On the use of idealised test cases for ocean model development

2021 ◽  
Author(s):  
Julie Deshayes
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Model Development ◽  
General Circulation Models ◽  
Ocean Model ◽  
Ocean Dynamics ◽  
Test Cases ◽  
Training Tool ◽  
Research Activities ◽  
Historical Progress

<p>When comparing realistic simulations produced by two ocean general circulation models, differences may emerge from alternative choices in boundary conditions and forcings, which alters our capacity to identify the actual differences between the two models (in the equations solved, the discretization schemes employed and/or the parameterizations introduced). The use of idealised test cases (idealized configurations with analytical boundary conditions and forcings, resolving a given set of equations) has proven efficient to reveal numerical bugs, determine advantages and pitfalls of certain numerical choices, and highlight remaining challenges. I propose to review historical progress enabled by the use of idealised test cases, and promote their utilization when assessing ocean dynamics as represented by an ocean model. For the latter, I would illustrate my talk using illustrations from my own research activities using NEMO in various contexts. I also see idealised test cases as a promising training tool for inexperienced ocean modellers, and an efficient solution to enlarge collaboration with experts in adjacent disciplines, such as mathematics, fluid dynamics and computer sciences.</p>

scholarly journals Modeling Air–Land–Sea Interactions Using the Integrated Regional Model System in Monterey Bay, California

2012 ◽  
Vol 140 (4) ◽  
pp. 1285-1306 ◽  
Author(s):  
Yu-Heng Tseng ◽  
Shou-Hung Chien ◽  
Jiming Jin ◽  
Norman L. Miller
Keyword(s):  
High Resolution ◽  
General Circulation ◽  
Coastal Upwelling ◽  
General Circulation Models ◽  
Regional Model ◽  
Ocean Model ◽  
Model System ◽  
Ocean Dynamics ◽  
Monterey Bay ◽  
Community Land Model

The air–land–sea interaction in the vicinity of Monterey Bay, California, is simulated and investigated using a new Integrated Regional Model System (I-RMS). This new model realistically resolves coastal processes and submesoscale features that are poorly represented in atmosphere–ocean general circulation models where systematic biases are seen in the long-term model integration. The current I-RMS integrates version 3.1 of the Weather Research and Forecasting Model and version 3.0 of the Community Land Model with an advanced coastal ocean model, based on the nonhydrostatic Monterey Bay Area Regional Ocean Model. The daily land–sea-breeze circulations and the Santa Cruz eddy are fully resolved using high-resolution grids in the coastal margin. In the ocean, coastal upwelling and submesoscale gyres are also well simulated with this version of the coupled I-RMS. Comparison with observations indicates that the high-resolution, improved representation of ocean dynamics in the I-RMS increases the surface moisture flux and the resulting lower-atmospheric water vapor, a primary controlling mechanism for the enhancement of regional coastal fog formation, particularly along the West Coast of the conterminous United States. The I-RMS results show the importance of detailed ocean feedbacks due to coastal upwelling in the marine atmospheric boundary layer.

scholarly journals Coupled ice sheet–climate modeling under glacial and pre-industrial boundary conditions

2014 ◽  
Vol 10 (5) ◽  
pp. 1817-1836 ◽  
Author(s):  
F. A. Ziemen ◽  
C. B. Rodehacke ◽  
U. Mikolajewicz
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Climate Modeling ◽  
Ice Sheets ◽  
Ice Sheet ◽  
General Circulation Models ◽  
Quasi Equilibrium ◽  
Ice Streams ◽  
Ice Stream ◽  
First Results

Abstract. In the standard Paleoclimate Modelling Intercomparison Project (PMIP) experiments, the Last Glacial Maximum (LGM) is modeled in quasi-equilibrium with atmosphere–ocean–vegetation general circulation models (AOVGCMs) with prescribed ice sheets. This can lead to inconsistencies between the modeled climate and ice sheets. One way to avoid this problem would be to model the ice sheets explicitly. Here, we present the first results from coupled ice sheet–climate simulations for the pre-industrial times and the LGM. Our setup consists of the AOVGCM ECHAM5/MPIOM/LPJ bidirectionally coupled with the Parallel Ice Sheet Model (PISM) covering the Northern Hemisphere. The results of the pre-industrial and LGM simulations agree reasonably well with reconstructions and observations. This shows that the model system adequately represents large, non-linear climate perturbations. A large part of the drainage of the ice sheets occurs in ice streams. Most modeled ice stream systems show recurring surges as internal oscillations. The Hudson Strait Ice Stream surges with an ice volume equivalent to about 5 m sea level and a recurrence interval of about 7000 yr. This is in agreement with basic expectations for Heinrich events. Under LGM boundary conditions, different ice sheet configurations imply different locations of deep water formation.

scholarly journals Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)

2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Middle Miocene ◽  
Climate Models ◽  
Global Climate ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Ice Volume ◽  
Climate Transition

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice-sheet expansion and global cooling during the interval ~ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry and vegetation. Additionally, Antarctic ice volume and geometry, sea-level and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.

scholarly journals An automatic and effective parameter optimization method for model tuning

2015 ◽  
Vol 8 (11) ◽  
pp. 3579-3591 ◽  
Author(s):  
T. Zhang ◽  
L. Li ◽  
Y. Lin ◽  
W. Xue ◽  
F. Xie ◽  
...  
Keyword(s):  
Simplex Method ◽  
General Circulation ◽  
Model Development ◽  
Model Performance ◽  
Parameter Tuning ◽  
General Circulation Models ◽  
Development Stage ◽  
Optimum Combination ◽  
Downhill Simplex Method ◽  
Downhill Simplex

Abstract. Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

Salinity Assimilation Using S(T): Covariance Relationships

2006 ◽  
Vol 134 (3) ◽  
pp. 759-771 ◽  
Author(s):  
K. Haines ◽  
J. D. Blower ◽  
J-P. Drecourt ◽  
C. Liu ◽  
A. Vidard ◽  
...  
Keyword(s):  
General Circulation ◽  
Power Spectra ◽  
General Circulation Models ◽  
Temporal Variations ◽  
Ocean Model ◽  
Spatial Covariance ◽  
Ocean Reanalysis ◽  
Argo Data ◽  
Ocean Reanalyses ◽  
Salinity Data

Abstract Assimilation of salinity into ocean and climate general circulation models is a very important problem. Argo data now provide far more salinity observations than ever before. In addition, a good analysis of salinity over time in ocean reanalyses can give important results for understanding climate change. Here it is shown from the historical ocean database that over large regions of the globe (mainly midlatitudes and lower latitudes) variance of salinity on an isotherm S(T) is often less than variance measured at a particular depth S(z). It is also shown that the dominant temporal variations in S(T) occur more slowly than variations in S(z), based on power spectra from the Bermuda time series. From ocean models it is shown that the horizontal spatial covariance of S(T) often has larger scales than S(z). These observations suggest an assimilation method based on analyzing S(T). An algorithm for assimilating salinity data on isotherms is then presented, and it is shown how this algorithm produces orthogonal salinity increments to those produced during the assimilation of temperature profiles. It is argued that the larger space and time scales can be used for the S(T) assimilation, leading to better use of scarce salinity observations. Results of applying the salinity assimilation algorithm to a single analysis time within the ECMWF seasonal forecasting ocean model are also shown. The separate salinity increments coming from temperature and salinity data are identified, and the independence of these increments is demonstrated. Results of an ocean reanalysis with this method will appear in a future paper.

scholarly journals A One-Dimensional Mixed Layer Ocean Model for Use in Three-Dimensional Climate Simulations: Control Simulation Compared to Observations

2005 ◽  
Vol 18 (13) ◽  
pp. 2199-2221 ◽  
Author(s):  
Monica Y. Stephens ◽  
Robert J. Oglesby ◽  
Martin Maxey
Keyword(s):  
Heat Flux ◽  
Mixed Layer ◽  
General Circulation ◽  
Climate Model ◽  
Mixed Layer Depth ◽  
Circulation Model ◽  
Ocean Model ◽  
Ocean Dynamics ◽  
One Dimensional ◽  
Mixed Layer Ocean

Abstract A study has been made of the dynamic interactions between the surface layer of the ocean and the atmosphere using a climate model that contains a new approach to predicting the sea surface temperature (SST). The atmospheric conditions are simulated numerically with the NCAR Community Climate Model (CCM3). The SST is determined by a modified Kraus–Turner-type one-dimensional mixed layer ocean model (MLOM) for the upper ocean that has been coupled to CCM3. The MLOM simulates vertical ocean dynamics and demonstrates the effects of the seasonal variation of mixed layer depth and convective instability on the SST. A purely thermodynamic slab ocean model (SOM) is currently available for use with CCM3 to predict the SST. A large-scale ocean general circulation model (OGCM) may also be coupled to CCM3; however, the OGCM is computationally intensive and is therefore not a good tool for conducting multiple sensitivity studies. The MLOM provides an alternative to the SOM that contains seasonally and spatially specified mixed layer depths. The SOM also contains a heat flux correction called Q-flux that crudely accounts for ocean heat transport by artificially specifying a heat flux that forces the SOM to replicate the observed SST. The results of the coupled MLOM–CCM3 reveal that the MLOM may be used on a global scale and can therefore replace the standard coupled SOM–CCM3 that contains no explicit ocean dynamics. Additionally, stand-alone experiments of the MLOM that are forced with realistic winds, heat, and moisture fluxes show that the MLOM closely approximates the observed seasonal cycle of SST.

Estimating structural and parametric uncertainties in the simulated early Eocene surface warming

2020 ◽  
Author(s):  
Sebastian Steinig ◽  
Fran J. Bragg ◽  
Peter J. Irvine ◽  
Daniel J. Lunt ◽  
Paul J. Valdes
Keyword(s):  
Temperature Gradient ◽  
Boundary Conditions ◽  
Greenhouse Gas ◽  
General Circulation ◽  
Parametric Uncertainty ◽  
General Circulation Models ◽  
Parametric Uncertainties ◽  
Early Eocene ◽  
Meridional Temperature Gradient ◽  
Surface Warming

<p>Simulating the proxy-derived surface warming and reduced meridional temperature gradient of the early Eocene greenhouse climate still represents a challenge for most atmosphere-ocean general circulation models. A profound understanding of uncertainties associated with the respective model results is thereby essential to reliably identify any similarities or misfits to the proxy record. Besides incomplete knowledge of past greenhouse gas concentrations and other boundary conditions, structural and parametric uncertainties are the main factors that determine our confidence in paleoclimate simulation results.</p><p>The recent publication of coordinated model experiments that apply identical paleogeographic boundary conditions for key time periods of the early Eocene (DeepMIP) allows a systematic analysis of inter-model differences and therefore of structural uncertainties in the simulated surface warming. Here we additionally explore the parametric uncertainty of the early Eocene climatic optimum (EECO) surface warming within one DeepMIP model. For this we performed perturbed parameter ensemble (PPE) simulations with HadCM3B at different atmospheric CO<sub>2</sub> concentrations following the DeepMIP protocol. Twenty-one parameter sets based on changes in six atmospheric parameters, a sea-ice parameter and the ocean background diffusivity were branched off from the respective DeepMIP control simulations and integrated for a further 1500 model years. The selected parameter sets are based on previous results demonstrating their ability to simulate a pre-industrial global-mean surface temperature within ±2 °C of the standard configuration.</p><p>Preliminary results indicate a large spread of the simulated low-latitude surface warming in the PPE and therefore significant changes of the large-scale meridional temperature gradient for the EECO. Some ensemble members develop numerical instabilities at CO<sub>2</sub> concentrations of 840 ppmv and above, most likely in consequence of high temperatures in the tropical troposphere. We further compare the magnitude of the parametric uncertainty of the HadCM3B perturbation experiments with the structural differences found in the DeepMIP multi-model ensemble and explore the sensitivity of the results to the strength of the applied greenhouse gas forcing. Model skill of the PPE members is tested against the most recent DeepMIP compilations of marine and terrestrial proxy temperatures.</p>

scholarly journals Transient Climate Response in Coupled Atmospheric–Ocean General Circulation Models

2013 ◽  
Vol 70 (4) ◽  
pp. 1291-1296 ◽  
Author(s):  
Mao-Chang Liang ◽  
Li-Ching Lin ◽  
Ka-Kit Tung ◽  
Yuk L. Yung ◽  
Shan Sun
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
General Circulation Models ◽  
Ocean Model ◽  
Climate Response ◽  
Intergovernmental Panel ◽  
Transient Climate Response ◽  
Climate System Model ◽  
Uncertainty Range ◽  
Model Version

Abstract The equilibrium climate sensitivity (ECS) has a large uncertainty range among models participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and has recently been presented as “inherently unpredictable.” One way to circumvent this problem is to consider the transient climate response (TCR). However, the TCR among AR4 models also differs by more than a factor of 2. The authors argue that the situation may not necessarily be so pessimistic, because much of the intermodel difference may be due to the fact that the models were run with their oceans at various stages of flux adjustment with their atmosphere. This is shown by comparing multimillennium-long runs of the Goddard Institute for Space Studies model, version E, coupled with the Hybrid Coordinate Ocean Model (GISS-EH) and the Community Climate System Model, version 4 (CCSM4) with what were reported to AR4. The long model runs here reveal the range of variability (~30%) in their TCR within the same model with the same ECS. The commonly adopted remedy of subtracting the “climate drift” is ineffective and adds to the variability. The culprit is the natural variability of the control runs, which exists even at quasi equilibration. Fortunately, for simulations with multidecadal time horizon, robust solutions can be obtained by branching off thousand-year-long control runs that reach “quasi equilibration” using a new protocol, which takes advantage of the fact that forced solutions to radiative forcing forget their initial condition after 30–40 yr and instead depend mostly on the trajectory of the radiative forcing.

scholarly journals Do climate simulations from models forced by averaged sea surface temperatures represent actual dynamics?

1997 ◽  
Vol 4 (2) ◽  
pp. 93-100 ◽  
Author(s):  
P. J. Roebber ◽  
A. A. Tsonis ◽  
J. B. Elsner
Keyword(s):  
General Circulation ◽  
Climatic Variability ◽  
General Circulation Models ◽  
Ocean Model ◽  
Coupled Systems ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Surface Temperatures ◽  
Fully Coupled ◽  
Low Order

Abstract. Recently atmospheric general circulation models (AGCMs) forced by observed sea surface temperatures (SSTs) have offered the possibility of studying climate variability over periods ranging from years to decades. Such models represent and alternative to fully coupled asynchronous atmosphere ocean models whose long term integration remains problematic. Here, the degree of the approximation represented by this approach is investigated from a conceptual point of view by comparing the dynamical properties of a low order coupled atmosphere-ocean model to those of the atmospheric component of the same model when forced with monthly values of SST derived from the fully coupled simulation. The low order modelling approach is undertaken with the expectation that it may reveal general principles concerning the dynamical behaviour of the forced versus coupled systems; it is not expected that such an approach will determine the details of these differences, for which higher order modelling studies will be required. We discover that even though attractor (global) averages may be similar, local dynamics and the resultant variability and predictability characteristics differ substantially. These results suggest that conclusions concerning regional climatic variability (in time as well as space) drawn from forced modelling approaches may be contaminated by an inherently unquantifiable error. It is therefore recommended that this possibility be carefully investigated using state-of-the-art coupled AGCMs.

Sign in / Sign up

Export Citation Format

Share Document