scholarly journals Identifying Signatures of Natural Climate Variability in Time Series of Global-Mean Surface Temperature: Methodology and Insights

2009 ◽  
Vol 22 (22) ◽  
pp. 6120-6141 ◽  
Author(s):  
David W. J. Thompson ◽  
John M. Wallace ◽  
Phil D. Jones ◽  
John J. Kennedy
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Surface Temperature ◽  
High Latitude ◽  
Volcanic Eruptions ◽  
Natural Variability ◽  
Natural Climate Variability ◽  
Global Mean Surface Temperature ◽  
Natural Climate ◽  
Global Mean

Abstract Global-mean surface temperature is affected by both natural variability and anthropogenic forcing. This study is concerned with identifying and removing from global-mean temperatures the signatures of natural climate variability over the period January 1900–March 2009. A series of simple, physically based methodologies are developed and applied to isolate the climate impacts of three known sources of natural variability: the El Niño–Southern Oscillation (ENSO), variations in the advection of marine air masses over the high-latitude continents during winter, and aerosols injected into the stratosphere by explosive volcanic eruptions. After the effects of ENSO and high-latitude temperature advection are removed from the global-mean temperature record, the signatures of volcanic eruptions and changes in instrumentation become more clearly apparent. After the volcanic eruptions are subsequently filtered from the record, the residual time series reveals a nearly monotonic global warming pattern since ∼1950. The results also reveal coupling between the land and ocean areas on the interannual time scale that transcends the effects of ENSO and volcanic eruptions. Globally averaged land and ocean temperatures are most strongly correlated when ocean leads land by ∼2–3 months. These coupled fluctuations exhibit a complicated spatial signature with largest-amplitude sea surface temperature perturbations over the Atlantic Ocean.

scholarly journals Towards Reliable Probabilistic Time-Series Projections of Global Mean Surface Temperature

2021 ◽  
Author(s):  
Philip G. Sansom ◽  
Donald Cummins ◽  
Stefan Siegert ◽  
David B Stephenson
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Surface Temperature ◽  
Climate Model ◽  
Future Projections ◽  
Perfect Model ◽  
Global Mean Surface Temperature ◽  
Time Series Approach ◽  
Energy Balance Models ◽  
Global Mean

Abstract Quantifying the risk of global warming exceeding critical targets such as 2.0 ◦ C requires reliable projections of uncertainty as well as best estimates of Global Mean Surface Temperature (GMST). However, uncertainty bands on GMST projections are often calculated heuristically and have several potential shortcomings. In particular, the uncertainty bands shown in IPCC plume projections of GMST are based on the distribution of GMST anomalies from climate model runs and so are strongly determined by model characteristics with little influence from observations of the real-world. Physically motivated time-series approaches are proposed based on fitting energy balance models (EBMs) to climate model outputs and observations in order to constrain future projections. It is shown that EBMs fitted to one forcing scenario will not produce reliable projections when different forcing scenarios are applied. The errors in the EBM projections can be interpreted as arising due to a discrepancy in the effective forcing felt by the model. A simple time-series approach to correcting the projections is proposed based on learning the evolution of the forcing discrepancy so that it can be projected into the future. This approach gives reliable projections of GMST when tested in a perfect model setting. When applied to observations this leads to projected warming of 2.2 ◦ C (1.7 ◦ C to 2.9 ◦ C) in 2100 compared to pre-industrial conditions, 0.4 ◦ C lower than a comparable IPCC anomaly estimate. The probability of staying below the critical 2.0 ◦ C warming target in 2100 more than doubles to 0.28 compared to only 0.11 from a comparably IPCC estimate.

Climate variability following large volcanic eruption: CMIP6 model investigation

2021 ◽  
Author(s):  
Elizaveta Malinina ◽  
Nathan Gillett
Keyword(s):  
Climate Variability ◽  
Volcanic Eruption ◽  
Volcanic Eruptions ◽  
Arctic Sea Ice ◽  
Evaluation Tool ◽  
Global Mean Temperature ◽  
Arctic Sea ◽  
Global Mean Surface Temperature ◽  
Krakatoa Eruption ◽  
Global Mean

<p>Volcanic eruptions are an important driver of climate variability. Multiple literature sources have shown that after large explosive eruptions there is a decrease in global mean temperature, caused by an increased amount of stratospheric aerosols which influence the global radiative budget. In this study, we investigate the changes in several climate variables after a volcanic eruption. Using ESMValTool (Earth System Model Evaluation Tool) on an ensemble of historical simulations from CMIP6, such variables as global mean surface temperature (GMST), Arctic sea ice area and Nino 3.4 index were analyzed following the 1883 Krakatoa eruption. While there is a definite decrease in the multi-model mean GMST after the eruption, other indices do not show as prominent change. The reasons for this behavior are under investigation. </p>

scholarly journals Effects of strongly eddying oceans on multidecadal climate variability in the Community Earth System Model

Ocean Science ◽  
2021 ◽  
Vol 17 (5) ◽  
pp. 1251-1271
Author(s):  
André Jüling ◽  
Anna von der Heydt ◽  
Henk A. Dijkstra
Keyword(s):  
Climate Variability ◽  
Surface Temperature ◽  
Sea Surface ◽  
System Model ◽  
Earth System ◽  
Multidecadal Variability ◽  
Global Mean Surface Temperature ◽  
Ocean Flows ◽  
Community Earth System Model ◽  
Global Mean

Abstract. Climate variability on multidecadal timescales appears to be organized in pronounced patterns with clear expressions in sea surface temperature, such as the Atlantic Multidecadal Variability and the Pacific Decadal Oscillation. These patterns are now well studied both in observations and global climate models and are important in the attribution of climate change. Results from CMIP5 models have indicated large biases in these patterns with consequences for ocean heat storage variability and the global mean surface temperature. In this paper, we use two multi-century Community Earth System Model simulations at coarse (1∘) and fine (0.1∘) ocean model horizontal grid spacing to study the effects 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. In the strongly eddying model, multidecadal variability increases compared to sub-decadal variability. This shift of spectral power is seen in sea surface temperature indices, basin-scale surface heat fluxes, and the global mean surface temperature. This implies that the current CMIP6 model generation, which predominantly does not resolve the ocean mesoscale, may systematically underestimate multidecadal variability.

Precipitation and Temperature Variations on the Interannual Time Scale: Assessing the Impact of ENSO and Volcanic Eruptions

2011 ◽  
Vol 24 (9) ◽  
pp. 2258-2270 ◽  
Author(s):  
Guojun Gu ◽  
Robert F. Adler
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Surface Temperature ◽  
Volcanic Eruptions ◽  
Time Lags ◽  
Tropospheric Temperature ◽  
Precipitation Temperature ◽  
The Impact ◽  
Global Mean ◽  
Temperature Surface

Abstract The effects of ENSO and two large tropical volcanic eruptions (El Chichón, March 1982; Mt. Pinatubo, June 1991) are examined for the period of 1979–2008 using various satellite- and station-based observations of precipitation, temperature (surface and atmospheric), and tropospheric water vapor content. By focusing on the responses in the time series of tropical and global means over land, ocean, and land and ocean combined, the authors intend to provide an observational comparison of how these two phenomena, represented by Niño-3.4 and the tropical mean stratospheric aerosol optical thickness (τ), respectively, influence precipitation, temperature, and water vapor variations. As discovered in past studies, strong same-sign ENSO signals appear in tropical and global mean temperature (surface and tropospheric) over both land and ocean. However, ENSO only has very weak impact on tropical and global mean (land + ocean) precipitation, though intense anomalies are readily seen in the time series of precipitation averaged over either land or ocean. In contrast, the two volcanoes decreased not only tropical and global mean surface and tropospheric temperature but also tropical and global mean (land + ocean) precipitation. The differences between the responses to ENSO and volcanic eruptions are thus further examined by means of lag-correlation analyses. The ENSO-related peak responses in oceanic precipitation and sea surface temperature (SST) have the same time lags with Niño-3.4, 2 (4) months for the tropical (global) means. Tropical and global mean tropospheric water vapor over ocean (and land) generally follows surface temperature. However, land precipitation responds to ENSO much faster than temperature, suggesting a certain time needed for surface energy adjustment there following ENSO-related circulation and precipitation anomalies. Weak ENSO signals in the tropical and global mean mid- to lower-tropospheric atmospheric (dry) static instability are further discovered, which tend to be consistent with weak ENSO responses in the tropical and global mean (land + ocean) precipitation. For volcanic eruptions, tropical and global mean precipitation over either ocean or land responds faster than temperature (surface and atmospheric) and tropospheric water vapor averaged over the same areas, suggesting that precipitation tends to be more sensitive to volcanic-related solar forcing. The volcanic-related precipitation variations are further shown to be related to the changes in the mid- to lower-tropospheric atmospheric (dry) instability.

scholarly journals Effects of strongly eddying oceans on multidecadal climate variability in the Community Earth System Model

2020 ◽  
Author(s):  
André Jüling ◽  
Anna von der Heydt ◽  
Henk A. Dijkstra
Keyword(s):  
Climate Variability ◽  
Surface Temperature ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Multidecadal Variability ◽  
Global Mean Surface Temperature ◽  
Ocean Flows ◽  
Community Earth System Model ◽  
Global Mean

Abstract. Climate variability on multidecadal time scales appears to be organized in pronounced patterns with clear expressions in sea surface temperature, such as the Atlantic Multidecadal Variability and the Pacific Decadal Oscillation. These patterns are now well studied both in observations and global climate models and are important in the attribution of climate change. Results from CMIP5 models have indicated large biases in these patterns with consequences for ocean heat storage variability and eventually the global mean surface temperature. In this paper, we use two multi-century Community Earth System Model simulations at coarse (1°) and fine (0.1°) ocean model horizontal grid spacing to study the effects 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. The effect on the global mean surface temperature is relatively minor.

scholarly journals Quantifying the impact of early 21st century volcanic eruptions on global-mean surface temperature

2017 ◽  
Vol 12 (5) ◽  
pp. 054010 ◽  
Author(s):  
Paul-Arthur Monerie ◽  
Marie-Pierre Moine ◽  
Laurent Terray ◽  
Sophie Valcke
Keyword(s):  
Surface Temperature ◽  
21St Century ◽  
Volcanic Eruptions ◽  
Early 21St Century ◽  
Global Mean Surface Temperature ◽  
The Impact ◽  
Global Mean

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>

Simulation and Projection of Global Mean Surface Temperature Using the Empirical Model of Global Climate and Comparison to CMIP6 GCMs

2021 ◽  
Author(s):  
Laura McBride ◽  
Austin Hope ◽  
Timothy Canty ◽  
Walter Tribett ◽  
Brian Bennett ◽  
...  
Keyword(s):  
Global Warming ◽  
Greenhouse Gases ◽  
Surface Temperature ◽  
Empirical Model ◽  
Global Climate ◽  
Volcanic Eruptions ◽  
Climate Record ◽  
Global Mean Surface Temperature ◽  
Global Mean ◽  
Human Component

<p>The Empirical Model of Global Climate (EM-GC) (Canty et al., ACP, 2013, McBride et al., ESDD, 2020) is a multiple linear regression, energy balance model that accounts for the natural influences on global mean surface temperature due to ENSO, the 11-year solar cycle, major volcanic eruptions, as well as the anthropogenic influence of greenhouse gases and aerosols and the efficiency of ocean heat uptake. First, we will analyze the human contribution of global warming from 1975-2014 based on the climate record, also known as the attributable anthropogenic warming rate (AAWR). We will compare the values of AAWR found using the EM-GC with values of AAWR from the CMIP6 multi-model ensemble. Preliminary analysis indicates that over the past three decades, the human component of global warming inferred from the CMIP6 GCMs is larger than the human component of warming from the climate record. Second, we will compare values of equilibrium climate sensitivity inferred from the historical climate record to those determined from CMIP6 GCMs using the Gregory et al., GRL, 2004 method. Third, we will use the future abundances of greenhouse gases and aerosols provided by the Shared Socioeconomic Pathways (SSPs) to project future global mean surface temperature change. We will compare the projections of future temperature anomalies from CMIP6 GCMs to those determined by the EM-GC. We will conclude by assessing the probability of the CMIP6 and EM-GC projections of achieving the Paris Agreement target (1.5°C) and upper limit (2.0°C) for several of the SSP scenarios.</p>

scholarly journals Recent warming inconsistent with natural association between temperature and atmospheric circulation over the last 2000 years

2006 ◽  
Vol 2 (3) ◽  
pp. 327-355 ◽  
Author(s):  
P. A. Mayewski ◽  
K. A. Maasch
Keyword(s):  
Climate Variability ◽  
Atmospheric Circulation ◽  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
High Latitude ◽  
Natural Climate Variability ◽  
The Past ◽  
Past 2000 Years ◽  
Hemisphere Temperature ◽  
Natural Climate

Abstract. Comparison between proxies for atmospheric circulation and temperature reveals associations over the last few decades that are inconsistent with those of the past 2000 years. Notably, patterns of middle to high latitude atmospheric circulation in both hemispheres are still within the range of variability of the last 6–10 centuries while, as demonstrated by Mann and Jones (2003), Northern Hemisphere temperatures over recent decades are the highest of the last 2000 years. Further, recent temperature change precedes change in middle to high latitude atmospheric circulation unlike the two most notable changes in climate of the past 2000 years during which change in atmospheric circulation preceded or coincided with change in temperature. In addition, the most prominent change in Southern Hemisphere temperature and atmospheric circulation of the past 2000, and probably 9000 years, precedes change in temperature and atmospheric circulation in the Northern Hemisphere unlike the recent change in Northern Hemisphere temperature that leads. These findings provide new verification that recent rise in temperature is inconsistent with natural climate variability and is most likely related to anthropogenic activity in the form of enhanced greenhouse gases. From our investigation we conclude that the delayed warming over much of the Southern Hemisphere may be, in addition to other factors, a consequence of underpinning by natural climate variability. Further bipolar comparison of proxy records of atmospheric circulation demonstrates that change in atmospheric circulation in the Southern Hemisphere led by 400 years, the most abrupt change in Northern Hemisphere atmospheric circulation of the last 9000 years. This finding may be highly relevant to understanding a future when warming becomes more fully established in the Southern Hemisphere.

scholarly journals Flood history of the Bavarian Alpine Foreland since the late Middle Ages in the context of internal and external climate forcing factors

2014 ◽  
Vol 11 (7) ◽  
pp. 7409-7440 ◽  
Author(s):  
O. Böhm ◽  
J. Jacobeit ◽  
R. Glaser ◽  
K.-F. Wetzel
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Variability ◽  
Little Ice Age ◽  
Ice Age ◽  
Natural Climate Variability ◽  
Long Time ◽  
History Of ◽  
Alpine Foreland ◽  
Natural Climate

Abstract. This paper describes the flood history of the Bavarian part of the Alpine Foreland of Germany and addresses different questions concerning climate variability and flood frequencies from the 13th century until today. Will recent climatic change modify the flood frequencies within the Bavarian Alpine Foreland or are the flood frequencies varying due to altering climatic conditions since historical times? In the context of recent discussions whether man-made climate change will modify the present state of flood frequencies, a look back into the past is essential to understand the occurrence of floods in general and of recent floods in particular. In order to understand climatic variability and changes in a comprehensive way, it is necessary to review long time series. A perceived increase of summer floods in eastern Germany and Bavaria since 1997 requires examination of long time series to estimate changes in flood frequencies in a proper way. In view of the annual distribution of flood events within the Alpine Foreland of Germany, summer floods prove to be most important. Based on written historical sources, the flood history of the Alpine Foreland of Germany can be reconstructed back to the 14th century. One major result is the occurrence of "flood-rich" and "flood-poor" episodes in nearly cyclical sequences. Flood-rich periods were recorded in the periods 1300–1335, 1370–1450, 1470–1525, 1555–1590, 1615–1665, 1730–1780, 1820–1870, and 1910–1955 as well as in a 9th period beginning in 1980. The flood-rich periods are characterized by longer flood durations. Most of the flood-rich and flood-poor periods (in particular the beginning and the end of them) can be connected to changes in natural climate variability. These include changing sunspot numbers (as a measure of solar activity), so-called Little Ice Age Type Events (LIATEs) as well as changes in the North Atlantic Oscillation (NAO). Climate signals from external forcing factors, which could be used to explain the changing flood frequencies in the Bavarian Alpine Foreland, end in 1930. Relationships within the climate system such as the correlation of flood frequencies with the NAO have changed during the transition from the post Little Ice Age period to the Modern Climate Optimum around 1930. Natural climate variability might have been outperformed by anthropogenic climate change.

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