scholarly journals Ocean model response to stochastically perturbed momentum fluxes

2021 ◽  
Author(s):  
Terence O'Kane ◽  
Russell Fiedler ◽  
Mark Collier ◽  
Vassili Kitsios
Keyword(s):  
Kinetic Energy ◽  
Climate Model ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Dynamical Theory ◽  
Ocean Model ◽  
Energy Spectra ◽  
Small Scale ◽  
Model Errors ◽  
Momentum Fluxes

In climate model configurations, standard approaches to the representation of unresolved, or subgrid scales, via deterministic closure schemes are being challenged by stochastic approaches inspired by statistical dynamical theory. Despite gaining popularity, studies of various stochastic subgrid scale parameterizations applied to atmospheric climate and weather prediction systems have revealed a diversity of model responses, including degeneracy in the response to different forcings and compensating model errors, with little reduction in artificial damping of the small scales required for numerical stability. Due to the greater range of spatio-temporal scales involved, how to best sample subgrid fluctuations in a computationally inexpensive manner, with the aim of reduced model error and improvements to the simulated climatological state of the ocean, remains an open question. While previous studies have considered perturbations to the surface forcing or subsurface temperature tendencies, we implement an energetically consistent, simple, stochastic subgrid eddy parameterization of the momentum fluxes in regions of the three-dimensional ocean typically associated with high eddy variability. We consider the changes in the modelled energetics of low-resolution simulations in response to stochastically forced velocity tendencies whose perturbation statistics and amplitudes are calculated from an eddy resolving ocean configuration. Kinetic energy spectra from a triple-decomposition reveal a systematic redistribution from the seasonal (climatological minus mean) potential energy to preferentially generate small scale transient kinetic energy while the total energy spectra remains largely unchanged. We show that stochastic parameterization generally improves model biases, noticeably so for the simulated energetics of the Southern Oceans.

scholarly journals Physical-biogeochemical regional ocean model uncertainties stemming from stochastic parameterizations and potential impact on data assimilation

2019 ◽  
Author(s):  
Vassilios D. Vervatis ◽  
Pierre De Mey-Frémaux ◽  
Nadia Ayoub ◽  
Sarantis Sofianos ◽  
Charles-Emmanuel Testut ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Spatial Scales ◽  
Ecosystem Model ◽  
Ocean Model ◽  
Open Ocean ◽  
Small Scale ◽  
Biogeochemical Model ◽  
Frequency Error ◽  
Model Errors ◽  
Potential Impact

Abstract. We generate ocean biogeochemical model ensembles including several kinds of stochastic parameterizations. The NEMO stochastic modules are complemented by integrating a subroutine to calculate variable anisotropic spatial scales, which are of particular importance in high-resolution coastal configurations. The domain covers the Bay of Biscay at 1/36° resolution, as a case study for open-ocean and coastal shelf dynamics. At first, we identify uncertainties from assumptions subject to erroneous atmospheric forcing, ocean model improper parameterizations and ecosystem state uncertainties. The error regimes are found to be mainly driven by the wind forcing, with the rest of the perturbed tendencies locally augmenting the ensemble spread. Biogeochemical uncertainties arise from inborn ecosystem model errors and from errors in the physical state. Model errors in physics are found to have larger impact on chlorophyll spread than those of the ecosystem. In a second step, the ensembles undergo verification with respect to observations, focusing on upper-ocean properties. We investigate the statistical consistency of prior model errors and observation estimates, in view of joint uncertainty vicinities, associated with both sources of information. OSTIA-SST L4 distribution appears to be compatible with ensembles perturbing physics, since vicinities overlap, enabling data assimilation. The most consistent configuration for SLA along-track L3 data is in the Abyssal plain, where the spread is increased due to mesoscale eddy decorrelation. The largest statistical SLA biases are observed in coastal regions, sometimes to the point that vicinities become disjoint. Missing error processes in relation to SLA hint at the presence of high-frequency error sources currently unaccounted for, potentially leading to ill-posed assimilation problems. Ecosystem model-data samples with respect to Ocean Colour L4 appear to be compatible with each other only at times, with data assimilation being marginally well-posed. In a third step, we illustrate the potential influence of those uncertainties on data assimilation impact exercise, by means of multivariate representers and EnKF-type incremental analysis for a few members. Corrections on physical properties are associated with large-scale biases between model and data, with diverse characteristics in the open-ocean and the shelves. The increments are often characteristic of the underlying mesoscale features, chlorophyll included due to the vertical velocity field. Small scale local corrections are visible over the shelves. Chlorophyll information seems to have a very measurable potential impact on physical variables.

scholarly journals Tidal Energy Flows between the Midriff Islands in the Gulf of California

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 621
Author(s):  
Federico Angel Velazquez-Muñoz ◽  
Anatoliy Filonov
Keyword(s):  
Kinetic Energy ◽  
Internal Wave ◽  
Gulf Of California ◽  
Current Flow ◽  
Tidal Flow ◽  
Three Dimensional ◽  
Tidal Energy ◽  
Ocean Model ◽  
Field Development ◽  
Wave Measurements

The Gulf of California has many regions of potential tidal-stream energy that have been identified and characterized using in-situ measurements and numerical ocean models. The Midriff Islands region has received particular attention due to its increased current speeds and high kinetic energy. This increase in energy can be seen in the formation of internal wave packets propagating for several hundred kilometers. Here we present a brief description of internal wave measurements travel towards the Northern Gulf and explore energy generation sites. In this paper we characterize the tidal inflow and outflow that passes throughout the Midriff Islands in the central part of the Gulf. We use a three-dimensional numerical ocean model that adequately reproduces the tidal flow and the increase in speed and kinetic energy between the islands. The current flow structure shows the highest velocity cores near the shore and far from the bottom. During the rising tide, the maximum current flow (~0.6 ms−1) was found between Turón Island and San Lorenzo Island, from the surface to 200 m depth. When the currents flowed out of the Gulf, during the falling tide, the maximum negative current (−0.8 ms−1) was found between Tiburon Island and Turón Island, from near the surface to 80 m depth. Although there are favorable conditions for power generation potential by tidal flows, the vertical variability of the current must be considered for field development and equipment installation sites.

Assessing spatio-temporal variability and biases of climate models

2020 ◽  
Author(s):  
Nedjeljka Žagar
Keyword(s):  
Temporal Variability ◽  
Prediction Models ◽  
Climate Model ◽  
Weather Prediction ◽  
Ocean Model ◽  
Spatial And Temporal Variability ◽  
Dynamical Regime ◽  
Temporal Variance ◽  
Slab Ocean ◽  
Spatio Temporal

<div>Atmospheric spatial and temporal variability are closely related with the former being relatively well observed compared to the latter. The former is also regularly assessed in the validation of numerical weather prediction models while the latter is more difficult to estimate. Likewise, thermodynamical fields and circulation are closely coupled calling for an approach that considers them simultaneously.  </div> <div>In this contribution, spatio-temporal variability spectra of the four major reanalysis datasets are discussed and applied for the validation of a climate model prototype.  A relationship between deficiencies in simulated variability and model biases is derived. The underlying method includes dynamical regime decomposition thereby providing a better understanding of the role of tropical variability in global circulation. </div> <div>Results of numerical simulations are validated by a 20th century reanalysis. A climate model was forced either with the prescribed SST or with a slab ocean model that updates SST in each forecast step.  Scale-dependent validation shows that missing temporal variance in the model relative to verifying reanalysis increases as the spatial scale reduces that appears associated with an increasing lack of spatial variance at smaller scales. Similar to variability, bias is strongly scale dependent; the larger the scale, the greater the bias. Biases present in the SST-forced simulation increase in the simulation using the slab ocean. The comparison of biases computed as a systematic difference between the model and reanalysis and between the SST-forced model and slab-ocean model (a perfect-model scenario) suggests that improving the atmospheric model increases the variance in the model on synoptic and subsynoptic scales but large biases associated with a poor SST remain at planetary scales.</div> <p> </p>

scholarly journals Subseasonal Forecasting with an Icosahedral, Vertically Quasi-Lagrangian Coupled Model. Part I: Model Overview and Evaluation of Systematic Errors

2018 ◽  
Vol 146 (5) ◽  
pp. 1601-1617 ◽  
Author(s):  
Shan Sun ◽  
Rainer Bleck ◽  
Stanley G. Benjamin ◽  
Benjamin W. Green ◽  
Georg A. Grell
Keyword(s):  
Time Scales ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Coupled Model ◽  
Systematic Errors ◽  
Ocean Model ◽  
Grid Structure ◽  
Ensemble Forecasts ◽  
Vertical Coordinate ◽  
Hybrid Coordinate Ocean Model

Abstract The atmospheric hydrostatic Flow-Following Icosahedral Model (FIM), developed for medium-range weather prediction, provides a unique three-dimensional grid structure—a quasi-uniform icosahedral horizontal grid and an adaptive quasi-Lagrangian vertical coordinate. To extend the FIM framework to subseasonal time scales, an icosahedral-grid rendition of the Hybrid Coordinate Ocean Model (iHYCOM) was developed and coupled to FIM. By sharing a common horizontal mesh, air–sea fluxes between the two models are conserved locally and globally. Both models use similar adaptive hybrid vertical coordinates. Another unique aspect of the coupled model (referred to as FIM–iHYCOM) is the use of the Grell–Freitas scale-aware convective scheme in the atmosphere. A multiyear retrospective study is necessary to demonstrate the potential usefulness and allow for immediate bias correction of a subseasonal prediction model. In these two articles, results are shown based on a 16-yr period of hindcasts from FIM–iHYCOM, which has been providing real-time forecasts out to a lead time of 4 weeks for NOAA’s Subseasonal Experiment (SubX) starting July 2017. Part I provides an overview of FIM–iHYCOM and compares its systematic errors at subseasonal time scales to those of NOAA’s operational Climate Forecast System version 2 (CFSv2). Part II uses bias-corrected hindcasts to assess both deterministic and probabilistic subseasonal skill of FIM–iHYCOM. FIM–iHYCOM has smaller biases than CFSv2 for some fields (including precipitation) and comparable biases for other fields (including sea surface temperature). FIM–iHYCOM also has less drift in bias between weeks 1 and 4 than CFSv2. The unique grid structure and physics suite of FIM–iHYCOM is expected to add diversity to multimodel ensemble forecasts at subseasonal time scales in SubX.

scholarly journals Formulation of an ocean model for global climate simulations

Ocean Science ◽  
2005 ◽  
Vol 1 (1) ◽  
pp. 45-79 ◽  
Author(s):  
S. M. Griffies ◽  
A. Gnanadesikan ◽  
K. W. Dixon ◽  
J. P. Dunne ◽  
R. Gerdes ◽  
...  
Keyword(s):  
Free Surface ◽  
Climate Model ◽  
Global Climate ◽  
Three Dimensional ◽  
Ocean Model ◽  
Tidal Mixing ◽  
The Arctic ◽  
Tracer Transport ◽  
Marginal Seas ◽  
Ocean Climate Model

Abstract. This paper summarizes the formulation of the ocean component to the Geophysical Fluid Dynamics Laboratory's (GFDL) climate model used for the 4th IPCC Assessment (AR4) of global climate change. In particular, it reviews the numerical schemes and physical parameterizations that make up an ocean climate model and how these schemes are pieced together for use in a state-of-the-art climate model. Features of the model described here include the following: (1) tripolar grid to resolve the Arctic Ocean without polar filtering, (2) partial bottom step representation of topography to better represent topographically influenced advective and wave processes, (3) more accurate equation of state, (4) three-dimensional flux limited tracer advection to reduce overshoots and undershoots, (5) incorporation of regional climatological variability in shortwave penetration, (6) neutral physics parameterization for representation of the pathways of tracer transport, (7) staggered time stepping for tracer conservation and numerical efficiency, (8) anisotropic horizontal viscosities for representation of equatorial currents, (9) parameterization of exchange with marginal seas, (10) incorporation of a free surface that accomodates a dynamic ice model and wave propagation, (11) transport of water across the ocean free surface to eliminate unphysical ``virtual tracer flux" methods, (12) parameterization of tidal mixing on continental shelves. We also present preliminary analyses of two particularly important sensitivities isolated during the development process, namely the details of how parameterized subgridscale eddies transport momentum and tracers.

scholarly journals A New Theoretical Framework for Understanding Multiscale Atmospheric Predictability

2020 ◽  
Vol 77 (7) ◽  
pp. 2297-2309
Author(s):  
Y. Qiang Sun ◽  
Fuqing Zhang
Keyword(s):  
Energy Spectrum ◽  
Numerical Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Theoretical Framework ◽  
Growth Behavior ◽  
Small Scale ◽  
Growth Equation ◽  
Error Growth ◽  
Atmospheric Predictability

AbstractHere we present a new theoretical framework that connects the error growth behavior in numerical weather prediction (NWP) with the atmospheric kinetic energy spectrum. Building on previous studies, our newly proposed framework applies to the canonical observed atmospheric spectrum that has a −3 slope at synoptic scales and a −5/3 slope at smaller scales. Based on this realistic hybrid energy spectrum, our new experiment using hybrid numerical models provides reasonable estimations for the finite predictable ranges at different scales. We further derive an analytical equation that helps understand the error growth behavior. Despite its simplicity, this new analytical error growth equation is capable of capturing the results of previous comprehensive theoretical and observational studies of atmospheric predictability. The success of this new theoretical framework highlights the combined effects of quasi-two-dimensional dynamics at synoptic scales (−3 slope) and three-dimensional turbulence-like small-scale chaotic flows (−5/3 slope) in dictating the error growth. It is proposed that this new framework could serve as a guide for understanding and estimating the predictability limit in the real world.

scholarly journals Comment on "Tropospheric temperature response to stratospheric ozone recovery in the 21st century" by Hu et al. (2011)

2012 ◽  
Vol 12 (5) ◽  
pp. 2533-2540 ◽  
Author(s):  
C. McLandress ◽  
J. Perlwitz ◽  
T. G. Shepherd
Keyword(s):  
Northern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Stratospheric Ozone ◽  
Three Dimensional ◽  
Temperature Response ◽  
Ocean Model ◽  
Tropospheric Temperature ◽  
Cmip3 Model ◽  
Incomplete Removal

Abstract. In a recent paper Hu et al. (2011) suggest that the recovery of stratospheric ozone during the first half of this century will significantly enhance free tropospheric and surface warming caused by the anthropogenic increase of greenhouse gases, with the effects being most pronounced in Northern Hemisphere middle and high latitudes. These surprising results are based on a multi-model analysis of CMIP3 model simulations with and without prescribed stratospheric ozone recovery. Hu et al. suggest that in order to properly quantify the tropospheric and surface temperature response to stratospheric ozone recovery, it is necessary to run coupled atmosphere-ocean climate models with stratospheric ozone chemistry. The results of such an experiment are presented here, using a state-of-the-art chemistry-climate model coupled to a three-dimensional ocean model. In contrast to Hu et al., we find a much smaller Northern Hemisphere tropospheric temperature response to ozone recovery, which is of opposite sign. We suggest that their result is an artifact of the incomplete removal of the large effect of greenhouse gas warming between the two different sets of models.

scholarly journals Transition to turbulence in an elliptic vortex

1996 ◽  
Vol 307 ◽  
pp. 43-62 ◽  
Author(s):  
T. S. Lundgren ◽  
N. N. Mansour
Keyword(s):  
Swirling Flow ◽  
Three Dimensional ◽  
Reynolds Numbers ◽  
Periodic Wave ◽  
Transition To Turbulence ◽  
Energy Spectra ◽  
Small Scale ◽  
Two Dimensional ◽  
Secondary Instabilities ◽  
Vortex Tubes

Stability and transition to turbulence are studied in a simple incompressible two-dimensional bounded swirling flow with a rectangular planform – a vortex in a box. This flow is unstable to three-dimensional disturbances. The instability takes the form of counter-rotating swirls perpendicular to the axis which bend the vortex into a periodic wave. As these swirls grow in amplitude the primary vorticity is compressed into thin vortex layers. These develop secondary instabilities which roll up into vortex tubes. In this way the flow attains a turbulent state which is populated by intense elongated vortex tubes and weaker vortex layers which spiral around them. The flow was computed at two Reynolds numbers by spectral methods with up to 2563 resolution. At the higher Reynolds number broad three-dimensional shell-averaged energy spectra are found with nearly a decade of Kolmogorov k−5/3 law and small-scale isotropy.

scholarly journals A Diagnosis of Excessive Mixing in Smagorinsky Subfilter-Scale Turbulent Kinetic Energy Models

2017 ◽  
Vol 74 (5) ◽  
pp. 1495-1511 ◽  
Author(s):  
Stephan R. de Roode ◽  
Harm J. J. Jonker ◽  
Bas J. H. van de Wiel ◽  
Victor Vertregt ◽  
Vincent Perrin
Keyword(s):  
Kinetic Energy ◽  
Prandtl Number ◽  
Turbulent Kinetic Energy ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Constant Length ◽  
Similarity Relations ◽  
Stable Conditions ◽  
Mixing Functions

Abstract Large-eddy simulation (LES) models are widely used to study atmospheric turbulence. The effects of small-scale motions that cannot be resolved need to be modeled by a subfilter-scale (SFS) model. The SFS contribution to the turbulent fluxes is typically significant in the surface layer. This study presents analytical solutions of the classical Smagorinsky SFS turbulent kinetic energy (TKE) model including a buoyancy flux contribution. Both a constant length scale and a stability-dependent one as proposed by Deardorff are considered. Analytical expressions for the mixing functions are derived and Monin–Obukhov similarity relations that are implicitly imposed by the SFS TKE model are diagnosed. For neutral and weakly stable conditions, observations indicate that the turbulent Prandtl number (PrT) is close to unity. However, based on observations in the convective boundary layer, a lower value for PrT is often applied in LES models. As a lower Prandtl number promotes a stronger mixing of heat, this may cause excessive mixing, which is quantified from a direct comparison of the mixing function as imposed by the SFS TKE model with empirical fits from field observations. For a strong stability, the diagnosed mixing functions for both momentum and heat are larger than observed. The problem of excessive mixing will be enhanced for anisotropic grids. The findings are also relevant for high-resolution numerical weather prediction models that use a Smagorinsky-type TKE closure.

scholarly journals Formulation of an ocean model for global climate simulations

2005 ◽  
Vol 2 (3) ◽  
pp. 165-246 ◽  
Author(s):  
S. M. Griffies ◽  
A. Gnanadesikan ◽  
K. W. Dixon ◽  
J. P. Dunne ◽  
R. Gerdes ◽  
...  
Keyword(s):  
Free Surface ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Three Dimensional ◽  
Coupled Model ◽  
Ocean Model ◽  
Tidal Mixing ◽  
The Arctic ◽  
Tracer Transport

Abstract. This paper summarizes the formulation of the ocean component to the Geophysical Fluid Dynamics Laboratory's (GFDL) coupled climate model used for the 4th IPCC Assessment (AR4) of global climate change. In particular, it reviews elements of ocean climate models and how they are pieced together for use in a state-of-the-art coupled model. Novel issues are also highlighted, with particular attention given to sensitivity of the coupled simulation to physical parameterizations and numerical methods. Features of the model described here include the following: (1) tripolar grid to resolve the Arctic Ocean without polar filtering, (2) partial bottom step representation of topography to better represent topographically influenced advective and wave processes, (3) more accurate equation of state, (4) three-dimensional flux limited tracer advection to reduce overshoots and undershoots, (5) incorporation of regional climatological variability in shortwave penetration, (6) neutral physics parameterization for representation of the pathways of tracer transport, (7) staggered time stepping for tracer conservation and numerical efficiency, (8) anisotropic horizontal viscosities for representation of equatorial currents, (9) parameterization of exchange with marginal seas, (10) incorporation of a free surface that accomodates a dynamic ice model and wave propagation, (11) transport of water across the ocean free surface to eliminate unphysical "virtual tracer flux" methods, (12) parameterization of tidal mixing on continental shelves.

Sign in / Sign up

Export Citation Format

Share Document