scholarly journals Tropical extra-tropical thermocline water mass exchanges in the Community Climate Model v.3 Part I: the Atlantic Ocean

Ocean Science ◽  
2006 ◽  
Vol 2 (2) ◽  
pp. 137-146 ◽  
Author(s):  
I. Wainer ◽  
A. Lazar ◽  
A. Solomon
Keyword(s):  
Atlantic Ocean ◽  
Numerical Experiment ◽  
Numerical Experiments ◽  
Climate Model ◽  
Water Mass ◽  
Coupled Model ◽  
Atmospheric Component ◽  
The Third ◽  
Simulation Results ◽  
Fully Coupled

Abstract. The climatological annual mean tropical-extra-tropical pathways of thermocline waters in the Atlantic Ocean are investigated with the NCAR CCSM numerical coupled model. Results from three numerical experiments are analyzed: Two are fully coupled runs with different spatial resolution (T42 and T85) for the atmospheric component. The third numerical experiment is an ocean-only run forced by NCEP winds and fluxes. Results show that the different atmospheric resolutions have a significant impact on the subduction pathways in the Atlantic because of how the wind field is represented. These simulation results also show that the water subducted at the subtropics reaching the EUC is entirely from the South Atlantic. The coupled model ability to simulate the STCs is discussed.

scholarly journals Tropical Extra-tropical thermocline water mass exchanges in the community climate model v.3 Part I: the Atlantic Ocean

2006 ◽  
Vol 3 (3) ◽  
pp. 55-84
Author(s):  
I. Wainer ◽  
A. Lazar ◽  
A. Solomon
Keyword(s):  
Atlantic Ocean ◽  
Numerical Experiment ◽  
Numerical Experiments ◽  
Climate Model ◽  
Water Mass ◽  
Coupled Model ◽  
Atmospheric Component ◽  
The Third ◽  
Simulation Results ◽  
Fully Coupled

Abstract. The NCAR CCSM numerical coupled model is used to understand the tropical-extra-tropical pathways of thermocline waters in the Atlantic Ocean. Climatological annual mean simulation results from three numerical experiments are analyzed. Two are fully coupled runs with different spatial resolution (T42 and T85) for the atmospheric component. The third numerical experiment is an ocean-only run forced by NCEP winds and fluxes. Results show that the different atmospheric resolutions have a significant impact on the subduction pathways in the Atlantic because of how the wind field is represented. These simulation results also show that the water subducted at the subtropics reaching the EUC is entirely from the South Atlantic. The coupled model ability to simulate the STCs is discussed.

scholarly journals Explicit silicate cycling in the Kiel Marine Biogeochemistry Model, version 3 (KMBM3) embedded in the UVic ESCM version 2.9

2020 ◽  
Author(s):  
Karin Kvale ◽  
David P. Keller ◽  
Wolfgang Koeve ◽  
Katrin J. Meissner ◽  
Chris Somes ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Primary Production ◽  
Large Scale ◽  
Climate Model ◽  
Net Primary Production ◽  
Coupled Model ◽  
Co2 Concentration ◽  
Ecosystem Model ◽  
New Model ◽  
Fully Coupled

Abstract. We describe and test a new model of biological marine silicate cycling, implemented in the University of Victoria Earth System Climate Model (UVic ESCM) version 2.9. This new model adds diatoms, which are a key aspect of the biological carbon pump, to an existing ecosystem model. The new model performs well against important ocean biogeochemical indicators and captures the large-scale features of the marine silica cycle. Furthermore it is computationally efficient, allowing both fully-coupled, long-timescale transient simulations, as well as "offline" transport matrix spinups. We assess the fully-coupled model against modern ocean observations, the historical record since 1960, and a business-as-usual atmospheric CO2 forcing to the year 2300. The model simulates a global decline in net primary production (NPP) of 1.3 % having occurred since the 1960s, with the strongest declines in the tropics, northern mid-latitudes, and Southern Ocean. The simulated global decline in NPP reverses after the year 2100 (forced by the extended RCP CO2 concentration scenario), and NPP returns to pre-industrial rates by 2300. This recovery is dominated by increasing primary production in the Southern Ocean, mostly by calcifying phytoplankton. Large increases in calcifying phytoplankton in the Southern Ocean offset a decline in the low latitudes, producing a global net calcite export in 2300 that varies only slightly from pre-industrial rates. Diatoms migrate southward in our simulations, following the receding Antarctic ice front, but are out-competed by calcifiers across most of their pre-industrial Southern Ocean habitat. Global opal export production thus drops to 50 % of its pre-industrial value by 2300. Model nutrients phosphate, silicate, and nitrate build up along the Southern Ocean particle export pathway, but dissolved iron (for which ocean sources are held constant) increases in the upper ocean. This different behaviour of iron is attributed to a reduction of low-latitude NPP (and consequently, a reduction in both uptake and export and particle, including calcite, scavenging), an increase in seawater temperatures (raising the solubility of particle forms), and stratification that "traps" the iron near the surface. These results are meant to serve as a baseline for sensitivity assessments to be undertaken with this model in the future.

System Design and Evaluation of Coupled Ensemble Data Assimilation for Global Oceanic Climate Studies

2007 ◽  
Vol 135 (10) ◽  
pp. 3541-3564 ◽  
Author(s):  
S. Zhang ◽  
M. J. Harrison ◽  
A. Rosati ◽  
A. Wittenberg
Keyword(s):  
Twentieth Century ◽  
Data Assimilation ◽  
Climate Variability ◽  
Climate Model ◽  
Heat Content ◽  
Coupled Model ◽  
Atmospheric Temperature ◽  
Meridional Overturning Circulation ◽  
Climate Trends ◽  
Fully Coupled

Abstract A fully coupled data assimilation (CDA) system, consisting of an ensemble filter applied to the Geophysical Fluid Dynamics Laboratory’s global fully coupled climate model (CM2), has been developed to facilitate the detection and prediction of seasonal-to-multidecadal climate variability and climate trends. The assimilation provides a self-consistent, temporally continuous estimate of the coupled model state and its uncertainty, in the form of discrete ensemble members, which can be used directly to initialize probabilistic climate forecasts. Here, the CDA is evaluated using a series of perfect model experiments, in which a particular twentieth-century simulation—with temporally varying greenhouse gas and natural aerosol radiative forcings—serves as a “truth” from which observations are drawn, according to the actual ocean observing network for the twentieth century. These observations are then assimilated into a coupled model ensemble that is subjected only to preindustrial forcings. By examining how well this analysis ensemble reproduces the “truth,” the skill of the analysis system in recovering anthropogenically forced trends and natural climate variability is assessed, given the historical observing network. The assimilation successfully reconstructs the twentieth-century ocean heat content variability and trends in most locations. The experiments highlight the importance of maintaining key physical relationships among model fields, which are associated with water masses in the ocean and geostrophy in the atmosphere. For example, when only oceanic temperatures are assimilated, the ocean analysis is greatly improved by incorporating the temperature–salinity covariance provided by the analysis ensemble. Interestingly, wind observations are more helpful than atmospheric temperature observations for constructing the structure of the tropical atmosphere; the opposite holds for the extratropical atmosphere. The experiments indicate that the Atlantic meridional overturning circulation is difficult to constrain using the twentieth-century observational network, but there is hope that additional observations—including those from the newly deployed Argo profiles—may lessen this problem in the twenty-first century. The challenges for data assimilation of model systematic biases and evolving observing systems are discussed.

scholarly journals Free and Forced Variability of the Tropical Atlantic Ocean: Role of the Wind–Evaporation–Sea Surface Temperature Feedback

2010 ◽  
Vol 23 (22) ◽  
pp. 5958-5977 ◽  
Author(s):  
Salil Mahajan ◽  
R. Saravanan ◽  
Ping Chang
Keyword(s):  
Atlantic Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Model ◽  
Coupled Model ◽  
Sea Surface ◽  
Tropical Atlantic ◽  
Wes Feedback ◽  
Meridional Mode

Abstract The role of the wind–evaporation–sea surface temperature (WES) feedback in the low-frequency natural variability of the tropical Atlantic is studied using an atmospheric global climate model—the NCAR Community Climate Model, version 3 (CCM3)—thermodynamically coupled to a slab ocean model (SOM). The coupled model is modified to suppress the WES feedback and is compared to a control run. Singular value decomposition (SVD) analysis over the tropical Atlantic reveals that the coupled meridional mode of the Atlantic Ocean is amplified in the presence of the WES feedback. In its absence, the meridional mode still exists, but with a weaker amplitude. A feedback mechanism that involves the near-surface specific humidity is proposed to sustain the weaker Atlantic meridional mode in the absence of the WES feedback. Similar analysis of coupled model integrations when forced with an artificial El Niño–Southern Oscillation (ENSO)-like SST cycle in the Pacific reveals that in the presence of the WES feedback, the meridional mode is the preferred mode of response of the tropical Atlantic to ENSO forcing. In the absence of the WES feedback, the tropical Atlantic response is unlike the meridional mode and the effects of tropospheric warming and subsidence dominate. Regression analysis over the tropical Atlantic reveals that the meridional mode response to ENSO peaks in the spring and begins to decay in the fall in the coupled model in the presence of the WES feedback. The WES feedback also appears to be responsible for the northward migration of the ITCZ during ENSO events.

scholarly journals Three-Dimensional Temperature Field Change in the South China Sea during Typhoon Kai-Tak (1213) Based on a Fully Coupled Atmosphere–Wave–Ocean Model

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 140 ◽  
Author(s):  
Zhiyuan Wu ◽  
Changbo Jiang ◽  
Jie Chen ◽  
Yuannan Long ◽  
Bin Deng ◽  
...  
Keyword(s):  
Temperature Field ◽  
Heat Exchange ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coupled Model ◽  
Ocean Model ◽  
Sea Surface ◽  
Sea Temperature ◽  
Simulation Results ◽  
Fully Coupled

Studying the sea–air interaction between the upper ocean and typhoons is crucial to improve our understanding of heat and momentum exchange between the atmosphere and the ocean. There is a strong heat flux exchange between the atmosphere and the ocean during the impact of a typhoon, and the physical fields, such as the wind field, wave field, flow field, and SST field, also interact with each other. A fully coupled Atmosphere–Wave–Ocean model in the South China Sea was established by the mesoscale atmospheric model WRF, wave model SWAN, and the regional ocean model ROMS based on the COAWST model system. Typhoon Kai-tak was simulated using this fully coupled model and some other coupled schemes. In this paper, the variation of sea surface temperature (SST) and ocean subsurface temperature caused by Typhoon Kai-tak is analyzed by the fully coupled model, and the basic characteristics of the response of the upper ocean to the typhoon are given. The simulation results demonstrate that the fully coupled WRF-SWAN-ROMS model shows that the typhoon passes through the sea with obvious cooling. In the cold eddy region, the sea surface temperature cools 4 to 5 °C, and the cooling zone is concentrated on the right side of the track. The change of sea surface temperature lags more than 12 h behind the change of sea surface height. The decrease of SST on the left side of the track was relatively small: ranging from 1.5 to 2.5 °C. The disturbance of typhoon causes the subsurface water to surge to the surface, changes the temperature distribution of the surface, and causes the mixing layer to deepen about 40 m to 60 m. The simulation results reveal the temporal and spatial distribution of sea temperature and mixed layer depth. The sea surface temperature field has an asymmetrical distribution in space and has a lag in time. The heat exchange at the air–sea interface is very strong under the influence of the typhoon. The heat exchange between the air and sea is divided into latent heat and sensible heat, and the latent heat generated by water vapor evaporation plays a dominant role in the heat exchange at the air–sea interface, which shows that the heat carried by the vaporization of the sea surface is one of the important factors for the decrease of sea temperature under the influence of the typhoon.

Stress self-sensing in Amplified Piezoelectric Actuators through a fully-coupled model of hysteresis

2020 ◽  
Vol 579 ◽  
pp. 411894
Author(s):  
Valerio Apicella ◽  
Carmine Stefano Clemente ◽  
Daniele Davino ◽  
Damiano Leone ◽  
Ciro Visone
Keyword(s):  
Coupled Model ◽  
Piezoelectric Actuators ◽  
Fully Coupled

scholarly journals Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhili Wang ◽  
Lei Lin ◽  
Yangyang Xu ◽  
Huizheng Che ◽  
Xiaoye Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Impact Analysis ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern China ◽  
Coupled Model ◽  
Regional Climate Change ◽  
Anthropogenic Aerosol ◽  
Wide Range

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

scholarly journals Limits of reproducibility and hydrodynamic noise in atmospheric regional modelling

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Beate Geyer ◽  
Thomas Ludwig ◽  
Hans von Storch
Keyword(s):  
Regional Climate Model ◽  
Computer Architecture ◽  
Climate Model ◽  
Initial Conditions ◽  
Regional Climate ◽  
Quality Criterion ◽  
Dynamic State ◽  
Regional Modelling ◽  
Simulation Results ◽  
Mathematical Operations

AbstractReproducibility of research results is a fundamental quality criterion in science; thus, computer architecture effects on simulation results must be determined. Here, we investigate whether an ensemble of runs of a regional climate model with the same code on different computer platforms generates the same sequences of similar and dissimilar weather streams when noise is seeded using different initial states of the atmosphere. Both ensembles were produced using a regional climate model named COSMO-CLM5.0 model with ERA-Interim forcing. Divergent phase timing was dependent on the dynamic state of the atmosphere and was not affected by noise seeded by changing computers or initial model state variations. Bitwise reproducibility of numerical results is possible with such models only if everything is fixed (i.e., computer, compiler, chosen options, boundary values, and initial conditions) and the order of mathematical operations is unchanged between program runs; otherwise, at best, statistically identical simulation results can be expected.

scholarly journals The Interpretation and Use of Biases in Decadal Climate Predictions

2014 ◽  
Vol 27 (8) ◽  
pp. 2931-2947 ◽  
Author(s):  
Ed Hawkins ◽  
Buwen Dong ◽  
Jon Robson ◽  
Rowan Sutton ◽  
Doug Smith
Keyword(s):  
Climate Model ◽  
Coupled Model ◽  
Internal Variability ◽  
Time Dependent ◽  
Start Time ◽  
Transient Climate Response ◽  
Global Mean Temperature ◽  
Decadal Climate ◽  
Highly Correlated ◽  
Hadley Centre

Abstract Decadal climate predictions exhibit large biases, which are often subtracted and forgotten. However, understanding the causes of bias is essential to guide efforts to improve prediction systems, and may offer additional benefits. Here the origins of biases in decadal predictions are investigated, including whether analysis of these biases might provide useful information. The focus is especially on the lead-time-dependent bias tendency. A “toy” model of a prediction system is initially developed and used to show that there are several distinct contributions to bias tendency. Contributions from sampling of internal variability and a start-time-dependent forcing bias can be estimated and removed to obtain a much improved estimate of the true bias tendency, which can provide information about errors in the underlying model and/or errors in the specification of forcings. It is argued that the true bias tendency, not the total bias tendency, should be used to adjust decadal forecasts. The methods developed are applied to decadal hindcasts of global mean temperature made using the Hadley Centre Coupled Model, version 3 (HadCM3), climate model, and it is found that this model exhibits a small positive bias tendency in the ensemble mean. When considering different model versions, it is shown that the true bias tendency is very highly correlated with both the transient climate response (TCR) and non–greenhouse gas forcing trends, and can therefore be used to obtain observationally constrained estimates of these relevant physical quantities.

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