Resolving the differences in the simulated and reconstructed climate response to volcanism over the last millennium

2020 ◽  
Author(s):  
Feng Zhu ◽  
Julien Emile-Geay ◽  
Greg Hakim ◽  
Jonathan King ◽  
Kevin Anchukaitis
Keyword(s):  
Tree Ring ◽  
Radiative Forcing ◽  
Natural Experiment ◽  
Climate Model ◽  
Simulated Data ◽  
Growing Season ◽  
Explosive Volcanism ◽  
Last Millennium ◽  
Climate Response ◽  
Climate Model Simulations

<p>Explosive volcanism imposes impulse-like radiative forcing on the climate system, providing a natural experiment to study the climate response to perturbation. Previous studies have identified disagreements between paleoclimate reconstructions and climate model simulations (GCMs) with respect to the magnitude and recovery from volcanic cooling, questioning the fidelity of GCMs, reconstructions, or both. Using the paleoenvironmental data assimilation framework of the Last Millennium Reanalysis, this study investigates the causes of the disagreements, using both real and simulated data. We demonstrate that the disagreement may be resolved by assimilating tree-ring density records only, by targeting growing-season temperature instead of annual temperature, and by performing the comparison at proxy locales. Our work suggests that discrepancies between paleoclimate models and data can be largely resolved by accounting for these features of tree-ring proxy networks.</p>

scholarly journals Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 3: Practical considerations, relaxed assumptions, and using tree-ring data to address the amplitude of solar forcing

2014 ◽  
Vol 10 (3) ◽  
pp. 2627-2683
Author(s):  
A. Moberg ◽  
R. Sundberg ◽  
H. Grudd ◽  
A. Hind
Keyword(s):  
Tree Ring ◽  
Large Amplitude ◽  
Small Amplitude ◽  
Climate Model ◽  
Last Millennium ◽  
Solar Forcing ◽  
Proxy Data ◽  
Statistical Framework ◽  
Tree Ring Data ◽  
Climate Model Simulations

Abstract. Practical issues arise when applying a statistical framework for unbiased ranking of alternative forced climate model simulations by comparison with climate observations from instrumental and proxy data (Part 1 in this series). Given a set of model and observational data, several decisions need to be made; e.g. concerning the region that each proxy series represents, the weighting of different regions, and the time resolution to use in the analysis. Objective selection criteria cannot be made here, but we argue to study how sensitive the results are to the choices made. The framework is improved by the relaxation of two assumptions; to allow autocorrelation in the statistical model for simulated climate variability, and to enable direct comparison of alternative simulations to test if any of them fit the observations significantly better. The extended framework is applied to a set of simulations driven with forcings for the pre-industrial period 1000–1849 CE and fifteen tree-ring based temperature proxy series. Simulations run with only one external forcing (land-use, volcanic, small-amplitude solar, or large-amplitude solar), do not significantly capture the variability in the tree-ring data – although the simulation with volcanic forcing does so for some experiment settings. When all forcings are combined (using either the small- or large-amplitude solar forcing) including also orbital, greenhouse-gas and non-volcanic aerosol forcing, and additionally used to produce small simulation ensembles starting from slightly different initial ocean conditions, the resulting simulations are highly capable of capturing some observed variability. Nevertheless, for some choices in the experiment design, they are not significantly closer to the observations than when unforced simulations are used, due to highly variable results between regions. It is also not possible to tell whether the small-amplitude or large-amplitude solar forcing causes the multiple-forcing simulations to be closer to the reconstructed temperature variability. This suggests that proxy data from more regions and proxy types, or representing larger regions and other seasons, are needed for more conclusive results from model-data comparisons in the last millennium.

scholarly journals Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 3: Practical considerations, relaxed assumptions, and using tree-ring data to address the amplitude of solar forcing

2015 ◽  
Vol 11 (3) ◽  
pp. 425-448 ◽  
Author(s):  
A. Moberg ◽  
R. Sundberg ◽  
H. Grudd ◽  
A. Hind
Keyword(s):  
Tree Ring ◽  
Large Amplitude ◽  
Small Amplitude ◽  
Climate Model ◽  
Last Millennium ◽  
Solar Forcing ◽  
Proxy Data ◽  
Statistical Framework ◽  
Tree Ring Data ◽  
Climate Model Simulations

Abstract. A statistical framework for evaluation of climate model simulations by comparison with climate observations from instrumental and proxy data (part 1 in this series) is improved by the relaxation of two assumptions. This allows autocorrelation in the statistical model for simulated internal climate variability and enables direct comparison of two alternative forced simulations to test whether one fits the observations significantly better than the other. The extended framework is applied to a set of simulations driven with forcings for the pre-industrial period 1000–1849 CE and 15 tree-ring-based temperature proxy series. Simulations run with only one external forcing (land use, volcanic, small-amplitude solar, or large-amplitude solar) do not significantly capture the variability in the tree-ring data – although the simulation with volcanic forcing does so for some experiment settings. When all forcings are combined (using either the small- or large-amplitude solar forcing), including also orbital, greenhouse-gas and non-volcanic aerosol forcing, and additionally used to produce small simulation ensembles starting from slightly different initial ocean conditions, the resulting simulations are highly capable of capturing some observed variability. Nevertheless, for some choices in the experiment design, they are not significantly closer to the observations than when unforced simulations are used, due to highly variable results between regions. It is also not possible to tell whether the small-amplitude or large-amplitude solar forcing causes the multiple-forcing simulations to be closer to the reconstructed temperature variability. Proxy data from more regions and of more types, or representing larger regions and complementary seasons, are apparently needed for more conclusive results from model–data comparisons in the last millennium.

scholarly journals A data assimilation approach to last millennium temperature field reconstruction using a limited high-sensitivity proxy network

2021 ◽  
pp. 1-64
Author(s):  
Jonathan M. King ◽  
Kevin J. Anchukaitis ◽  
Jessica E. Tierney ◽  
Gregory J. Hakim ◽  
Julien Emile-Geay ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Tree Ring ◽  
Radiative Forcing ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Spatial Uncertainty ◽  
Ice Age ◽  
Temperature Sensitive ◽  
Last Millennium ◽  
Uncertainty Estimates

AbstractWe use theNorthern Hemisphere Tree-RingNetwork Development (NTREND) tree-ring database to examine the effects of using a small, highly-sensitive proxy network for paleotemperature data assimilation over the last millennium. We first evaluate our methods using pseudo-proxy experiments. These indicate that spatial assimilations using this network are skillful in the extratropical Northern Hemisphere and improve on previous NTREND reconstructions based on Point-by-Point regression. We also find our method is sensitive to climate model biases when the number of sites becomes small. Based on these experiments, we then assimilate the real NTREND network. To quantify model prior uncertainty, we produce 10 separate reconstructions, each assimilating a different climate model. These reconstructions are most dissimilar prior to 1100 CE, when the network becomes sparse, but show greater consistency as the network grows. Temporal variability is also underestimated before 1100 CE. Our assimilation method produces spatial uncertainty estimates and these identify treeline North America and eastern Siberia as regions that would most benefit from development of new millennial-length temperature-sensitive tree-ring records. We compare our multi-model mean reconstruction to five existing paleo-temperature products to examine the range of reconstructed responses to radiative forcing. We find substantial differences in the spatial patterns and magnitudes of reconstructed responses to volcanic eruptions and in the transition between the Medieval epoch and Little Ice Age. These extant uncertainties call for the development of a paleoclimate reconstruction intercomparison framework for systematically examining the consequences of proxy network composition and reconstruction methodology and for continued expansion of tree-ring proxy networks.

scholarly journals Anthropogenic forcing and response yield observed positive trend in Earth’s energy imbalance

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shiv Priyam Raghuraman ◽  
David Paynter ◽  
V. Ramaswamy
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Solar Spectrum ◽  
Internal Variability ◽  
Satellite Observations ◽  
Positive Trend ◽  
Energy Imbalance ◽  
Model Simulations ◽  
Heat Uptake ◽  
Climate Model Simulations

AbstractThe observed trend in Earth’s energy imbalance (TEEI), a measure of the acceleration of heat uptake by the planet, is a fundamental indicator of perturbations to climate. Satellite observations (2001–2020) reveal a significant positive globally-averaged TEEI of 0.38 ± 0.24 Wm−2decade−1, but the contributing drivers have yet to be understood. Using climate model simulations, we show that it is exceptionally unlikely (<1% probability) that this trend can be explained by internal variability. Instead, TEEI is achieved only upon accounting for the increase in anthropogenic radiative forcing and the associated climate response. TEEI is driven by a large decrease in reflected solar radiation and a small increase in emitted infrared radiation. This is because recent changes in forcing and feedbacks are additive in the solar spectrum, while being nearly offset by each other in the infrared. We conclude that the satellite record provides clear evidence of a human-influenced climate system.

Why does the climate response to greenhouse warming and greenhouse cooling differ? 

2021 ◽  
Author(s):  
Jennifer Kay ◽  
Jason Chalmers
Keyword(s):  
Carbon Dioxide ◽  
Radiative Forcing ◽  
Climate Model ◽  
Temperature Response ◽  
Greenhouse Warming ◽  
Climate Response ◽  
Cloud Feedbacks ◽  
Surface Climate ◽  
Carbon Dioxide Concentrations ◽  
Radiative Feedbacks

&lt;p&gt;While the long-standing quest to constrain equilibrium climate sensitivity has resulted in intense scrutiny of the processes controlling idealized greenhouse warming, the processes controlling idealized greenhouse cooling have received less attention. Here, differences in the climate response to increased and decreased carbon dioxide concentrations are assessed in state-of-the-art fully coupled climate model experiments. One hundred and fifty years after an imposed instantaneous forcing change, surface global warming from a carbon dioxide doubling (abrupt-2xCO2, 2.43 K) is larger than the surface global cooling from a carbon dioxide halving (abrupt-0p5xCO2, 1.97 K). Both forcing and feedback differences explain these climate response differences. Multiple approaches show the radiative forcing for a carbon dioxide doubling is ~10% larger than for a carbon dioxide halving. In addition, radiative feedbacks are less negative in the doubling experiments than in the halving experiments. Specifically, less negative tropical shortwave cloud feedbacks and more positive subtropical cloud feedbacks lead to more greenhouse 2xCO2 warming than 0.5xCO2 greenhouse cooling. Motivated to directly isolate the influence of cloud feedbacks on these experiments, additional abrupt-2xCO2 and abrupt-0p5xCO2 experiments with disabled cloud-climate feedbacks were run. Comparison of these &amp;#8220;cloud-locked&amp;#8221; simulations with the original &amp;#8220;cloud active&amp;#8221; simulations shows cloud feedbacks help explain the nonlinear global surface temperature response to greenhouse warming and greenhouse cooling. Overall, these results demonstrate that both radiative forcing and radiative feedbacks are needed to explain differences in the surface climate response to increased and decreased carbon dioxide concentrations.&lt;/p&gt;

Large ensemble assessment of how the global surface warming response to cumulative carbon differs for negative and positive carbon emissions  

2021 ◽  
Author(s):  
Negar Vakilifard ◽  
Katherine Turner ◽  
Ric Williams ◽  
Philip Holden ◽  
Neil Edwards ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Radiative Forcing ◽  
Climate Model ◽  
Climate Feedback ◽  
Climate Response ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Surface Warming ◽  
Radiative Processes ◽  
Negative Emission

&lt;p&gt;The controls of the effective transient climate response (TCRE), defined in terms of the dependence of surface warming since the pre-industrial to the cumulative carbon emission, is explained in terms of climate model experiments for a scenario including positive emissions and then negative emission over a period of 400 years. We employ a pre-calibrated ensemble of GENIE, grid-enabled integrated Earth system model, consisting of 86 members to determine the process of controlling TCRE in both CO&lt;sub&gt;2&lt;/sub&gt; emissions and drawdown phases. Our results are based on the GENIE simulations with historical forcing from AD 850 including land use change, and the future forcing defined by CO&lt;sub&gt;2&lt;/sub&gt; emissions and a non-CO&lt;sub&gt;2&lt;/sub&gt; radiative forcing timeseries. We present the results for the point-source carbon capture and storage (CCS) scenario as a negative emission scenario, following the medium representative concentration pathway (RCP4.5), assuming that the rate of emission drawdown is 2 PgC/yr CO&lt;sub&gt;2&lt;/sub&gt; for the duration of 100 years. The climate response differs between the periods of positive and negative carbon emissions with a greater ensemble spread during the negative carbon emissions. The controls of the spread in ensemble responses are explained in terms of a combination of thermal processes (involving ocean heat uptake and physical climate feedback), radiative processes (saturation in radiative forcing from CO&lt;sub&gt;2&lt;/sub&gt; and non-CO&lt;sub&gt;2&lt;/sub&gt; contributions) and carbon dependences (involving terrestrial and ocean carbon uptake).&amp;#160;&amp;#160;&lt;/p&gt;

scholarly journals Teleconnections and relationship between the El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) in reconstructions and models over the past millennium

2020 ◽  
Vol 16 (2) ◽  
pp. 743-756 ◽  
Author(s):  
Christoph Dätwyler ◽  
Martin Grosjean ◽  
Nathan J. Steiger ◽  
Raphael Neukom
Keyword(s):  
Climate Model ◽  
El Nino ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Last Millennium ◽  
Annular Mode ◽  
Model Simulations ◽  
The Past ◽  
Climate Model Simulations ◽  
Past Millennium

Abstract. The climate of the Southern Hemisphere (SH) is strongly influenced by variations in the El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode (SAM). Because of the limited length of instrumental records in most parts of the SH, very little is known about the relationship between these two key modes of variability over time. Using proxy-based reconstructions and last-millennium climate model simulations, we find that ENSO and SAM indices are mostly negatively correlated over the past millennium. Pseudo-proxy experiments indicate that currently available proxy records are able to reliably capture ENSO–SAM relationships back to at least 1600 CE. Palaeoclimate reconstructions show mostly negative correlations back to about 1400 CE. An ensemble of last-millennium climate model simulations confirms this negative correlation, showing a stable correlation of approximately −0.3. Despite this generally negative relationship we do find intermittent periods of positive ENSO–SAM correlations in individual model simulations and in the palaeoclimate reconstructions. We do not find evidence that these relationship fluctuations are caused by exogenous forcing nor by a consistent climate pattern. However, we do find evidence that strong negative correlations are associated with strong positive (negative) anomalies in the Interdecadal Pacific Oscillation and the Amundsen Sea Low during periods when SAM and ENSO indices are of opposite (equal) sign.

scholarly journals Evaluating Climate Model Simulations of the Radiative Forcing and Radiative Response at Earth’s Surface

2019 ◽  
Vol 32 (13) ◽  
pp. 4089-4102 ◽  
Author(s):  
Ryan J. Kramer ◽  
Brian J. Soden ◽  
Angeline G. Pendergrass
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Lapse Rate ◽  
Radiation Budget ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract We analyze the radiative forcing and radiative response at Earth’s surface, where perturbations in the radiation budget regulate the atmospheric hydrological cycle. By applying a radiative kernel-regression technique to CMIP5 climate model simulations where CO2 is instantaneously quadrupled, we evaluate the intermodel spread in surface instantaneous radiative forcing, radiative adjustments to this forcing, and radiative responses to surface warming. The cloud radiative adjustment to CO2 forcing and the temperature-mediated cloud radiative response exhibit significant intermodel spread. In contrast to its counterpart at the top of the atmosphere, the temperature-mediated cloud radiative response at the surface is found to be positive in some models and negative in others. Also, the compensation between the temperature-mediated lapse rate and water vapor radiative responses found in top-of-atmosphere calculations is not present for surface radiative flux changes. Instantaneous radiative forcing at the surface is rarely reported for model simulations; as a result, intermodel differences have not previously been evaluated in global climate models. We demonstrate that the instantaneous radiative forcing is the largest contributor to intermodel spread in effective radiative forcing at the surface. We also find evidence of differences in radiative parameterizations in current models and argue that this is a significant, but largely overlooked, source of bias in climate change simulations.

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