scholarly journals ENSO Predictability of a Fully Coupled GCM Model Using Singular Vector Analysis

2006 ◽  
Vol 19 (14) ◽  
pp. 3361-3377 ◽  
Author(s):  
Youmin Tang ◽  
Richard Kleeman ◽  
Sonya Miller
Keyword(s):  
Singular Vector ◽  
Climate Model ◽  
Global Climate Model ◽  
Heat Content ◽  
Enso Cycle ◽  
Coupled Models ◽  
Error Norm ◽  
Singular Vectors ◽  
Enso Predictability ◽  
Fully Coupled

Abstract Using a recently developed method of computing climatically relevant singular vectors (SVs), the error growth properties of ENSO in a fully coupled global climate model are investigated. In particular, the authors examine in detail how singular vectors are influenced by the phase of ENSO cycle—the physical variable under consideration as well as the error norm deployed. Previous work using SVs for studying ENSO predictability has been limited to intermediate or hybrid coupled models. The results show that the singular vectors share many of the properties already seen in simpler models. Thus, for example, the singular vector spectrum is dominated by one fastest growing member, regardless of the phase of ENSO cycle and the variable of perturbation or the error norm; in addition the growth rates of the singular vectors are very sensitive to the phase of the ENSO cycle, the variable of perturbation, and the error norm. This particular CGCM also displays some differences from simpler models; thus subsurface temperature optimal patterns are strongly sensitive to the phase of ENSO cycle, and at times an east–west dipole in the eastern tropical Pacific basin is seen. This optimal pattern also appears for SST when the error norm is defined using Niño-4. Simpler models consistently display a single-sign equatorial signature in the subsurface corresponding perhaps to the Wyrtki buildup of heat content before a warm event. Some deficiencies in the CGCM and their possible influences on SV growth are also discussed.

scholarly journals Decadal Prediction of the Sahelian Precipitation in CMIP5 Simulations

2013 ◽  
Vol 26 (19) ◽  
pp. 7708-7719 ◽  
Author(s):  
Marco Gaetani ◽  
Elsa Mohino
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
System Model ◽  
Low Resolution ◽  
Coupled Models ◽  
Climate System Model ◽  
Model Version ◽  
Coupled Global Climate Model

Abstract In this study the capability of eight state-of-the-art ocean–atmosphere coupled models in predicting the monsoonal precipitation in the Sahel on a decadal time scale is assessed. To estimate the importance of the initialization, the predictive skills of two different CMIP5 experiments are compared, a set of 10 decadal hindcasts initialized every 5 years in the period 1961–2009 and the historical simulations in the period 1961–2005. Results indicate that predictive skills are highly model dependent: the Fourth Generation Canadian Coupled Global Climate Model (CanCM4), Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5 (CNRM-CM5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR) models show improved skill in the decadal hindcasts, while the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) is skillful in both the decadal and historical experiments. The Beijing Climate Center, Climate System Model, version 1.1 (BCC-CSM1.1), Hadley Centre Coupled Model, version 3 (HadCM3), L'Institut Pierre-Simon Laplace Coupled Model, version 5, coupled with NEMO, low resolution (IPSL-CM5A-LR), and Meteorological Research Institute Coupled Atmosphere–Ocean General Circulation Model, version 3 (MRI-CGCM3) models show insignificant or no skill in predicting the Sahelian precipitation. Skillful predictions are produced by models properly describing the SST multidecadal variability and the initialization appears to play an important role in this respect.

A Gaussian process emulator for simulating ice sheet-climate interactions on a multi-million year timescale

2020 ◽  
Author(s):  
Jonas Van Breedam ◽  
Philippe Huybrechts ◽  
Michel Crucifix
Keyword(s):  
Gaussian Process ◽  
Climate Model ◽  
Ice Sheet ◽  
Climate System ◽  
Lapse Rate ◽  
Coupled Models ◽  
Climate Interactions ◽  
Coupling Time ◽  
Fully Coupled ◽  
Gaussian Process Emulator

<p>Fully coupled state-of-the-art Atmosphere-Ocean General Circulation Models are the best tool to investigate feedbacks between the different components of the climate system on a decadal to centennial timescale. On millennial to multi-millennial timescales, Earth System Models of Intermediate Complexity are used to explore the feedbacks in the climate system between the ice sheets, the atmosphere and the ocean. Those fully coupled models, even at coarser resolution, are computationally very expensive and other techniques have been proposed to simulate ice sheet-climate interactions on a million-year timescale. The asynchronous coupling technique proposes to run a climate model for a few decades and subsequently an ice sheet model for a few millennia. Another, more efficient method is the use of a matrix look-up table where climate model runs are performed for end-members and intermediate climatic states are linearly interpolated.</p><p>In this study, a novel coupling approach is presented where a Gaussian Process emulator applied to the climate model HadSM3 is coupled to the ice sheet model AISMPALEO. We have tested the sensitivity of the formulation of the ice sheet parameter and of the coupling time to the evolution of the ice sheet over time. Additionally, we used different lapse rate adjustments between the relatively coarse climate model and the much finer ice sheet model topography. It is shown that the ice sheet evolution over a million year timescale is strongly sensitive to the choice of the coupling time and to the implementation of the lapse rate adjustment. With the new coupling procedure, we provide a more realistic and computationally efficient framework for ice sheet-climate interactions on a multi-million year timescale.</p><p> </p>

scholarly journals Optimal Forcing Patterns for Coupled Models of ENSO

2006 ◽  
Vol 19 (18) ◽  
pp. 4683-4699 ◽  
Author(s):  
Andrew M. Moore ◽  
Javier Zavala-Garay ◽  
Youmin Tang ◽  
Richard Kleeman ◽  
Anthony T. Weaver ◽  
...  
Keyword(s):  
Singular Vector ◽  
Southern Oscillation ◽  
Coupled System ◽  
Effective Dimension ◽  
Coupled Models ◽  
Singular Vectors ◽  
Interaction Processes ◽  
Optimal Excitation ◽  
Single Pattern ◽  
Time Invariant

Abstract The optimal forcing patterns for El Niño–Southern Oscillation (ENSO) are examined for a hierarchy of hybrid coupled models using generalized stability theory. Specifically two cases are considered: one where the forcing is stochastic in time, and one where the forcing is time independent. The optimal forcing patterns in these two cases are described by the stochastic optimals and forcing singular vectors, respectively. The spectrum of stochastic optimals for each model was found to be dominated by a single pattern. In addition, the dominant stochastic optimal structure is remarkably similar to the forcing singular vector, and to the dominant singular vectors computed in a previous related study using a subset of the same models. This suggests that irrespective of whether the forcing is in the form of an impulse, is time invariant, or is stochastic in nature, the optimal excitation for the eigenmode that describes ENSO in each model is the same. The optimal forcing pattern, however, does vary from model to model, and depends on air–sea interaction processes. Estimates of the stochastic component of forcing were obtained from atmospheric analyses and the projection of the dominant optimal forcing pattern from each model onto this component of the forcing was computed. It was found that each of the optimal forcing patterns identified may be present in nature and all are equally likely. The existence of a dominant optimal forcing pattern is explored in terms of the effective dimension of the coupled system using the method of balanced truncation, and was found to be O(1) for the models used here. The implications of this important result for ENSO prediction and predictability are discussed.

scholarly journals An Energy Conservation Analysis of Ocean Drift in the CMIP5 Global Coupled Models*

2016 ◽  
Vol 29 (5) ◽  
pp. 1639-1653 ◽  
Author(s):  
Will Hobbs ◽  
Matthew D. Palmer ◽  
Didier Monselesan
Keyword(s):  
Energy Budget ◽  
Climate Model ◽  
Heat Content ◽  
Ocean Model ◽  
Future Climate Change ◽  
Energy Budgets ◽  
State Variables ◽  
Coupled Models ◽  
Significant Disagreement ◽  
Climate Model Simulations

Abstract Climate model simulations of changes to Earth’s energy budget are fundamental to improve understanding of both historical and future climate change. However, coupled models are prone to “drift” (i.e., they contain spurious unforced trends in state variables) due to incomplete spinup or nonclosure of the energy budget. This work assesses the globally integrated energy budgets of 25 models in phase 5 of CMIP (CMIP5). It is shown that for many of the models there is a significant disagreement between ocean heat content changes and net top-of-atmosphere radiation. The disagreement is largely time-constant and independent of forcing scenario. Furthermore, most of the nonconservation seems to occur as a result of energy leaks external to the ocean model realm. After drift correction, the time-varying energy budget is consistent at decadal time scales, and model responses to climate forcing are not sensitive to the magnitude of their drift. This demonstrates that, although drift terms can be significant, model output can be corrected post hoc without biasing results.

Simulating Interactive Ice Sheets in the Multi-Resolution AWI-ESM: A case study using the SCOPE Coupler

2021 ◽  
Author(s):  
Paul Gierz ◽  
Lars Ackermann ◽  
Christian Rodehacke ◽  
Uta Krebs-Kanzow ◽  
Christian Stepanek ◽  
...  
Keyword(s):  
Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Global Ocean ◽  
Earth System ◽  
Last Interglacial ◽  
Ice Shelf ◽  
Coupled Models ◽  
Fully Coupled ◽  
Paleoclimate Studies

<p>Interactions between the climate and the cryosphere have the potential to induce strong non-linear transitions in the Earth's climate. These interactions influence both the atmospheric circulation, by changing the ice sheet's geometry, as well as the oceanic circulation, by modification of the water mass properties. Furthermore, the waxing and waning of large continental ice sheets influences the global albedo, altering the energy balance of the Earth System and inducing climate-ice sheet feedbacks on a global scale as evident in Pleistocene glacial-interglacial cycles. To date, few fully<br>comprehensive models exist, that do not only contain a coupled atmosphere/land/ocean component, but also consider interactive cryosphere physics. Yet, on glacial-interglacial and tectonic time scales, as well as in the Anthropocene, ice sheets are not in equilibrium with the climate, and prescribed fixed ice sheet representations in the model can principally be only an approximation to reality. Only climate models, that contain interactive ice sheets, can produce simulations of the Earth's climate which include all feedbacks and processes related to atmosphere-land-ocean-ice interactions. Previous fully coupled models were limited either by low spatial resolution or an incomplete representation of ice sheet processes, such as iceberg calving, surface ablation processes, and ocean/ice-shelf interactions. Here, we present the newly developed AWI-Earth System Model (AWI-ESM), which tackles some of these problems. Our modelling toolbox is based on the AWI-climate model, including atmosphere and vegetation components suitable for paleoclimate studies, a multi-resolution global ocean component which can be refined to simulate regions of interest at high resolution, and an ice sheet component suitable for simulating both ice sheet and ice shelf dynamics and thermodynamics. We describe the currently implemented coupling between these components, present first results for the Mid-Holocene and Last Interglacial, and introduce further ideas for scientific applications for both future and past climate states with a focus on the Northern Hemisphere. Finally, we provide an outlook on the potential of such fully coupled Earth System models in improving representation of climate-ice sheet feedbacks in future paleoclimate studies with this model.</p>

Multiyear predictability of extratropical North Atlantic sea surface temperatures in hindcasts initialized with wind stress anomalies

2020 ◽  
Author(s):  
Annika Reintges ◽  
Mojib Latif ◽  
Mohammad Hadi Bordbar ◽  
Wonsun Park
Keyword(s):  
Wind Stress ◽  
North Atlantic ◽  
Climate Model ◽  
Initial Conditions ◽  
Global Climate ◽  
Global Climate Model ◽  
Heat Content ◽  
Meridional Overturning Circulation ◽  
Sea Surface ◽  
Sst Anomalies

<p>Multiyear to decadal predictability of the North Atlantic sea surface temperature (SST) is commonly attributed to buoyancy-forced changes of the Atlantic Meridional Overturning Circulation and associated poleward heat transport. Here we investigate the role of the wind stress anomalies in decadal hindcasts for the prediction of annual extratropical North Atlantic SST anomalies. A global climate model is forced by ERA-interim wind stress anomalies over the period 1979-2017. The resulting climate states serve as initial conditions for the decadal hindcasts. We find significant skill in predicting annual SST anomalies over the central extratropical North Atlantic with anomaly correlation coefficients exceeding 0.6 at lead times of 4 to 7 years. The skill of annual SSTs is basically insensitive to the calendar month of initialization. This skill is potentially linked to a gyre-driven upper-ocean heat content anomaly that leads anomalous SSTs by several years.</p>

Estimating Climatically Relevant Singular Vectors for Decadal Predictions of the Atlantic Ocean

2011 ◽  
Vol 24 (1) ◽  
pp. 109-123 ◽  
Author(s):  
Ed Hawkins ◽  
Rowan Sutton
Keyword(s):  
Atlantic Ocean ◽  
Climate Model ◽  
Initial Conditions ◽  
Global Climate ◽  
Global Climate Model ◽  
Meridional Overturning Circulation ◽  
Small Perturbations ◽  
Singular Vectors ◽  
Meridional Overturning ◽  
Ocean Observing

Abstract A key aspect in designing an efficient decadal prediction system is ensuring that the uncertainty in the ocean initial conditions is sampled optimally. Here one strategy for addressing this issue is considered by investigating the growth of optimal perturbations in the third climate configuration of the Met Office Unified Model (HadCM3) global climate model (GCM). More specifically, climatically relevant singular vectors (CSVs)—the small perturbations of which grow most rapidly for a specific set of initial conditions—are estimated for decadal time scales in the Atlantic Ocean. It is found that reliable CSVs can be estimated by running a large ensemble of integrations of the GCM. Amplification of the optimal perturbations occurs for more than 10 yr, and possibly up to 40 yr. The identified regions for growing perturbations are found to be in the far North Atlantic, and these perturbations cause amplification through an anomalous meridional overturning circulation response. Additionally, this type of analysis potentially informs the design of future ocean observing systems by identifying the sensitive regions where small uncertainties in the ocean state can grow maximally. Although these CSVs are expensive to compute, ways in which the process could be made more efficient in the future are identified.

scholarly journals Implications of global warming for the climate of African rainforests

2013 ◽  
Vol 368 (1625) ◽  
pp. 20120298 ◽  
Author(s):  
Rachel James ◽  
Richard Washington ◽  
David P. Rowell
Keyword(s):  
Global Warming ◽  
Amazon Basin ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Temperature ◽  
Congo Basin ◽  
Coupled Models ◽  
Temperature And Precipitation ◽  
Equatorial Africa

African rainforests are likely to be vulnerable to changes in temperature and precipitation, yet there has been relatively little research to suggest how the regional climate might respond to global warming. This study presents projections of temperature and precipitation indices of relevance to African rainforests, using global climate model experiments to identify local change as a function of global temperature increase. A multi-model ensemble and two perturbed physics ensembles are used, one with over 100 members. In the east of the Congo Basin, most models (92%) show a wet signal, whereas in west equatorial Africa, the majority (73%) project an increase in dry season water deficits. This drying is amplified as global temperature increases, and in over half of coupled models by greater than 3% per °C of global warming. Analysis of atmospheric dynamics in a subset of models suggests that this could be partly because of a rearrangement of zonal circulation, with enhanced convection in the Indian Ocean and anomalous subsidence over west equatorial Africa, the Atlantic Ocean and, in some seasons, the Amazon Basin. Further research to assess the plausibility of this and other mechanisms is important, given the potential implications of drying in these rainforest regions.

scholarly journals Feedback of mesoscale ocean currents on atmospheric winds in high-resolution coupled models and implications for the forcing of ocean-only models

2017 ◽  
Author(s):  
Rafael Abel ◽  
Claus W. Böning ◽  
Richard J. Greatbatch ◽  
Helene T. Hewitt ◽  
Malcolm J. Roberts
Keyword(s):  
Climate Model ◽  
Global Climate Model ◽  
Surface Wind ◽  
Ocean Currents ◽  
Global Ocean ◽  
Ocean Current ◽  
Western Boundary ◽  
Coupling Coefficients ◽  
Coupled Models ◽  
Near Surface

Abstract. The repercussions of surface ocean currents for the near-surface wind and the air-sea momentum flux are investigated in two versions of a global climate model with eddying ocean. The focus is on the effect of mesoscale ocean current features at scales of less than 150 km, by considering high-pass filtered, monthly-mean model output fields. We find a clear signature of a mesoscale oceanic imprint in the wind fields over the energetic areas of the oceans, particularly along the extensions of the western boundary currents and the Antarctic Circumpolar Current. These areas are characterized by a positive correlation between mesoscale perturbations in the curl of the surface currents and the wind curl. The coupling coefficients are spatially non-uniform and show a pronounced seasonal cycle. The positive feedback of mesoscale current features on the near-surface wind acts in opposition to their damping effect on the wind stress. A tentative incorporation of this feedback in the surface stress formulation of an eddy-permitting global ocean-only model leads to a gain in the kinetic energy of up to 10 %, suggesting a fundamental shortcoming of present ocean model configurations.

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.

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