scholarly journals Indo-Pacific Climate Modes in Warming Climate: Consensus and Uncertainty Across Model Projections

2019 ◽  
Vol 5 (4) ◽  
pp. 308-321 ◽  
Author(s):  
Xiao-Tong Zheng
Keyword(s):  
Climate Models ◽  
Internal Variability ◽  
Forced Response ◽  
Future Climate Change ◽  
Climate Modes ◽  
Warming Climate ◽  
Warming Pattern ◽  
Large Ensembles ◽  
Projected Changes ◽  
Climate Mode

Abstract Purpose of Review Understanding the changes in climate variability in a warming climate is crucial for reliable projections of future climate change. This article reviews the recent progress in studies of how climate modes in the Indo-Pacific respond to greenhouse warming, including the consensus and uncertainty across climate models. Recent Findings Recent studies revealed a range of robust changes in the properties of climate modes, often associated with the mean state changes in the tropical Indo-Pacific. In particular, the intermodel diversity in the ocean warming pattern is a prominent source of uncertainty in mode changes. The internal variability also plays an important role in projected changes in climate modes. Summary Model biases and intermodel variability remain major challenges for reducing uncertainty in projecting climate mode changes in warming climate. Improved models and research linking simulated present-day climate and future changes are essential for reliable projections of climate mode changes. In addition, large ensembles should be used for each model to reduce the uncertainty from internal variability and isolate the forced response to global warming.

Which climate models capture the variability and forced response in observed temperatures: a large ensemble comparison

2020 ◽  
Author(s):  
Nicola Maher ◽  
Laura Suarez-Gutierrez ◽  
Sebastian Milinski
Keyword(s):  
Climate Models ◽  
Internal Variability ◽  
Forced Response ◽  
Tropical Eastern Pacific ◽  
The North ◽  
Surface Temperatures ◽  
External Forcings ◽  
Coupled Climate Models ◽  
Large Ensembles ◽  
Adequate Representation

<p>We evaluate how large ensembles of ten coupled climate models represent the observed internal variability and response to external forcings in historical surface temperatures based on a novel methodological framework. This framework allows us to directly attribute whether discrepancies between models and observations arise due to biases in the simulated internal variability or rather in the forced response, without relying on assumptions to separate both signals in the observations. The largest discrepancies occur due to overestimated forced warming in some models during recent decades. The areas where most models, a maximum of nine, adequately simulate observed temperatures are the North Atlantic, Tropical Eastern Pacific, and the Northern Hemisphere land areas. In contrast, none of the models considered offers an adequate representation over the Southern Ocean. Our evaluation shows that CESM-LE, GFDL-ESM2M, and MPI-GE perform best at representing the internal variability and forced response in observed surface temperatures both globally and regionally. </p>

Exploiting large ensembles for a better yet simpler climate model evaluation

2021 ◽  
Author(s):  
Laura Suarez-Gutierrez ◽  
Sebastian Milinski ◽  
Nicola Maher
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Internal Variability ◽  
Forced Response ◽  
Evaluation Framework ◽  
Surface Areas ◽  
Global Mean Temperature ◽  
External Forcings ◽  
Large Ensembles

<p>We use a methodological framework exploiting the power of large ensembles to evaluate how well ten coupled climate models represent the internal variability and response to external forcings in observed historical surface temperatures. This evaluation framework allows us to directly attribute discrepancies between models and observations to biases in the simulated internal variability or forced response, without relying on assumptions to separate these signals in observations. The largest discrepancies result from the overestimated forced warming in some models during recent decades. In contrast, models do not systematically over- or underestimate internal variability in global mean temperature. On regional scales, all models misrepresent surface temperature variability over the Southern Ocean, while overestimating variability over land-surface areas, such as the Amazon and South Asia, and high-latitude oceans. Our evaluation shows that MPI-GE, followed by GFDL-ESM2M and CESM-LE offer the best global and regional representation of both the internal variability and forced response in observed historical temperatures.</p>

scholarly journals Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6

2020 ◽  
Vol 11 (2) ◽  
pp. 491-508 ◽  
Author(s):  
Flavio Lehner ◽  
Clara Deser ◽  
Nicola Maher ◽  
Jochem Marotzke ◽  
Erich M. Fischer ◽  
...  
Keyword(s):  
Coupled Model ◽  
Internal Variability ◽  
Potential Method ◽  
Added Value ◽  
Future Climate Change ◽  
Climate Projections ◽  
Good Representation ◽  
Transient Climate Response ◽  
Large Ensembles ◽  
Method Bias

Abstract. Partitioning uncertainty in projections of future climate change into contributions from internal variability, model response uncertainty and emissions scenarios has historically relied on making assumptions about forced changes in the mean and variability. With the advent of multiple single-model initial-condition large ensembles (SMILEs), these assumptions can be scrutinized, as they allow a more robust separation between sources of uncertainty. Here, the framework from Hawkins and Sutton (2009) for uncertainty partitioning is revisited for temperature and precipitation projections using seven SMILEs and the Coupled Model Intercomparison Project CMIP5 and CMIP6 archives. The original approach is shown to work well at global scales (potential method bias < 20 %), while at local to regional scales such as British Isles temperature or Sahel precipitation, there is a notable potential method bias (up to 50 %), and more accurate partitioning of uncertainty is achieved through the use of SMILEs. Whenever internal variability and forced changes therein are important, the need to evaluate and improve the representation of variability in models is evident. The available SMILEs are shown to be a good representation of the CMIP5 model diversity in many situations, making them a useful tool for interpreting CMIP5. CMIP6 often shows larger absolute and relative model uncertainty than CMIP5, although part of this difference can be reconciled with the higher average transient climate response in CMIP6. This study demonstrates the added value of a collection of SMILEs for quantifying and diagnosing uncertainty in climate projections.

scholarly journals Impact of internal variability on climate change for the upcoming decades: analysis of the CanESM2-LE and CESM-LE large ensembles

2019 ◽  
Vol 156 (3) ◽  
pp. 299-314 ◽  
Author(s):  
Gabriel Rondeau-Genesse ◽  
Marco Braun
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Ghg Emissions ◽  
Internal Variability ◽  
Mean Annual Temperature ◽  
Large Ensemble ◽  
Climate Change Effects ◽  
Large Ensembles ◽  
The Mean

Abstract The pace of climate change can have a direct impact on the efforts required to adapt. For short timescales, however, this pace can be masked by internal variability (IV). Over a few decades, this can cause climate change effects to exceed what would be expected from the greenhouse gas (GHG) emissions alone or, to the contrary, cause slowdowns or even hiatuses. This phenomenon is difficult to explore using ensembles such as CMIP5, which are composed of multiple climate models and thus combine both IV and inter-model differences. This study instead uses CanESM2-LE and CESM-LE, two state-of-the-art large ensembles (LE) that comprise multiple realizations from a single climate model and a single GHG emission scenario, to quantify the relationship between IV and climate change over the next decades in Canada and the USA. The mean annual temperature and the 3-day maximum and minimum temperatures are assessed. Results indicate that under the RCP8.5, temperatures within most of the individual large ensemble members will increase in a roughly linear manner between 2021 and 2060. However, members of the large ensembles in which a slowdown of warming is found during the 2021–2040 period are two to five times more likely to experience a period of very fast warming in the following decades. The opposite scenario, where the changes expected by 2050 would occur early because of IV, remains fairly uncommon for the mean annual temperature, but occurs in 5 to 15% of the large ensemble members for the temperature extremes.

scholarly journals Modulation of the Occurrence of Heatwaves over the Euro-Mediterranean Region by the Intensity of the Atlantic Multidecadal Variability

2021 ◽  
Vol 34 (3) ◽  
pp. 1099-1114
Author(s):  
Saïd Qasmi ◽  
Emilia Sanchez-Gomez ◽  
Yohan Ruprich-Robert ◽  
Julien Boé ◽  
Christophe Cassou
Keyword(s):  
Mediterranean Basin ◽  
Climate Models ◽  
Sensible Heat Flux ◽  
Forced Response ◽  
Atlantic Multidecadal Variability ◽  
Multidecadal Variability ◽  
Local Climate ◽  
Large Ensembles ◽  
The Mediterranean ◽  
The Mediterranean Basin

AbstractThe influence of the Atlantic multidecadal variability (AMV) and its amplitude on the Euro-Mediterranean summer climate is studied in two climate models, namely CNRM-CM5 and EC-Earth3P. Large ensembles of idealized experiments have been conducted in which North Atlantic sea surface temperatures are relaxed toward different amplitudes of the observed AMV anomalies. In agreement with observations, during a positive phase of the AMV both models simulate an increase (decrease) in temperature of 0.2°–0.8°C and a decrease (increase) in precipitation over the Mediterranean basin of 0.1–0.2 mm day−1 (northern half of Europe) compared to a negative phase. Heatwave durations over the Mediterranean land regions are 40% (up to 85% over the eastern regions) longer for a moderate amplitude of the AMV. Lower and higher amplitudes lead to longer durations of ~30% and ~100%, respectively. A comparison with observed heatwaves indicates that the AMV can considerably modulate the current anthropogenically forced response on heatwaves durations depending on the area and on the AMV amplitude. The related anticyclonic anomalies over the Mediterranean basin are associated with drier soils and a reduction of cloud cover, which concomitantly induce a decrease (increase) of the latent (sensible) heat flux, and an enhancement of the downward radiative fluxes over lands. It is found that both tropical and extratropical forcings from the AMV are needed to trigger mechanisms, which modulate the atmospheric circulation over the Euro-Atlantic region. The amplitude of the local climate response over the Mediterranean basin evolves linearly with the amplitude of the AMV. However, the strength of this relationship differs between the models, and depends on their intrinsic biases.

scholarly journals Assessing the Robustness of Future Extreme Precipitation Intensification in the CMIP5 Ensemble

2018 ◽  
Vol 31 (16) ◽  
pp. 6505-6525 ◽  
Author(s):  
Margot Bador ◽  
Markus G. Donat ◽  
Olivier Geoffroy ◽  
Lisa V. Alexander
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Internal Variability ◽  
Global Scale ◽  
Grid Cells ◽  
Wet Season ◽  
Tropical Regions ◽  
Projected Changes ◽  
Background Climate ◽  
Climate Noise

Abstract A warming climate is expected to intensify extreme precipitation, and climate models project a general intensification of annual extreme precipitation in most regions of the globe throughout the twenty-first century. We investigate the robustness of this future intensification over land across different models, regions, and seasons and evaluate the role of model interdependencies in the CMIP5 ensemble. Strong similarities in extreme precipitation changes are found between models that share atmospheric physics, turning an ensemble of 27 models into around 14 projections. We find that future annual extreme precipitation intensity increases in the majority of models and in the majority of land grid cells, from the driest to the wettest regions, as defined by each model’s precipitation climatology. The intermodel spread is generally larger over wet than over dry regions, smaller in the dry season compared to the wet season and at the annual scale, and largely reduced in extratropical compared to tropical regions and at the global scale. For each model, the future increase in annual and seasonal maximum daily precipitation amounts exceeds the range of simulated internal variability in the majority of land grid cells. At both annual and seasonal scales, however, there are a few regions where the change is still within the background climate noise, but their size and location differ between models. In extratropical regions, the signal-to-noise ratio of projected changes in extreme precipitation is particularly robust across models because of a similar change and background climate noise, whereas projected changes are less robust in the tropics.

scholarly journals The Emergence and Transient Nature of Arctic Amplification in Coupled Climate Models

2021 ◽  
Vol 9 ◽  
Author(s):  
Marika M. Holland ◽  
Laura Landrum
Keyword(s):  
Sea Ice ◽  
21St Century ◽  
Climate Models ◽  
Internal Variability ◽  
The Arctic ◽  
Arctic Amplification ◽  
Arctic Warming ◽  
Transient Nature ◽  
Coupled Climate Models ◽  
Large Ensembles

Under rising atmospheric greenhouse gas concentrations, the Arctic exhibits amplified warming relative to the globe. This Arctic amplification is a defining feature of global warming. However, the Arctic is also home to large internal variability, which can make the detection of a forced climate response difficult. Here we use results from seven model large ensembles, which have different rates of Arctic warming and sea ice loss, to assess the time of emergence of anthropogenically-forced Arctic amplification. We find that this time of emergence occurs at the turn of the century in all models, ranging across the models by a decade from 1994–2005. We also assess transient changes in this amplified signal across the 21st century and beyond. Over the 21st century, the projections indicate that the maximum Arctic warming will transition from fall to winter due to sea ice reductions that extend further into the fall. Additionally, the magnitude of the annual amplification signal declines over the 21st century associated in part with a weakening albedo feedback strength. In a simulation that extends to the 23rd century, we find that as sea ice cover is completely lost, there is little further reduction in the surface albedo and Arctic amplification saturates at a level that is reduced from its 21st century value.

Attribution of high-impact extreme sea surface temperature events

2021 ◽  
Author(s):  
Armineh Barkhordarian ◽  
Johanna Baehr
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Models ◽  
Internal Variability ◽  
High Impact ◽  
Sea Surface ◽  
Discrete Events ◽  
Tasman Sea ◽  
Coupled Climate Models ◽  
Large Ensembles

&lt;p&gt;We evaluate whether anthropogenic influence has affected the observed extreme sea surface temperature (SST), defined as discrete events of anomalously warm or cold ocean temperatures, over the last decades. To this end we utilize three large ensembles of coupled climate models and use two methods. The &amp;#64257;rst method analyzes the observed long-term spatiotemporal changes of extreme SST to detect the presence of a signal beyond changes solely due to natural (internal) variability and to attribute the detected changes to external climate drivers. The second method is based on single event attribution, which determines how an external forcing have changed the likelihood of high-impact extreme SST events, such as the&amp;#160;north Atlantic cold blob, the northeast Pacific warm blob, Tasman Sea marine heatwave, etc. In this study we further combine observations and model simulations under present and future forcing to assess how internal variability and anthropogenic climate change modulate extreme SST events.&lt;/p&gt;

scholarly journals Potential to Constrain Projections of Hot Temperature Extremes

2017 ◽  
Vol 30 (24) ◽  
pp. 9949-9964 ◽  
Author(s):  
Aleksandra Borodina ◽  
Erich M Fischer ◽  
Reto Knutti
Keyword(s):  
Temperature Distribution ◽  
North America ◽  
Model Evaluation ◽  
Climate Models ◽  
Internal Variability ◽  
Temperature Extremes ◽  
High Quality ◽  
North Asia ◽  
Projected Changes

Projected changes in temperature extremes, such as regional changes in the intensity and frequency of hot extremes, differ strongly across climate models. This study shows that this disagreement can be partly explained by discrepancies in the representation of the present-day temperature distribution, motivating the evaluation of models with observations. By evaluating climate models on carefully selected metrics, the models that are more likely to be reliable for long-term projections of temperature extremes are identified. The study found that frequencies of hot extremes are likely to increase at a higher rate than the multimodel mean estimate over large parts of the Northern Hemisphere and Australia. This implies that a higher degree of adaptation is required for a given global temperature target. It also found that projected changes in the intensity of hot extremes can be constrained in several regions, including Australia, central North America, and north Asia. In many other regions, large internal variability can often hamper model evaluation. For both aspects—the intensity and the frequency of hot extremes—the total area over which the constraints can be implemented is limited by the quality and completeness of observations. Thereby, this study highlights the importance of long-term, high-quality, and easily accessible observational records for model evaluation, which are vital to ultimately reduce uncertainties in projections of temperature extremes.

scholarly journals New Perspectives on Observed and Simulated Antarctic Sea Ice Extent Trends Using Optimal Fingerprinting Techniques*

2015 ◽  
Vol 28 (4) ◽  
pp. 1543-1560 ◽  
Author(s):  
William Richard Hobbs ◽  
Nathaniel L. Bindoff ◽  
Marilyn N. Raphael
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Ross Sea ◽  
Internal Variability ◽  
Ice Cover ◽  
Natural Variability ◽  
Forced Response ◽  
Cmip5 Models ◽  
Sea Ice Extent ◽  
Optimal Fingerprinting

Abstract Using optimal fingerprinting techniques, a detection analysis is performed to determine whether observed trends in Southern Ocean sea ice extent since 1979 are outside the expected range of natural variability. Consistent with previous studies, it is found that for the seasons of maximum sea ice cover (i.e., winter and early spring), the observed trends are not outside the range of natural variability and in some West Antarctic sectors they may be partially due to tropical variability. However, when information about the spatial pattern of trends is included in the analysis, the summer and autumn trends fall outside the range of internal variability. The detectable signal is dominated by strong and opposing trends in the Ross Sea and the Amundsen–Bellingshausen Sea regions. In contrast to the observed pattern, an ensemble of 20 CMIP5 coupled climate models shows that a decrease in Ross Sea ice cover would be expected in response to external forcings. The simulated decreases in the Ross, Bellingshausen, and Amundsen Seas for the autumn season are significantly different from unforced internal variability at the 95% confidence level. Unlike earlier work, the authors formally show that the simulated sea ice response to external forcing is different from both the observed trends and simulated internal variability and conclude that in general the CMIP5 models do not adequately represent the forced response of the Antarctic climate system.

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