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.

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 On the deep convection events and Antarctic Bottom Water formation in ocean reanalysis products

2017 ◽  
Author(s):  
Wilton Aguiar ◽  
Mauricio M. Mata ◽  
Rodrigo Kerr
Keyword(s):  
General Circulation ◽  
Bottom Water ◽  
Deep Convection ◽  
General Circulation Models ◽  
Open Ocean ◽  
Weddell Sea ◽  
Antarctic Bottom Water ◽  
Ocean Reanalysis ◽  
Ocean General Circulation Models ◽  
Bottom Water Formation

Abstract. Deep convection in open ocean polynyas are common sources of error on the representation of Antarctic Bottom Water (AABW) formation in Ocean General Circulation Models. Even though those events are well described in non-assimilatory ocean simulations, recent appearance of open ocean polynya in Estimating the Circulation and Climate of the Ocean Phase II reanalysis product raises a question if this spurious event is also found in state-of-art reanalysis products. In order to answer this question, we evaluate how three recently released high-resolution ocean reanalysis form AABW in their simulations. We found that two of them (ECCO2 and SoSE) create AABW by open ocean deep convection events in Weddell Sea, showing that assimilation of sea ice has not been enough to avoid open ocean polynya appearance. The third reanalysis – My Ocean University Reading – actually creates AABW by a rather dynamically accurate mechanism, depicting both continental shelf convection, and exporting of Dense Shelf Water to open ocean. Although the accuracy of the AABW formation in this reanalysis allows an advance in represent this process, the differences found between the real ocean and the simulated one suggests that ocean reanalysis still need substantial improvements to accurately represent AABW formation.

scholarly journals Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies

2015 ◽  
Vol 1 (1) ◽  
pp. 29-44 ◽  
Author(s):  
R. Philbin ◽  
M. Jun
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Global Precipitation Climatology Project ◽  
Temperature Fields ◽  
Spatial Covariance ◽  
Proxy Data ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
Northern Latitudes ◽  
Environmental Prediction

Abstract. This study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational proxy data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis temperatures and Global Precipitation Climatology Project (GPCP) precipitation data. We model the joint distribution of these two fields with a parsimonious bivariate Matérn spatial covariance model, accounting for the two fields' spatial cross-correlation as well as their own smoothnesses. We fit output from each AOGCM (30-year seasonal averages from 1981 to 2010) to a statistical model on each of 21 land regions. Both variance and smoothness values agree for both fields over all latitude bands except southern mid-latitudes. Our results imply that temperature fields have smaller smoothness coefficients than precipitation fields, while both have decreasing smoothness coefficients with increasing latitude. Models predict fields with smaller smoothness coefficients than observational proxy data for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most GCMs in mid-latitudes. Model correlation estimates agree well with those for observational proxy data for Australia, at high northern latitudes across North America, Europe and Asia, as well as across the Sahara, India, and Southeast Asia, but elsewhere, little consistent agreement exists.

scholarly journals Assimilating synthetic Biogeochemical-Argo and ocean colour observations into a global ocean model to inform observing system design

2021 ◽  
Vol 18 (2) ◽  
pp. 509-534
Author(s):  
David Ford
Keyword(s):  
Global Scale ◽  
Ocean Model ◽  
Point Of View ◽  
Global Ocean ◽  
Ocean Colour ◽  
Ocean Reanalysis ◽  
Argo Data ◽  
Argo Floats ◽  
Improved Model ◽  
The Impact

Abstract. A set of observing system simulation experiments was performed. This assessed the impact on global ocean biogeochemical reanalyses of assimilating chlorophyll from remotely sensed ocean colour and in situ observations of chlorophyll, nitrate, oxygen, and pH from a proposed array of Biogeochemical-Argo (BGC-Argo) floats. Two potential BGC-Argo array distributions were tested: one for which biogeochemical sensors are placed on all current Argo floats and one for which biogeochemical sensors are placed on a quarter of current Argo floats. Assimilating BGC-Argo data greatly improved model results throughout the water column. This included surface partial pressure of carbon dioxide (pCO2), which is an important output of reanalyses. In terms of surface chlorophyll, assimilating ocean colour effectively constrained the model, with BGC-Argo providing no added benefit at the global scale. The vertical distribution of chlorophyll was improved by assimilating BGC-Argo data. Both BGC-Argo array distributions gave benefits, with greater improvements seen with more observations. From the point of view of ocean reanalysis, it is recommended to proceed with development of BGC-Argo as a priority. The proposed array of 1000 floats will lead to clear improvements in reanalyses, with a larger array likely to bring further benefits. The ocean colour satellite observing system should also be maintained, as ocean colour and BGC-Argo will provide complementary benefits.

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 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.

Experiences with a coupled global model

1989 ◽  
Vol 329 (1604) ◽  
pp. 275-288 ◽  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Degrees Of Freedom ◽  
Coupled Model ◽  
General Circulation Models ◽  
Ocean Model ◽  
Atmosphere Model ◽  
Component Models ◽  
Ice Model ◽  
The Tropical Pacific

General circulation models of the atmosphere have been used to investigate the climate response to factors such as the changing concentration of CO 2 . Their usefulness is restricted by the need to specify the sea surface temperature. Partial solutions to this problem exist, such as adding a model of the ocean mixed layer to the atmosphere model, but these cannot simulate the response of the ocean heat transport to changes in the atmospheric circulation. Only a coupled atmosphere—ocean-sea-ice model can represent the mechanisms that determine the climate on time scales of decades. A coupled atmosphere-ocean-sea-ice model has been developed at the Meteorological Office. This paper describes the ocean and sea-ice components of that model and some of the characteristics of the ocean model when driven by observed fluxes of heat, fresh water, and momentum during a long spin-up experiment. Aspects of a four-year integration of the coupled model are discussed. Many factors contribute to the simulation of the coupled model. Not only are the characteristics of the component models present, but the additional degrees of freedom introduced by the removal of fixed boundary conditions at the ocean surface also introduce new features into the simulation. Particular features that result from the interaction of the models used in the simulations described in this paper include a feedback between the sea-ice model and the simulations of the atmosphere model at high latitudes, and a warming of the tropical Pacific.

scholarly journals Assimilating synthetic Biogeochemical-Argo and ocean colour observations into a global ocean model to inform observing system design

2020 ◽  
Author(s):  
David Ford
Keyword(s):  
Ocean Model ◽  
Point Of View ◽  
Global Ocean ◽  
Ocean Colour ◽  
Ocean Reanalysis ◽  
Argo Data ◽  
Argo Floats ◽  
Variable Surface ◽  
Added Benefit ◽  
The Impact

Abstract. A set of observing system simulation experiments has been performed to explore the impact on global ocean biogeochemical reanalyses of assimilating chlorophyll from remotely sensed ocean colour, and assess the potential impact of assimilating in situ observations of chlorophyll, nitrate, oxygen, and pH from a proposed array of Biogeochemical-Argo (BGC-Argo) floats. Two different potential BGC-Argo array distributions were tested: one where biogeochemical sensors are placed on all current Argo floats, and one where biogeochemical sensors are placed on a quarter of current Argo floats. This latter approximately corresponds to the proposed BGC-Argo array of 1000 floats. Different strategies for updating model variables when assimilating ocean colour were assessed. All similarly improved the assimilated variable surface chlorophyll, but had a mixed impact on the wider ecosystem and carbon cycle, degrading some key variables of interest. Assimilating BGC-Argo data gave no added benefit over ocean colour in terms of simulating surface chlorophyll, but for most other variables, including sub-surface chlorophyll, adding BGC-Argo greatly improved results throughout the water column. This included surface partial pressure of carbon dioxide (pCO2), which was not assimilated but is an important output of reanalyses. Both BGC-Argo array distributions gave benefits, with greater improvements seen with more observations. From the point of view of ocean reanalysis, it is recommended to proceed with development of BGC-Argo as a priority. The proposed array of 1000 floats will lead to clear improvements in reanalyses, with a larger array likely to bring further benefits. The ocean colour satellite observing system should also be maintained, as ocean colour and BGC-Argo will provide complementary benefits. There is also much potential to improve the use of existing observations, particularly in terms of multivariate balancing, through improving assimilation methodologies.

scholarly journals Representing El Niño in Coupled Ocean–Atmosphere GCMs: The Dominant Role of the Atmospheric Component

2004 ◽  
Vol 17 (24) ◽  
pp. 4623-4629 ◽  
Author(s):  
E. Guilyardi ◽  
S. Gualdi ◽  
J. Slingo ◽  
A. Navarra ◽  
P. Delecluse ◽  
...  
Keyword(s):  
El Niño ◽  
General Circulation ◽  
State Of The Art ◽  
El Nino ◽  
Dominant Role ◽  
Power Spectra ◽  
General Circulation Models ◽  
Coupled Models ◽  
Model Improvement

Abstract A systematic modular approach to investigate the respective roles of the ocean and atmosphere in setting El Niño characteristics in coupled general circulation models is presented. Several state-of-the-art coupled models sharing either the same atmosphere or the same ocean are compared. Major results include 1) the dominant role of the atmosphere model in setting El Niño characteristics (periodicity and base amplitude) and errors (regularity) and 2) the considerable improvement of simulated El Niño power spectra—toward lower frequency—when the atmosphere resolution is significantly increased. Likely reasons for such behavior are briefly discussed. It is argued that this new modular strategy represents a generic approach to identifying the source of both coupled mechanisms and model error and will provide a methodology for guiding model improvement.

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