scholarly journals The Life and Death of the Hiatus Consistently Explained

2018 ◽  
Author(s):  
Kristoffer Rypdal
Keyword(s):  
Long Memory ◽  
Southern Oscillation ◽  
Thermal Inertia ◽  
Volcanic Eruptions ◽  
Delayed Response ◽  
Small Contribution ◽  
Life And Death ◽  
Model Driven ◽  
Global Mean Surface Temperature ◽  
Global Mean

The main features of the instrumental global mean surface temperature (GMST) are reasonably well described by a simple linear response model driven by anthropogenic, volcanic and solar forcing. This model acts as a linear long-memory filter of the forcing signal. The physical interpretation of this filtering is the delayed response due to the thermal inertia of the ocean. This description is considerably more accurate if El Ni\~{n}o Southern Oscillation (ENSO) and the Atlantic Multi-decadal Oscillation (AMO) are regarded as additional forcing of the global temperature and hence subject to the same filtering as the other forcing components. By considering these as predictors in a linear regression scheme, more than 92\% of the variance in the instrumental GMST over the period 1870-2017 is explained by this model, and in particular all features of the 1998 -- 2015 hiatus, including its death. While the more prominent pauses during 1870 -- 1915 and 1940 -- 1970 can be attributed to clustering in time of strong volcanic eruptions, the recent hiatus is an unremarkable phenomenon that is attributed to ENSO and a small contribution from solar activity.

scholarly journals The Life and Death of the Recent Global Surface Warming Hiatus Parsimoniously Explained

Climate ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 64 ◽  
Author(s):  
Kristoffer Rypdal
Keyword(s):  
Southern Oscillation ◽  
Thermal Inertia ◽  
Volcanic Eruptions ◽  
Atlantic Multidecadal Oscillation ◽  
Delayed Response ◽  
Small Contribution ◽  
Surface Warming ◽  
Life And Death ◽  
Model Driven ◽  
Warming Hiatus

The main features of the instrumental global mean surface temperature (GMST) are reasonably well described by a simple linear response model driven by anthropogenic, volcanic and solar forcing. This model acts as a linear long-memory filter of the forcing signal. The physical interpretation of this filtering is the delayed response due to the thermal inertia of the ocean. This description is considerably more accurate if El Niño Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO) are regarded as additional forcings of the global temperature and hence subject to the same filtering as the other forcing components. By considering these as predictors in a linear regression scheme, more than 92% of the variance in the instrumental GMST over the period 1870–2017 is explained by this model, in particular, all features of the 1998–2015 hiatus, including its death. While the more prominent pauses during 1870–1915 and 1940–1970 can be attributed to clustering in time of strong volcanic eruptions, the recent hiatus is an unremarkable phenomenon that is attributed to ENSO with a small contribution from solar activity.

Dwindling impact of large volcanic eruptions on global glacier changes in the Anthropocene

2021 ◽  
Author(s):  
Michael Zemp ◽  
Ben Marzeion
Keyword(s):  
Solar Activity ◽  
Southern Oscillation ◽  
Volcanic Eruptions ◽  
Anthropogenic Influences ◽  
Positive Mass ◽  
Climate Conditions ◽  
Glacier Changes ◽  
Global Mean Surface Temperature ◽  
Large Volcanic Eruptions ◽  
Global Mean

<p>Large volcanic eruptions impact climate through the injection of ash and sulfur gas into the atmosphere. While the ash particles fall out rapidly, the gas is converted to sulfate aerosols, which reflect solar radiation in the stratosphere and cause a cooling of the global mean surface temperature. Earlier studies suggested that major volcanic eruptions resulted in positive mass balances and advances of glaciers. Here we perform a multivariate analysis to decompose global glacier mass changes from 1961 to 2005 into components associated with anthropogenic influences, volcanic and solar activity, and El Niño Southern Oscillation (ENSO). We find that the global glacier mass loss was mainly driven by the anthropogenic forcing, interrupted by a few years of intermittent mass gains following large volcanic eruptions. The relative impact of volcanic eruptions is dwindling due to strongly increasing greenhouse gas concentrations since the mid of the 20<sup>th</sup> century. Furthermore, our study indicates that solar activity and ENSO have limited impacts on climate conditions at glacier locations and that volcanic eruptions alone can hardly explain decadal periods of glacier advances documented since the 16<sup>th</sup> century.</p>

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 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 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

scholarly journals Current rapid global temperature rise linked to falling SO<sub>2</sub> emissions

2018 ◽  
Author(s):  
Nick E. B. Cowern
Keyword(s):  
Heat Exchange ◽  
Solar Irradiance ◽  
Southern Oscillation ◽  
Volcanic Eruptions ◽  
Global Temperature ◽  
Climate Forcing ◽  
Accurate Estimation ◽  
Tropospheric Aerosol ◽  
Ocean Atmosphere ◽  
Global Mean

Abstract. It is widely held that global temperature variations on time scales of a decade or less are primarily caused by internal climate variability, with smaller contributions from changes in external climate forcing such as solar irradiance. This paper shows that observed variations in global mean surface temperature, TGS, and ocean heat content (OHC) during the last 1–2 decades imply major changes in climate forcing during this period. In a first step, two independent methods are used to evaluate global temperature corrected for ocean–atmosphere heat exchange. El Niño/Southern Oscillation (ENSO) corrected TGS (written as TGS) is shown to agree closely with a novel temperature metric θ that combines uncorrected TGS with scaled OHC. This agreement rules out a substantial 21st-century contribution to TGS from ocean-atmosphere heat exchange. In contrast to TGS, the time series TGS (t) provides a clear fingerprint of transient global cooling associated with major volcanic eruptions, enabling a more accurate empirical estimate of the climate response of the global mean surface. This allows more accurate estimation of the net climate forcing by stratospheric aerosols and solar irradiance, which is then subtracted from TGS (t) to determine the underlying signal of anthropogenic global warming. Key features of this signal are a slowdown from the late 1990s to 2011 – corresponding to the well known climate hiatus – and a subsequent sharp upturn indicating a steep increase in anthropogenic climate forcing. It is argued that the only plausible cause for this increase is a large fractional decrease in tropospheric aerosol cooling. This attribution is supported by satellite-based observations of a > 50 % decrease in SO2 emissions from large sources during the last six years. It suggests that current clean-air policies and replacement of coal by natural gas are driving a significant human made climatic event, 2–4 times faster than greenhouse driven warming alone. If confirmed, this implies a considerably shortened timescale to meet the IPCC 1.5 °C objective, with major implications for near-term carbon emission policies.

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

&lt;p&gt;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&amp;#176;C) and upper limit (2.0&amp;#176;C) for several of the SSP scenarios.&lt;/p&gt;

scholarly journals An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature

2013 ◽  
Vol 4 (2) ◽  
pp. 743-783 ◽  
Author(s):  
A. Tantet ◽  
H. A. Dijkstra
Keyword(s):  
Community Structure ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Southern Oscillation ◽  
Function Analysis ◽  
Interaction Network ◽  
Sea Surface ◽  
Global Mean Surface Temperature ◽  
Global Mean

Abstract. On interannual-to-multidecadal time scales variability in sea surface temperature appears to be organized in large-scale spatiotemporal patterns. In this paper, we investigate these patterns by studying the community structure of interaction networks constructed from sea surface temperature observations. Much of the community structure as well as the first neighbour maps can be interpreted using known dominant patterns of variability, such as the El Niño/Southern Oscillation and the Atlantic Multidecadal Oscillation and teleconnections. The community detection method allows to overcome some shortcomings of Empirical Orthogonal Function analysis or composite analysis and hence provides additional information with respect to these classical analysis tools. The community analysis provides also new insight into the relationship between patterns of sea surface temperature and the global mean surface temperature (GMST). On the decadal-to-multidecadal time scale, we show that only two communities (Indian Ocean and North Atlantic) determine most of the GMST variability.

scholarly journals ENSO sensitivity to radiative forcing

2020 ◽  
Author(s):  
Evgeniya Predybaylo ◽  
Georgiy Stenchikov ◽  
Andrew Wittenberg ◽  
Sergey Osipov
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Southern Oscillation ◽  
Volcanic Eruptions ◽  
Boreal Winter ◽  
Unified Framework ◽  
Surface Cooling ◽  
Radiative Forcings ◽  
Global Mean ◽  
Eruption Magnitude

&lt;p&gt;To improve El Ni&amp;#241;o / Southern Oscillation (ENSO) predictions and projections in a changing climate, it is essential to better understand ENSO&amp;#8217;s sensitivities to external radiative forcings. Strong volcanic eruptions can help to clarify ENSO&amp;#8217;s sensitivities, mechanisms, and feedbacks. Strong explosive volcanic eruptions inject millions of tons of sulfur dioxide into the stratosphere, where they are converted into sulfate aerosols. For equatorial volcanoes, these aerosols can spread globally, scattering and absorbing incoming sunlight, and inducing a global-mean surface cooling. Despite this global-mean cooling effect, paleo data confirm remarkable warming of the eastern equatorial Pacific in the two years after a tropical eruption, with a shift towards an El Ni&amp;#241;o-like state. To illuminate this response and explain why it tends to occur during particular seasons and ENSO phases, we present a unified framework that includes the roles of the seasonal cycle, stochastic wind forcing, eruption magnitude, and various tropical Pacific climate feedbacks. Analyzing over 20,000 years of large-ensemble simulations from the GFDL-CM2.1 climate model forced by volcanic eruptions, we find that the ENSO response comprises both stochastic and deterministic components, which vary depending on the perturbation season and the ocean preconditioning. For boreal winter eruptions, stochastic dispersion largely obscures the deterministic response, being the largest for the strong El Ni&amp;#241;o preconditioning. Deterministic El Ni&amp;#241;o-like responses to summer eruptions are well seen on neutral ENSO and weak to moderate El Ni&amp;#241;o preconditioning and grow with the eruption magnitude. The relative balance of these components determines the predictability and strength of the ENSO response. The results clarify why previous studies obtained seemingly conflicting results.&lt;/p&gt;

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