scholarly journals Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

2021 ◽  
Author(s):  
Goratz Beobide-Arsuaga ◽  
Tobias Bayr ◽  
Annika Reintges ◽  
Mojib Latif
Keyword(s):  
Global Warming ◽  
Standard Deviation ◽  
Zonal Wind ◽  
Model Uncertainty ◽  
Internal Variability ◽  
First Century ◽  
Amplitude Change ◽  
Enso Dynamics ◽  
Scenario Uncertainty ◽  
Twenty First Century

AbstractThere is a long-standing debate on how the El Niño/Southern Oscillation (ENSO) amplitude may change during the twenty-first century in response to global warming. Here we identify the sources of uncertainty in the ENSO amplitude projections in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5) and Phase 6 (CMIP6), and quantify scenario uncertainty, model uncertainty and uncertainty due to internal variability. The model projections exhibit a large spread, ranging from increasing standard deviation of up to 0.6 °C to diminishing standard deviation of up to − 0.4 °C by the end of the twenty-first century. The ensemble-mean ENSO amplitude change is close to zero. Internal variability is the main contributor to the uncertainty during the first three decades; model uncertainty dominates thereafter, while scenario uncertainty is relatively small throughout the twenty-first century. The total uncertainty increases from CMIP5 to CMIP6: while model uncertainty is reduced, scenario uncertainty is considerably increased. The models with “realistic” ENSO dynamics have been analyzed separately and categorized into models with too small, moderate and too large ENSO amplitude in comparison to instrumental observations. The smallest uncertainties are observed in the sub-ensemble exhibiting realistic ENSO dynamics and moderate ENSO amplitude. However, the global warming signal in ENSO-amplitude change is undetectable in all sub-ensembles. The zonal wind-SST feedback is identified as an important factor determining ENSO amplitude change: global warming signal in ENSO amplitude and zonal wind-SST feedback strength are highly correlated across the CMIP5 and CMIP6 models.

ENSO amplitude uncertainty under global warming in CMIP5 models

2020 ◽  
Author(s):  
Goratz Beobide ◽  
Tobias Bayr ◽  
Annika Reintges ◽  
Mojib Latif
Keyword(s):  
Global Warming ◽  
Zonal Wind ◽  
Coupled Model ◽  
Correlation Coefficients ◽  
Internal Variability ◽  
Mean Amplitude ◽  
Cmip5 Models ◽  
Amplitude Change ◽  
Uncertainty Model ◽  
Scenario Uncertainty

<p>The possible change of ENSO amplitude during the 21<sup>st</sup> century in response to global warming has been analyzed in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5). Three types of uncertainties are investigated: scenario uncertainty, model uncertainty, and uncertainty due to internal variability.</p><p>The ENSO response obtained from the CMIP5 models is highly uncertain, leading to an ensemble-mean amplitude change of close to zero until the end of the 21<sup>st</sup> century, with an uncertainty exceeding 0.3 °C. The internal variability is the main contributor to the uncertainty during the first two decades of the projections. The inter-model differences dominate thereafter, while scenario uncertainty is relatively small throughout the whole 21<sup>st</sup> century. The zonal wind-SST feedback has been identified as an important factor of ENSO amplitude change: the global warming signal in the ENSO amplitude and zonal wind-SST feedback are highly correlated across the CMIP5 models, with correlation coefficients of 0.87, 0.84 and 0.78 for the RCP4.5, RCP6.0 and RCP8.5 scenarios, respectively.</p><p>The CMIP5 models with realistic ENSO dynamics have been analyzed separately. In this sub-ensemble, the global warming signal is strengthened with a mean ENSO amplitude decrease of approximately 0.1°C by the end of the 21<sup>st</sup> century. When only considering models with large decadal ENSO amplitude variability, the decrease in ENSO amplitude amounts to 0.1°C and 0.2°C for the RCP4.5 and RCP8.5 scenarios, respectively.</p>

scholarly journals A Simple, Coherent Framework for Partitioning Uncertainty in Climate Predictions

2011 ◽  
Vol 24 (17) ◽  
pp. 4634-4643 ◽  
Author(s):  
Stan Yip ◽  
Christopher A. T. Ferro ◽  
David B. Stephenson ◽  
Ed Hawkins
Keyword(s):  
Model Uncertainty ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
First Century ◽  
Uncertainty Model ◽  
Ensemble Mean ◽  
Scenario Uncertainty ◽  
Twenty First Century ◽  
Multimodel Ensembles

A simple and coherent framework for partitioning uncertainty in multimodel climate ensembles is presented. The analysis of variance (ANOVA) is used to decompose a measure of total variation additively into scenario uncertainty, model uncertainty, and internal variability. This approach requires fewer assumptions than existing methods and can be easily used to quantify uncertainty related to model–scenario interaction—the contribution to model uncertainty arising from the variation across scenarios of model deviations from the ensemble mean. Uncertainty in global mean surface air temperature is quantified as a function of lead time for a subset of the Coupled Model Intercomparison Project phase 3 ensemble and results largely agree with those published by other authors: scenario uncertainty dominates beyond 2050 and internal variability remains approximately constant over the twenty-first century. Both elements of model uncertainty, due to scenario-independent and scenario-dependent deviations from the ensemble mean, are found to increase with time. Estimates of model deviations that arise as by-products of the framework reveal significant differences between models that could lead to a deeper understanding of the sources of uncertainty in multimodel ensembles. For example, three models show a diverging pattern over the twenty-first century, while another model exhibits an unusually large variation among its scenario-dependent deviations.

scholarly journals Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections

2015 ◽  
Vol 28 (2) ◽  
pp. 838-852 ◽  
Author(s):  
Christopher M. Little ◽  
Radley M. Horton ◽  
Robert E. Kopp ◽  
Michael Oppenheimer ◽  
Stan Yip
Keyword(s):  
Sea Level ◽  
Model Uncertainty ◽  
Internal Variability ◽  
Climate System ◽  
First Century ◽  
The Arctic ◽  
Management Approach ◽  
Local Risk ◽  
Twenty First Century ◽  
Global And Local

Abstract The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere–ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.

Systemic Leadership and Energy: The Argument

2018 ◽  
Author(s):  
William R. Thompson ◽  
Leila Zakhirova
Keyword(s):  
Global Warming ◽  
Single Case ◽  
World Politics ◽  
First Century ◽  
Industrial Economy ◽  
Interactive Model ◽  
Agrarian Economy ◽  
Historical Processes ◽  
Twenty First Century ◽  
Significant Factors

This chapter introduces the issue of how systemic leadership and energy are intertwined. One compound question is: How did we shift from a primarily agrarian economy to a primarily industrial economy, and how did this shift shape world politics? We develop an interactive model of the significant factors involved in this change, not all of which necessarily had an equal impact in each single case. A second set of questions involve the linkages between the systemic leadership that emerged from these historical processes and the global warming crisis of the twenty-first century. How is systemic leadership linked to the crisis in the first place? What is systemic leadership’s likely role in responding to the crisis?

scholarly journals Late Twenty-First-Century Changes in the Midlatitude Atmospheric Circulation in the CESM Large Ensemble

2017 ◽  
Vol 30 (15) ◽  
pp. 5943-5960 ◽  
Author(s):  
Y. Peings ◽  
J. Cattiaux ◽  
S. Vavrus ◽  
Gudrun Magnusdottir
Keyword(s):  
Atmospheric Circulation ◽  
Extreme Temperature ◽  
Internal Variability ◽  
First Century ◽  
The Arctic ◽  
Arctic Amplification ◽  
Large Ensemble ◽  
Longitudinal Sector ◽  
Twenty First Century ◽  
Projected Changes

Projected changes in the midlatitude atmospheric circulation at the end of the twenty-first century are investigated using coupled ocean–atmosphere simulations from the Community Earth System Model Large Ensemble (CESM-LENS). Different metrics are used to describe the response of the midlatitude atmospheric dynamics in 40 ensemble members covering the 1920–2100 period. Contrasted responses are identified depending on the season and longitudinal sector that are considered. In winter, a slowdown of the zonal flow and an increase in waviness is found over North America, while the European sector exhibits a reinforced westerly flow and decreased waviness. Extreme temperature events in midlatitudes are more sensitive to thermodynamical than dynamical changes, and a general decrease in the intensity of wintertime cold spells is found. Analyses of individual ensemble members reveal a large spread in circulation changes due to internal variability. Causes for this spread are found to be tied to the Arctic amplification in the Pacific–North American sector and to the polar stratosphere in the North Atlantic. A competition mechanism is also discussed between the midlatitude response to polar versus tropical changes. While the upper-tropospheric tropical warming pushes the jet stream poleward, in winter, Arctic amplification and the weaker polar vortex exert an opposite effect. This competition results in a narrowing of the jet path in the midlatitudes, leading to decreased/unchanged waviness/blockings. This interpretation somewhat reconciles conflicting results between the hypothesized effect of Arctic amplification and projected changes in midlatitude flow characteristics. This study also illustrates that further understanding of regional processes is critical for anticipating changes in the midlatitude dynamics.

scholarly journals Quantifying Sources of Uncertainty in Projections of Future Climate*

2014 ◽  
Vol 27 (23) ◽  
pp. 8793-8808 ◽  
Author(s):  
Paul J. Northrop ◽  
Richard E. Chandler
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Internal Variability ◽  
Future Climate ◽  
First Century ◽  
Climate Projections ◽  
Large Contribution ◽  
Sources Of Uncertainty ◽  
Twenty First Century ◽  
Emissions Scenario

Abstract A simple statistical model is used to partition uncertainty from different sources, in projections of future climate from multimodel ensembles. Three major sources of uncertainty are considered: the choice of climate model, the choice of emissions scenario, and the internal variability of the modeled climate system. The relative contributions of these sources are quantified for mid- and late-twenty-first-century climate projections, using data from 23 coupled atmosphere–ocean general circulation models obtained from phase 3 of the Coupled Model Intercomparison Project (CMIP3). Similar investigations have been carried out recently by other authors but within a statistical framework for which the unbalanced nature of the data and the small number (three) of scenarios involved are potentially problematic. Here, a Bayesian analysis is used to overcome these difficulties. Global and regional analyses of surface air temperature and precipitation are performed. It is found that the relative contributions to uncertainty depend on the climate variable considered, as well as the region and time horizon. As expected, the uncertainty due to the choice of emissions scenario becomes more important toward the end of the twenty-first century. However, for midcentury temperature, model internal variability makes a large contribution in high-latitude regions. For midcentury precipitation, model internal variability is even more important and this persists in some regions into the late century. Implications for the design of climate model experiments are discussed.

scholarly journals The Impact of Anthropogenic Forcing and Natural Processes on Past, Present, and Future Rainfall over Victoria, Australia

2020 ◽  
Vol 33 (18) ◽  
pp. 8087-8106 ◽  
Author(s):  
Surendra P. Rauniyar ◽  
Scott B. Power
Keyword(s):  
Rainfall Variability ◽  
Internal Variability ◽  
First Century ◽  
External Forcing ◽  
Cool Season ◽  
Model Simulations ◽  
Millennium Drought ◽  
Twenty First Century ◽  
The Impact ◽  
Forced Drying

AbstractCool-season (April to October) rainfall dominates the annual average rainfall over Victoria, Australia, and is important for agriculture and replenishing reservoirs. Rainfall during the cool season has been unusually low since the beginning of the Millennium Drought in 1997 (~12% below the twentieth-century average). In this study, 24 CMIP5 climate models are used to estimate 1) the extent to which this drying is driven by external forcing and 2) future rainfall, taking both external forcing and internal natural climate variability into account. All models have preindustrial, historical, and twenty-first-century (RCP2.6, RCP4.5, and RCP8.5) simulations. It is found that rainfall in the past two decades is below the preindustrial average in two-thirds or more of model simulations. However, the magnitude of the multimodel median externally forced drying is equivalent to only 20% of the observed drying (interquartile range of 40% to −4%), suggesting that the drying is dominated by internally generated rainfall variability. Underestimation of internal variability of rainfall by the models, however, increases the uncertainties in these estimates. According to models the anthropogenically forced drying becomes dominant from 2010 to 2029, when drying is evident in over 90% of the model simulations. For the 2018–37 period, it is found that there is only a ~12% chance that internal rainfall variability could completely offset the anthropogenically forced drying. By the late twenty-first century, the anthropogenically forced drying under RCP8.5 is so large that internal variability appears too small to be able to offset it. Confidence in the projections is lowered because models have difficulty in simulating the magnitude of the observed decline in rainfall.

Remobilization of southern African desert dune systems by twenty-first century global warming

Nature ◽  
2005 ◽  
Vol 435 (7046) ◽  
pp. 1218-1221 ◽  
Author(s):  
David S. G. Thomas ◽  
Melanie Knight ◽  
Giles F. S. Wiggs
Keyword(s):  
Global Warming ◽  
First Century ◽  
Dune Systems ◽  
Twenty First Century
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