scholarly journals Dynamics and Predictability of Hemispheric-Scale Multidecadal Climate Variability in an Observationally Constrained Mechanistic Model

2020 ◽  
Vol 33 (11) ◽  
pp. 4599-4620 ◽  
Author(s):  
Sergey Kravtsov
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Mechanistic Model ◽  
Covariance Structure ◽  
Deep Ocean ◽  
Ocean Dynamics ◽  
Cmip5 Models ◽  
Model Parameters ◽  
Atmospheric Noise ◽  
Multidecadal Climate Variability

AbstractThis paper addresses the dynamics of internal hemispheric-scale multidecadal climate variability by postulating an energy-balance (EBM) model comprising two deep-ocean oscillators in the Atlantic and Pacific basins, coupled through their surface mixed layers via atmospheric teleconnections. This system is linear and driven by the atmospheric noise. Two sets of the EBM model parameters are developed by fitting the EBM-based mixed-layer temperature covariance structure to best mimic basin-average North Atlantic/Pacific sea surface temperature (SST) covariability in either observations or control simulations of comprehensive climate models within the CMIP5 project. The differences between the dynamics underlying the observed and CMIP5-simulated multidecadal climate variability and predictability are encapsulated in the algebraic structure of the two EBM model versions so obtained: EBMCMIP5 and EBMOBS. The multidecadal variability in EBMCMIP5 is overall weaker and amounts to a smaller fraction of the total SST variability than in EBMOBS, pointing to a lower potential decadal predictability of virtual CMIP5 climates relative to that of the actual climate. The EBMCMIP5 decadal hemispheric teleconnections (and, by inference, those in CMIP5 models) are largely controlled by the variability of the Pacific, in which the ocean, due to its large thermal and dynamical memory, acts as a passive integrator of atmospheric noise. By contrast, EBMOBS features a stronger two-way coupling between the Atlantic and Pacific multidecadal oscillators, thereby suggesting the existence of a hemispheric-scale and, perhaps, global multidecadal mode associated with internal ocean dynamics. The inferred differences between the observed and CMIP5 simulated climate variability stem from a stronger communication between the deep ocean and surface processes implicit in the observational data.

scholarly journals Climate Drift in the CMIP5 Models*

2013 ◽  
Vol 26 (21) ◽  
pp. 8597-8615 ◽  
Author(s):  
Alexander Sen Gupta ◽  
Nicolas C. Jourdain ◽  
Jaclyn N. Brown ◽  
Didier Monselesan
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Deep Ocean ◽  
Internal Variability ◽  
Correction Method ◽  
Physical Models ◽  
Cmip5 Models ◽  
Steric Sea Level ◽  
Biogeochemical Models ◽  
The Difference

Abstract Climate models often exhibit spurious long-term changes independent of either internal variability or changes to external forcing. Such changes, referred to as model “drift,” may distort the estimate of forced change in transient climate simulations. The importance of drift is examined in comparison to historical trends over recent decades in the Coupled Model Intercomparison Project (CMIP). Comparison based on a selection of metrics suggests a significant overall reduction in the magnitude of drift from phase 3 of CMIP (CMIP3) to phase 5 of CMIP (CMIP5). The direction of both ocean and atmospheric drift is systematically biased in some models introducing statistically significant drift in globally averaged metrics. Nevertheless, for most models globally averaged drift remains weak compared to the associated forced trends and is often smaller than the difference between trends derived from different ensemble members or the error introduced by the aliasing of natural variability. An exception to this is metrics that include the deep ocean (e.g., steric sea level) where drift can dominate in forced simulations. In such circumstances drift must be corrected for using information from concurrent control experiments. Many CMIP5 models now include ocean biogeochemistry. Like physical models, biogeochemical models generally undergo long spinup integrations to minimize drift. Nevertheless, based on a limited subset of models, it is found that drift is an important consideration and must be accounted for. For properties or regions where drift is important, the drift correction method must be carefully considered. The use of a drift estimate based on the full control time series is recommended to minimize the contamination of the drift estimate by internal variability.

scholarly journals Multi-annual modes in the 20th century temperature variability in reanalyses and CMIP5 models

2016 ◽  
Vol 9 (11) ◽  
pp. 4097-4109
Author(s):  
Heikki Järvinen ◽  
Teija Seitola ◽  
Johan Silén ◽  
Jouni Räisänen
Keyword(s):  
Climate Variability ◽  
20Th Century ◽  
Climate Models ◽  
Spectral Power ◽  
Singular Spectrum Analysis ◽  
Reanalysis Data ◽  
Cmip5 Models ◽  
Data Sets ◽  
Near Surface ◽  
Annual Variability

Abstract. A performance expectation is that Earth system models simulate well the climate mean state and the climate variability. To test this expectation, we decompose two 20th century reanalysis data sets and 12 CMIP5 model simulations for the years 1901–2005 of the monthly mean near-surface air temperature using randomised multi-channel singular spectrum analysis (RMSSA). Due to the relatively short time span, we concentrate on the representation of multi-annual variability which the RMSSA method effectively captures as separate and mutually orthogonal spatio-temporal components. This decomposition is a unique way to separate statistically significant quasi-periodic oscillations from one another in high-dimensional data sets.The main results are as follows. First, the total spectra for the two reanalysis data sets are remarkably similar in all timescales, except that the spectral power in ERA-20C is systematically slightly higher than in 20CR. Apart from the slow components related to multi-decadal periodicities, ENSO oscillations with approximately 3.5- and 5-year periods are the most prominent forms of variability in both reanalyses. In 20CR, these are relatively slightly more pronounced than in ERA-20C. Since about the 1970s, the amplitudes of the 3.5- and 5-year oscillations have increased, presumably due to some combination of forced climate change, intrinsic low-frequency climate variability, or change in global observing network. Second, none of the 12 coupled climate models closely reproduce all aspects of the reanalysis spectra, although some models represent many aspects well. For instance, the GFDL-ESM2M model has two nicely separated ENSO periods although they are relatively too prominent as compared with the reanalyses. There is an extensive Supplement and YouTube videos to illustrate the multi-annual variability of the data sets.

scholarly journals Do GCM's predict the climate... or macroweather?

2012 ◽  
Vol 3 (2) ◽  
pp. 1259-1286 ◽  
Author(s):  
S. Lovejoy ◽  
D. Schertzer ◽  
D. Varon
Keyword(s):  
Climate Models ◽  
Deep Ocean ◽  
Great Majority ◽  
Ocean Dynamics ◽  
Last Millennium ◽  
Nonlinear Dynamical ◽  
Continuous Background ◽  
Climate Forcings ◽  
Spectral Variance ◽  
Meteorological Models

Abstract. We are used to the weather – climate dichotomy, yet the great majority of the spectral variance of atmospheric fields is in the continuous "background" and this defines instead a trichotomy with a "macroweather" regime in the intermediate range ≈10 days to 30 yr. In the weather, macroweather and climate regimes, exponents characterize the type of variability over the entire ranges and it is natural to identify them with qualitatively different synergies of nonlinear dynamical mechanisms that repeat scale after scale. Since climate models are essentially meteorological models (although with extra couplings) it is thus important to determine whether they currently model all three regimes. Using Last Millennium simulations from four GCM's, we show that control runs only reproduce macroweather and that runs with various (reconstructed) climate forcings do somewhat better but have overly weak multicentennial variabilities. A possible explanation is that the models lack – or inadequately treat – important slow "climate" processes such as land-ice or deep ocean dynamics.

scholarly journals Frequency-dependent estimation of effective spatial degrees of freedom

2021 ◽  
pp. 1-49
Author(s):  
Torben Kunz ◽  
Thomas Laepple
Keyword(s):  
Climate Variability ◽  
Degrees Of Freedom ◽  
Climate Models ◽  
Model Simulation ◽  
Covariance Structure ◽  
Spatial Covariance ◽  
Frequency Dependent ◽  
Near Surface ◽  
Temporal Variance ◽  
Spatial Degrees Of Freedom

AbstractClimate variability occurs over wide ranges of spatial and temporal scales. It exhibits a complex spatial covariance structure, which depends on geographic location (e.g., tropics vs. extratropics), and also consists of a superposition of: (a) components with gradually decaying positive correlation functions, and (b) teleconnections that often involve anti-correlations. In addition, there are indications that the spatial covariance structure depends on frequency. Thus, a comprehensive assessment of the spatio-temporal covariance structure of climate variability would require an extensive set of statistical diagnostics. Therefore, it is often desirable to characterize the covariance structure by a simple summarizing metric that is easy to compute from datasets. Such summarizing metrics are useful, for example, in the context of comparisons between climate models or between models and observations. Here we introduce a frequency-dependent version of a simple measure of the effective spatial degrees of freedom. The measure is based on the temporal variance of the global average of some climate variable, and its novel aspect consists in its frequency-dependence. We also provide a clear geometric interpretation of the measure. Its easy applicability is demonstrated using near-surface temperature and precipitation fields obtained from a paleoclimate model simulation. This application reveals a distinct scaling behavior of the spatial degrees of freedom as a function of frequency, ranging from monthly to millennial scales.

Effects of mesoscale ocean flows on multidecadal climate variability

2020 ◽  
Author(s):  
André Jüling ◽  
Anna von der Heydt ◽  
Henk Dijkstra
Keyword(s):  
Climate Variability ◽  
Surface Temperature ◽  
Climate Models ◽  
Heat Content ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Multidecadal Variability ◽  
Global Mean Surface Temperature ◽  
Ocean Flows ◽  
Global Mean

<div> <div>Climate variability on decadal to multidecadal time scales appears to be organized in pronounced patterns with clear expressions in sea surface temperature, such as the Pacific Multidecadal Variability and the Atlantic Multidecadal Variability. These patterns are now well studied both in observations and in global climate models and are important in the attribution of climate change. Results in CMIP5 models have indicated large biases in these patterns with consequences for ocean heat storage variability and eventually the global mean surface temperature.</div> <div>We use two multi-century Community Earth System Model simulations at coarse (1°) and fine (0.1°) ocean model horizontal grid spacing and study the effect of the representation of mesoscale ocean flows on major patterns of multidecadal variability. We find that resolving mesoscale ocean flows both improves the characteristics of the modes of variability with respect to observations and increases the amplitude of the heat content variability in the individual ocean basins. However, the effect on the global mean surface temperature is relatively minor.</div> </div>

scholarly journals The Sensitivity of the Rate of Transient Climate Change to Ocean Physics Perturbations

2007 ◽  
Vol 20 (10) ◽  
pp. 2315-2320 ◽  
Author(s):  
M. Collins ◽  
C. M. Brierley ◽  
M. MacVean ◽  
B. B. B. Booth ◽  
G. R. Harris
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Deep Ocean ◽  
Time Dependent ◽  
Model Parameters ◽  
Climate Feedbacks ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Surface Climate

Abstract “Perturbed physics” ensembles of Hadley Centre climate models have recently been used to quantify uncertainties in atmospheric and surface climate feedbacks under enhanced levels of CO2, and to produce probabilistic estimates of the magnitude of equilibrium climate change. The rate of time-dependent climate change is determined both by the strength of atmosphere–surface climate feedbacks and by the strength of processes that remove heat from the surface to the deep ocean. Here a first small ensemble of coupled atmosphere–ocean climate model experiments in which the parameters that control three key ocean physical processes are perturbed is described. It is found that the perturbations have little impact on the rate of ocean heat uptake, and thus have little impact on the time-dependent rate of global warming. Under the idealized scenario of 1% yr−1 compounded CO2 increase, the spread in the transient climate response is of the order of a few tenths of a degree, in contrast to the spread of order of 1° caused by perturbing atmospheric model parameters.

A new method for studying the extratropical response to tropical precipitation anomalies and its role in improving projections of Northern Hemisphere climate variability

2020 ◽  
Author(s):  
Natasha Senior ◽  
Manoj Joshi ◽  
Adrian Matthews ◽  
Pranab Deb
Keyword(s):  
Climate Variability ◽  
Northern Hemisphere ◽  
Geopotential Height ◽  
Climate Models ◽  
Linear Response Theory ◽  
Teleconnection Pattern ◽  
Cmip5 Models ◽  
Boreal Winter ◽  
Response Functions ◽  
Tropical Precipitation

<p>Intensification of extreme precipitation and weather events are some of the projections under a 2°C average global temperature increase scenario. Rossby wave trains may be triggered by anomalous tropical precipitation through the interaction of the associated upper level divergent wind and the vorticity gradients of the subtropical jet streams. In this way, anomalous tropical precipitation can influence weather patterns in the Northern Hemisphere. Owing to the quasi-linearity of this teleconnection pattern, it may be studied statistically as a series of signal-response functions. Here the anomalous precipitation events are treated as input forcings and the resulting geopotential height anomalies are the output signals. Through calculating the response functions we are able to realistically capture the 250 hPa geopotential height response to a step-like change in precipitation over the Maritime Continent or the eastern Indian Ocean during the boreal winter. When examining these responses using the same forcing for a selection of CMIP5 models, we find that there is a large inter-model spread, owing to differences in the model basic state. Since these teleconnection patterns are not faithfully represented in climate models, this can obscure our ability to develop realistic projections of atmospheric circulation and extreme weather. We discuss the potential of the linear response theory method to provide improved projections for Northern Hemisphere climate variability.</p>

Modelling heavy metal mobilisation in solid waste deposits - a predictive tool for environmental risk assessment

1999 ◽  
Vol 39 (10-11) ◽  
pp. 193-196
Author(s):  
J. Petersen ◽  
J. G. Petrie
Keyword(s):  
Heavy Metal ◽  
Solid Waste ◽  
Environmental Risk ◽  
Mechanistic Model ◽  
Small Sample ◽  
Waste Material ◽  
Metal Species ◽  
Model Parameters ◽  
Assessment Methodology ◽  
Predictive Tool

The release of heavy metal species from deposits of solid waste materials originating from minerals processing operations poses a serious environmental risk should such species migrate beyond the boundaries of the deposit into the surrounding environment. Legislation increasingly places the liability for wastes with the operators of the process that generates them. The costs for long-term monitoring and clean-up following a potential critical leakage have to be factored in the overall project plan from the outset. Thus assessment of the potential for a particular waste material to generate a harmful leachate is directly relevant for estimating the environmental risk associated with the planned disposal operation. A rigorous mechanistic model is proposed, which allows prediction of the time-dependent generation of a leachate from a solid mineral waste deposit. Model parameters are obtained from a suitably designed laboratory waste assessment methodology on a relatively small sample of the prospective waste material. The parameters are not specific to the laboratory environment in which they were obtained but are valid also for full-scale heap modelling. In this way the model, combined with the assessment methodology, becomes a powerful tool for meaningful assessment of the risks associated with solid waste disposal strategies.

scholarly journals Parameter Optimization for Real-World ENSO Forecast in an Intermediate Coupled Model

2019 ◽  
Vol 147 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
Yuchu Zhao ◽  
Zhengyu Liu ◽  
Fei Zheng ◽  
Yishuai Jin
Keyword(s):  
Data Assimilation ◽  
Parameter Optimization ◽  
Real World ◽  
Climate Models ◽  
Coupled Model ◽  
Prediction Skill ◽  
Model Parameters ◽  
Real World Data ◽  
The Real ◽  
Advection Term

Abstract We performed parameter estimation in the Zebiak–Cane model for the real-world scenario using the approach of ensemble Kalman filter (EnKF) data assimilation and the observational data of sea surface temperature and wind stress analyses. With real-world data assimilation in the coupled model, our study shows that model parameters converge toward stable values. Furthermore, the new parameters improve the real-world ENSO prediction skill, with the skill improved most by the parameter of the highest climate sensitivity (gam2), which controls the strength of anomalous upwelling advection term in the SST equation. The improved prediction skill is found to be contributed mainly by the improvement in the model dynamics, and second by the improvement in the initial field. Finally, geographic-dependent parameter optimization further improves the prediction skill across all the regions. Our study suggests that parameter optimization using ensemble data assimilation may provide an effective strategy to improve climate models and their real-world climate predictions in the future.

scholarly journals Hydrological droughts in the southern Andes (40–45°S) from an ensemble experiment using CMIP5 and CMIP6 models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rodrigo Aguayo ◽  
Jorge León-Muñoz ◽  
René Garreaud ◽  
Aldo Montecinos
Keyword(s):  
Climate Models ◽  
Physicochemical Characteristics ◽  
Climate Impact ◽  
Economic Consequences ◽  
Cmip5 Models ◽  
Southern Andes ◽  
Weap Model ◽  
Coastal System ◽  
Hydrological Droughts ◽  
Impacts Of Climate Change

AbstractThe decrease in freshwater input to the coastal system of the Southern Andes (40–45°S) during the last decades has altered the physicochemical characteristics of the coastal water column, causing significant environmental, social and economic consequences. Considering these impacts, the objectives were to analyze historical severe droughts and their climate drivers, and to evaluate the hydrological impacts of climate change in the intermediate future (2040–2070). Hydrological modelling was performed in the Puelo River basin (41°S) using the Water Evaluation and Planning (WEAP) model. The hydrological response and its uncertainty were compared using different combinations of CMIP projects (n = 2), climate models (n = 5), scenarios (n = 3) and univariate statistical downscaling methods (n = 3). The 90 scenarios projected increases in the duration, hydrological deficit and frequency of severe droughts of varying duration (1 to 6 months). The three downscaling methodologies converged to similar results, with no significant differences between them. In contrast, the hydroclimatic projections obtained with the CMIP6 and CMIP5 models found significant climatic (greater trends in summer and autumn) and hydrological (longer droughts) differences. It is recommended that future climate impact assessments adapt the new simulations as more CMIP6 models become available.

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