scholarly journals Detectability of Decadal Anthropogenic Hydroclimate Changes over North America

2018 ◽  
Vol 31 (7) ◽  
pp. 2579-2597 ◽  
Author(s):  
Honghai Zhang ◽  
Thomas L. Delworth
Keyword(s):  
North America ◽  
Time Scales ◽  
Climate Models ◽  
Signal To Noise Ratio ◽  
Dominant Role ◽  
Internal Variability ◽  
Natural Variability ◽  
Large Ensembles ◽  
Current Century ◽  
Mean State

Regional hydroclimate changes on decadal time scales contain substantial natural variability. This presents a challenge for the detection of anthropogenically forced hydroclimate changes on these spatiotemporal scales because the signal of anthropogenic changes is modest, compared to the noise of natural variability. However, previous studies have shown that this signal-to-noise ratio can be greatly improved in a large model ensemble where each member contains the same signal but different noise. Here, using multiple state-of-the-art large ensembles from two climate models, the authors quantitatively assess the detectability of anthropogenically caused decadal shifts in precipitation-minus-evaporation (PmE) mean state against natural variability, focusing on North America during 2000–50. Anthropogenic forcing is projected to cause detectable (signal larger than noise) shifts in PmE mean state relative to the 1950–99 climatology over 50%–70% of North America by 2050. The earliest detectable signals include, during November–April, a moistening over northeastern North America and a drying over southwestern North America and, during May–October, a drying over central North America. Different processes are responsible for these signals. Changes in submonthly transient eddy moisture fluxes account for the northeastern moistening and central drying, while monthly atmospheric circulation changes explain the southwestern drying. These model findings suggest that despite the dominant role of natural internal variability on decadal time scales, anthropogenic shifts in PmE mean state can be detected over most of North America before the middle of the current century.

scholarly journals Sensitivity of Twentieth-Century Sahel Rainfall to Sulfate Aerosol and CO2 Forcing

2011 ◽  
Vol 24 (19) ◽  
pp. 4999-5014 ◽  
Author(s):  
Duncan Ackerley ◽  
Ben B. B. Booth ◽  
Sylvia H. E. Knight ◽  
Eleanor J. Highwood ◽  
David J. Frame ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Climate Models ◽  
Internal Variability ◽  
Natural Variability ◽  
Severe Drought ◽  
Relative Role ◽  
Coupled Climate Models ◽  
Large Ensembles ◽  
Drying Trend ◽  
Sahel Rainfall

A full understanding of the causes of the severe drought seen in the Sahel in the latter part of the twentieth-century remains elusive some 25 yr after the height of the event. Previous studies have suggested that this drying trend may be explained by either decadal modes of natural variability or by human-driven emissions (primarily aerosols), but these studies lacked a sufficiently large number of models to attribute one cause over the other. In this paper, signatures of both aerosol and greenhouse gas changes on Sahel rainfall are illustrated. These idealized responses are used to interpret the results of historical Sahel rainfall changes from two very large ensembles of fully coupled climate models, which both sample uncertainties arising from internal variability and model formulation. The sizes of these ensembles enable the relative role of human-driven changes and natural variability on historic Sahel rainfall to be assessed. The paper demonstrates that historic aerosol changes are likely to explain most of the underlying 1940–80 drying signal and a notable proportion of the more pronounced 1950–80 drying.

scholarly journals The Sensitivity of the Hydrological Cycle to Internal Climate Variability versus Anthropogenic Climate Change

2016 ◽  
Vol 29 (10) ◽  
pp. 3661-3673 ◽  
Author(s):  
Ryan J. Kramer ◽  
Brian J. Soden
Keyword(s):  
Water Vapor ◽  
Time Scales ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Internal Variability ◽  
Radiative Cooling ◽  
Surface Warming ◽  
Internal Climate Variability ◽  
Radiative Processes ◽  
Global Mean

Abstract In response to rising CO2 concentrations, climate models predict that globally averaged precipitation will increase at a much slower rate than water vapor. However, some observational studies suggest that global-mean precipitation and water vapor have increased at similar rates. While the modeling results emphasize changes at multidecadal time scales where the anthropogenic signal dominates, the shorter observational record is more heavily influenced by internal variability. Whether the physical constraints on the hydrological cycle fundamentally differ between these time scales is investigated. The results of this study show that while global-mean precipitation is constrained by radiative cooling on both time scales, the effects of CO2 dominate on multidecadal time scales, acting to suppress the increase in radiative cooling with warming. This results in a smaller precipitation change compared to interannual time scales where the effects of CO2 forcing are small. It is also shown that intermodel spread in the response of atmospheric radiative cooling (and thus global-mean precipitation) to anthropogenically forced surface warming is dominated by clear-sky radiative processes and not clouds, while clouds dominate under internal variability. The findings indicate that the sensitivity of the global hydrological cycle to surface warming differs fundamentally between internal variability and anthropogenically forced changes and this has important implications for interpreting observations of the hydrological sensitivity.

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 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.

scholarly journals Assessing the Quality of Southern Ocean Circulation in CMIP5 AOGCM and Earth System Model Simulations

2019 ◽  
Vol 32 (18) ◽  
pp. 5915-5940 ◽  
Author(s):  
R. L. Beadling ◽  
J. L. Russell ◽  
R. J. Stouffer ◽  
P. J. Goodman ◽  
M. Mazloff
Keyword(s):  
Southern Ocean ◽  
Wind Stress ◽  
Ocean Circulation ◽  
Climate Models ◽  
Dominant Role ◽  
Surface Wind ◽  
Coupled Model ◽  
Observational Uncertainty ◽  
Mean State

Abstract The Southern Ocean (SO) is vital to Earth’s climate system due to its dominant role in exchanging carbon and heat between the ocean and atmosphere and transforming water masses. Evaluating the ability of fully coupled climate models to accurately simulate SO circulation and properties is crucial for building confidence in model projections and advancing model fidelity. By analyzing multiple biases collectively across large model ensembles, physical mechanisms governing the diverse mean-state SO circulation found across models can be identified. This analysis 1) assesses the ability of a large ensemble of models contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5) to simulate observationally based metrics associated with an accurate representation of the Antarctic Circumpolar Current (ACC), and 2) presents a framework by which the quality of the simulation can be categorized and mechanisms governing the resulting circulation can be deduced. Different combinations of biases in critical metrics including the magnitude and position of the zonally averaged westerly wind stress maximum, wind-driven surface divergence, surface buoyancy fluxes, and properties and transport of North Atlantic Deep Water entering the SO produce distinct mean-state ACC transports. Relative to CMIP3, the quality of the CMIP5 SO simulations has improved. Eight of the thirty-one models simulate an ACC within observational uncertainty (2σ) for approximately the right reasons; that is, the models achieve accuracy in the surface wind stress forcing and the representation of the difference in the meridional density across the current. Improved observations allow for a better assessment of the SO circulation and its properties.

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

<p>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 first 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 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.</p>

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 Externally Forced and Internal Variability in Ensemble Climate Simulations of the Maunder Minimum

2005 ◽  
Vol 18 (20) ◽  
pp. 4253-4270 ◽  
Author(s):  
Masakazu Yoshimori ◽  
Thomas F. Stocker ◽  
Christoph C. Raible ◽  
Manuel Renold
Keyword(s):  
Time Scales ◽  
Climate Model ◽  
Signal To Noise Ratio ◽  
Surface Air Temperature ◽  
Volcanic Eruptions ◽  
Internal Variability ◽  
Maunder Minimum ◽  
Response Patterns ◽  
Near Surface ◽  
Transient Simulations

Abstract The response of the climate system to natural, external forcing during the Maunder Minimum (ca. a.d. 1645–1715) is investigated using a comprehensive climate model. An ensemble of six transient simulations is produced in order to examine the relative importance of externally forced and internally generated variability. The simulated annual Northern Hemisphere and zonal-mean near-surface air temperature agree well with proxy-based reconstructions on decadal time scales. A mean cooling signal during the Maunder Minimum is masked by the internal unforced variability in some regions such as Alaska, Greenland, and northern Europe. In general, temperature exhibits a better signal-to-noise ratio than precipitation. Mean salinity changes are found in basin averages. The model also shows clear response patterns to volcanic eruptions. In particular, volcanic forcing is projected onto the winter North Atlantic Oscillation index following the eruptions. It is demonstrated that the significant spread of ensemble members is possible even on multidecadal time scales, which has an important implication in coordinating comparisons between model simulations and regional reconstructions.

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.

Interpreting Results from the NARCCAP and NA-CORDEX Ensembles in the Context of Uncertainty in Regional Climate Change Projections

2018 ◽  
Vol 99 (10) ◽  
pp. 2093-2106 ◽  
Author(s):  
Ambarish V. Karmalkar
Keyword(s):  
Climate Change ◽  
North America ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Internal Variability ◽  
General Circulation Models ◽  
Eastern United States ◽  
The Impact

AbstractTwo ensembles of dynamically downscaled climate simulations for North America—the North American Regional Climate Change Assessment Program (NARCCAP) and the Coordinated Regional Climate Downscaling Experiment (CORDEX) featuring simulations for North America (NA-CORDEX)—are analyzed to assess the impact of using a small set of global general circulation models (GCMs) and regional climate models (RCMs) on representing uncertainty in regional projections. Selecting GCMs for downscaling based on their equilibrium climate sensitivities is a reasonable strategy, but there are regions where the uncertainty is not fully captured. For instance, the six NA-CORDEX GCMs fail to span the full ranges produced by models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) in summer temperature projections in the western and winter precipitation projections in the eastern United States. Similarly, the four NARCCAP GCMs are overall poor at spanning the full CMIP3 ranges in seasonal temperatures. For the Southeast, the NA-CORDEX GCMs capture the uncertainty in summer but not in winter projections, highlighting one consequence of downscaling a subset of GCMs. Ranges produced by the RCMs are often wider than their driving GCMs but are sensitive to the experimental design. For example, the downscaled projections of summer precipitation are of opposite polarity in two RCM ensembles in some regions. Additionally, the ability of the RCMs to simulate observed temperature trends is affected by the internal variability characteristics of both the RCMs and driving GCMs, and is not systematically related to their historical performance. This has implications for adequately sampling the impact of internal variability on regional trends and for using model performance to identify credible projections. These findings suggest that a multimodel perspective on uncertainties in regional projections is integral to the interpretation of RCM results.

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