, including the uncertainties in the simulations of ocean heat uptake, global mean sea level rise due to ocean thermal expansion and dynamic sea level change due to ocean circulation and density changes. The FAFMIP experiments have already been conducted with the Flexible Global Ocean-Atmosphere-Land System Model, gridpoint version 3.0 (FGOALS-g3). The model datasets have been submitted to the Earth System Grid Federation (ESGF) node. Here, the details of the experiments, the output variables and some baseline results are presented. Compared with the preliminary results of other models, the evolutions of global mean variables can be reproduced well by FGOALS-g3. The simulations of spatial patterns are also consistent with those of other models in most regions except the North Atlantic and the Southern Ocean, indicating large uncertainties in the regional sea level projections of these two regions.

scholarly journals Formulation of a new explicit tidal scheme in ocean general circulation model

2022 ◽  
Author(s):  
Jiangbo Jin ◽  
Run Guo ◽  
Minghua Zhang ◽  
Guangqing Zhou ◽  
Qingcun Zeng
Keyword(s):  
Sea Level ◽  
General Circulation ◽  
Thermohaline Circulation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Ocean Model ◽  
Tidal Mixing ◽  
Global Ocean ◽  
The North ◽  
Tidal Constituents

Abstract. Tides play an important role in ocean energy transfer and mixing, and provide major energy for maintaining thermohaline circulation. This study proposes a new explicit tidal scheme and assesses its performance in a global ocean model. Instead of using empirical specifications of tidal amplitudes and frequencies, the new scheme directly uses the positions of the Moon and Sun in a global ocean model to incorporate tides. Compared with the traditional method that has specified tidal constituents, the new scheme can better simulate the diurnal and spatial characteristics of the tidal potential of spring and neap tides as well as the spatial patterns and magnitudes of major tidal constituents (K1 and M2). It significantly reduces the total errors of eight tidal constituents (with the exception of N2 and Q1) in the traditional explicit tidal scheme. Relative to the control simulation without tides, both the new and traditional tidal schemes can lead to better dynamic sea level (DSL) simulation in the North Atlantic, reducing significant negative biases in this region. The new tidal scheme also shows smaller positive bias than the traditional scheme in the Southern Ocean. The new scheme is suited to calculate regional distributions of sea level height in addition to tidal mixing.

scholarly journals Next generation of Bluelink ocean reanalysis with multiscale data assimilation: BRAN2020

2021 ◽  
Vol 13 (12) ◽  
pp. 5663-5688
Author(s):  
Matthew A. Chamberlain ◽  
Peter R. Oke ◽  
Russell A. S. Fiedler ◽  
Helen M. Beggs ◽  
Gary B. Brassington ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
General Circulation ◽  
Mixed Layer Depth ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Global Ocean ◽  
Optimal Interpolation ◽  
Multiscale Approach ◽  
Ocean Reanalysis

Abstract. BRAN2020 (2020 version of the Bluelink ReANalysis) is an ocean reanalysis that combines observations with an eddy-resolving, near-global ocean general circulation model to produce a four-dimensional estimate of the ocean state. The data assimilation system employed is ensemble optimal interpolation, implemented with a new multiscale approach that constrains the broad-scale ocean properties and the mesoscale circulation in two steps. There is a separation in the scales that are corrected in the two steps: the high-resolution step corrects the mesoscale dynamics in the same way as previous versions of BRAN, while the extra coarse step is effective at correcting biases that develop at large scales. The reanalysis currently spans January 1993 to December 2019 and assimilates observations of in situ temperature and salinity, as well as of satellite sea-level anomaly and sea surface temperature. BRAN2020 is planned to be updated to within months of real time after this initial release, until an updated version of BRAN is available. Reanalysed fields from BRAN2020 generally show much closer agreement to observations than all previous versions with misfits between reanalysed and observed fields reduced by over 30 % for some variables, for subsurface temperature and salinity in particular. The BRAN2020 dataset is comprised of daily averaged fields of temperature, salinity, velocity, mixed-layer depth and sea level. Reanalysed fields realistically represent all of the major current systems within 75∘ S and 75∘ N, excluding processes relating to sea ice but including boundary currents, equatorial circulation, Southern Ocean variability and mesoscale eddies. BRAN2020 is publicly available at https://doi.org/10.25914/6009627c7af03 (Chamberlain et al., 2021b) and is intended for use by the research community.

scholarly journals Next generation of Bluelink ocean reanalysis with multiscale data assimilation: BRAN2020

2021 ◽  
Author(s):  
Matthew A. Chamberlain ◽  
Peter R. Oke ◽  
Russell A. S. Fiedler ◽  
Helen M. Beggs ◽  
Gary B. Brassington ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
General Circulation ◽  
Mixed Layer Depth ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Global Ocean ◽  
Optimal Interpolation ◽  
Multiscale Approach ◽  
Ocean Reanalysis

Abstract. BRAN2020 is an ocean reanalysis that combines ocean observations with an eddy-resolving, near-global ocean general circulation model, to produce four-dimensional estimates of the ocean state. The data assimilation system employed is ensemble optimal interpolation, implemented with a new multiscale approach that constrains the broad-scale ocean properties and the mesoscale circulation in two steps. The reanalysis spans January 1993 to December 2019, and assimilates observations of in situ temperature and salinity, as well as satellite sea-level anomaly and sea surface temperature. Reanalysed fields from BRAN2020 generally show much closer agreement to observations than all previous versions with mis-fits between reanalysed and observed fields reduced by over 30 % for some variables. The BRAN2020 dataset is comprised of daily-averaged fields of temperature, salinity, velocity, mixed-layer depth, and sea-level. Reanalysed fields realistically represent all of the major current systems within 75° S and 75° N, excluding processes relating to sea ice, but including boundary currents, equatorial circulation, Southern Ocean variability, and mesoscale eddies. BRAN2020 is publicly-available at https://doi.org/10.25914/6009627c7af03 (Chamberlain et al., 2021b) and is intended for use by the research community.

scholarly journals Global tide simulations with ICON-O: testing the model performance on highly irregular meshes

2020 ◽  
Vol 71 (1) ◽  
pp. 43-57
Author(s):  
Kai Logemann ◽  
Leonidas Linardakis ◽  
Peter Korn ◽  
Corinna Schrum
Keyword(s):  
General Circulation ◽  
Model Performance ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Discrete Fourier Transformation ◽  
Global Ocean ◽  
Transition Zones ◽  
Maximum Angle ◽  
Irregular Meshes

AbstractThe global tide is simulated with the global ocean general circulation model ICON-O using a newly developed tidal module, which computes the full tidal potential. The simulated coastal M2 amplitudes, derived by a discrete Fourier transformation of the output sea level time series, are compared with the according values derived from satellite altimetry (TPXO-8 atlas). The experiments are repeated with four uniform and sixteen irregular triangular grids. The results show that the quality of the coastal tide simulation depends primarily on the coastal resolution and that the ocean interior can be resolved up to twenty times lower without causing considerable reductions in quality. The mesh transition zones between areas of different resolutions are formed by cell bisection and subsequent local spring optimisation tolerating a triangular cell’s maximum angle up to 84°. Numerical problems with these high-grade non-equiangular cells were not encountered. The results emphasise the numerical feasibility and potential efficiency of highly irregular computational meshes used by ICON-O.

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