Resolving the Differences in the Simulated and Reconstructed Temperature Response to Volcanism

Zhu, Feng; Emile‐Geay, Julien; Hakim, Gregory J.; King, John D.; Anchukaitis, Kevin J.

doi:10.1029/2019gl086908

Cited by 39 publications

(36 citation statements)

References 92 publications

(168 reference statements)

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“…The seasonal information revealed by QWA can also be incorporated directly in proxy systems modeling within data assimilation approaches to climate field reconstruction (Tardif et al., 2019). Previous mismatches between modeled volcanic forcing and proxy observations have been traced in part to the type of proxy data used (Esper et al., 2015; Zhu et al., 2020). MXD is still considered the most appropriate proxy to detect volcanic cooling signals and provides the most robust temperature reconstructions, but calibration of the proxy with the instrumental record necessarily assumes that it directly or indirectly reflects temperatures integrated over the entire summer or extended growing season.…”

Section: Resultsmentioning

confidence: 99%

“…In the case of the Laki eruption, which began in June, MXD reconstructions probably overestimate the duration and magnitude of the cooling over northern Alaska when calibrated against average summer temperatures. Beyond improving spatial coverage of MXD networks (K. J. Anchukaitis et al., 2017; Esper et al., 2018; Zhu et al., 2020), a better understanding of the growth‐environment relationship is needed to understand how trees as proxies record volcanic forcing. QWA provides a valuable new tool for more precisely quantifying the timing and magnitude of the climate response to volcanism, and long continuous QWA chronologies could help support more accurate reconstructions of last millennium.…”

Section: Resultsmentioning

confidence: 99%

“…However, there remain significant discrepancies between the climate responses to volcanic eruptions in climate model simulations and those estimated from proxy reconstructions in both magnitude and duration (K. J. Anchukaitis et al., 2012; D'Arrigo et al., 2013; LeGrande & Anchukaitis, 2015; S. Stevenson et al., 2017; Stoffel et al., 2015; Wilson et al., 2016). Among the main sources of uncertainty in climate reconstructions themselves are the spatial coverage of the proxy network, the seasonal window recorded by the proxies, and biological memory and other nonclimatic or noise components of the proxy signal (K. J. Anchukaitis et al., 2012; D'Arrigo et al., 2013; Zhu et al., 2020). The precise timing of the eruption (S. Stevenson et al., 2017), the magnitude (Stoffel et al., 2015; Timmreck et al., 2009), the spatial distribution of aerosol loading (D. P. Schneider et al., 2009; Toohey & Sigl, 2017; Toohey et al., 2019), and representation of important aerosol processes (Aubry et al., 2020; LeGrande et al., 2016; Mann et al., 2015; Marshall et al., 2019; Mills et al., 2016; Pinto et al., 1989; A. Schmidt et al., 2018; Timmreck et al., 2010) are all major sources of uncertainty in model simulations.…”

Section: Introductionmentioning

confidence: 99%

“…The precise timing of the eruption (S. Stevenson et al., 2017), the magnitude (Stoffel et al., 2015; Timmreck et al., 2009), the spatial distribution of aerosol loading (D. P. Schneider et al., 2009; Toohey & Sigl, 2017; Toohey et al., 2019), and representation of important aerosol processes (Aubry et al., 2020; LeGrande et al., 2016; Mann et al., 2015; Marshall et al., 2019; Mills et al., 2016; Pinto et al., 1989; A. Schmidt et al., 2018; Timmreck et al., 2010) are all major sources of uncertainty in model simulations. Discrepancies can also arise when comparing modeled annual temperature to climate reconstructions from high‐latitude tree‐ring proxy data that predominantly reflect growing season temperatures (K. J. Anchukaitis et al., 2012; D'Arrigo et al., 2013; Zhu et al., 2020). Persistent growth anomalies associated with biological memory and proxy noise are more prevalent in tree‐ring width (TRW) reconstructions than maximum latewood density (MXD) reconstructions, and studies comparing modeled climate response to proxy reconstructions have found that TRW can both underestimate the volcanic cooling effect and show a lagged response (D'Arrigo et al., 2013; Esper et al., 2015; Frank et al., 2007).…”

Section: Introductionmentioning

confidence: 99%

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Intra‐Annual Climate Anomalies in Northwestern North America Following the 1783–1784 CE Laki Eruption

et al. 2021

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The 1783–1784 CE Laki eruption in Iceland was one of the largest, in terms of the mass of SO2 emitted, high‐latitude eruptions in the last millennium, but the seasonal and regional climate response was heterogeneous in space and time. Although the eruption did not begin until early June, tree‐ring maximum latewood density (MXD) reconstructions from Alaska suggest that the entire 1783 summer was extraordinarily cold. We use high‐resolution quantitative wood anatomy, climate model simulations, and proxy systems modeling to resolve the intra‐annual climate effects of the Laki eruption on temperatures over northwestern North America. We measured wood anatomical characteristics of white spruce (Picea glauca) trees from two northern Alaska sites. Earlywood cell characteristics of the 1783 ring are normal, while latewood cell wall thickness is significantly and anomalously reduced compared to non‐eruption years. Combined with complementary evidence from climate model experiments and proxy systems modeling, these features indicate an abrupt and premature cessation of cell wall thickening due to a rapid temperature decrease toward the end of the growing season. Reconstructions using conventional annual resolution MXD likely over‐estimate total growing season cooling in this year, while ring width fails to capture this abrupt late‐summer volcanic signal. Our study has implications not only for the interpretation of the climatic impacts of the Laki eruption in North America, but more broadly demonstrates the importance of timing and internal variability when comparing proxy temperature reconstructions and climate model simulations. It further demonstrates the value of developing cellular‐scale tree‐ring proxy measurements for paleoclimatology.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Intra‐Annual Climate Anomalies in Northwestern North America Following the 1783–1784 CE Laki Eruption

et al. 2021

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“…compare the PHYDA to another new and publicly available data assimilation product, the Last Millennium Reanalysis product (LMR) (Tardif et al, 2019), which was recently used to investigate disagreements between model and proxy estimates of global temperature responses to volcanism (Zhu et al, 2020). These two state-of-the-art data assimilation products, which provide global representations of volcanic responses, are compared to simulations from the NCAR CESM-LME, which served as the prior for the PHYDA.…”

Section: 1029/2020pa004128mentioning

confidence: 99%

Global Temperature Responses to Large Tropical Volcanic Eruptions in Paleo Data Assimilation Products and Climate Model Simulations Over the Last Millennium

Tejedor

Steiger

Smerdon

et al. 2021

Paleoceanog and Paleoclimatol

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Volcanic eruptions are one of the main natural causes of radiatively forced climatic changes over the Common Era, producing fluctuations on interannual to multi-year timescales. The analysis and interpretation of such changes has resulted in a wide body of research, especially following the influential work of H.H. Lamb (Lamb & Stanley, 1970), and expanding into many efforts to characterize and model the climate response to volcanism (e.g., Robock, 2000;Sigl et al., 2015;Zanchettin et al., 2016). It is now well understood that explosive volcanic eruptions can alter climate by injecting large amounts of sulfur-containing gases into the stratosphere, such as SO 2 and H 2 S, leading to the formation of liquid sulfate aerosols (Toohey & Sigl, 2017). These aerosols consequently scatter incoming solar radiation and absorb infrared radiation, which in turn leads to a net decrease in radiation reaching the Earth's surface and associated global cooling (Robock, 2000). The introduction of satellite observations led to rapid advancements in our understanding of how stratospheric aerosols affect global temperature, particularly since the El Chichon eruption in 1983 (e.g., Robock, 1983;Robock & Matson, 1983). This event served as a natural experiment to test and develop monitoring instruments and improved representations of atmospheric chemistry in climate models, which in turn improved simulations of the climate effects due to volcanic aerosols in the stratosphere (Rampino & Self, 1984). With the exception of the eruption of Mt. Pinatubo in 1991, however, the volcanic events monitored during the 20th century are of a much smaller magnitude than many of those that have occurred over the Common Era. Further improvement in our understanding of the impacts and dynamics of large volcanic eruptions is therefore dependent on high-resolution proxy reconstructions and model simulations of the larger volcanic events that occurred before the widespread availability of instrumental records. The

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Pyleoclim: Paleoclimate Timeseries Analysis and Visualization with Python

Khider

Emile‐Geay

Zhu

et al. 2022

Preprint

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We present a Python package geared towards the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim.The code is open-source, object-oriented, and built upon the standard scientific Python stack, allowing to take advantage of a large collection of existing and emerging techniques. We describe the code's philosophy, structure and base functionalities, and apply it to three paleoclimate problems: (1) orbital-scale climate variability in a deep-sea core, illustrating spectral, wavelet and coherency analysis in the presence of age uncertainties; (2) correlating a high-resolution speleothem to a climate field, illustrating correlation analysis in the presence of various statistical pitfalls (including age uncertainties); (3) model-data confrontations in the frequency domain, illustrating the characterization of scaling behavior. We show how the package may be used for transparent and reproducible analysis of paleoclimate and paleoceanographic datasets, supporting FAIR software and an open science ethos. The package is supported by an extensive documentation and a growing library of tutorials shared publicly as videos and cloud-executable Jupyter notebooks, to encourage adoption by new users.

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Resolving the Differences in the Simulated and Reconstructed Temperature Response to Volcanism

Cited by 39 publications

References 92 publications

Intra‐Annual Climate Anomalies in Northwestern North America Following the 1783–1784 CE Laki Eruption

Intra‐Annual Climate Anomalies in Northwestern North America Following the 1783–1784 CE Laki Eruption

Global Temperature Responses to Large Tropical Volcanic Eruptions in Paleo Data Assimilation Products and Climate Model Simulations Over the Last Millennium

Pyleoclim: Paleoclimate Timeseries Analysis and Visualization with Python

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