scholarly journals Global temperature responses to large tropical volcanic eruptions in paleo data assimilation products and climate model simulations over the Last Millennium

2021 ◽  
Author(s):  
E. Tejedor ◽  
N. Steiger ◽  
J.E. Smerdon ◽  
R. Serrano‐Notivoli ◽  
M. Vuille
Keyword(s):  
Data Assimilation ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Global Temperature ◽  
Last Millennium ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Temperature Responses

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.

Multiscale combination of climate model simulations and proxy records over the last millennium

2017 ◽  
Vol 132 (3-4) ◽  
pp. 763-777
Author(s):  
Xin Chen ◽  
Pei Xing ◽  
Yong Luo ◽  
Suping Nie ◽  
Zongci Zhao ◽  
...  
Keyword(s):  
Climate Model ◽  
Last Millennium ◽  
Model Simulations ◽  
Proxy Records ◽  
Climate Model Simulations

scholarly journals Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium

2012 ◽  
Vol 8 (1) ◽  
pp. 263-320 ◽  
Author(s):  
A. Hind ◽  
A. Moberg ◽  
R. Sundberg
Keyword(s):  
Climate Model ◽  
Distance Measure ◽  
Last Millennium ◽  
Proxy Data ◽  
Simulation Data ◽  
Model Simulations ◽  
Climate Proxy ◽  
Statistical Framework ◽  
Climate Model Simulations ◽  
Instrumental Series

Abstract. A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records is developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance changes and greenhouse gas concentrations. Two statistical tests are formulated. Firstly, a preliminary test to establish whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The new methods are applied in a pseudo-proxy experiment. Here, a set of previously published millennial forced model simulations, including both "low" and "high" solar radiative forcing histories together with other common forcings, were used to define "true" target temperatures as well as pseudo-proxy and pseudo-instrumental series. The pseudo-proxies were created to reflect current proxy locations and noise levels, where it was found that the low and high solar full-forcing simulations could be distinguished when the latter were used as targets. When the former were used as targets, a greater number of proxy locations were needed to make this distinction. It was also found that to improve detectability of the low solar simulations, increasing the signal-to-noise ratio was more efficient than increasing the spatial coverage of the proxy network. In the next phase of the work, we will apply these methods to real proxy and instrumental data, with the aim to distinguish which of the two solar forcing histories is most compatible with the observed/reconstructed climate.

scholarly journals Greenland temperature and precipitation over the last 20 000 years using data assimilation

2020 ◽  
Vol 16 (4) ◽  
pp. 1325-1346
Author(s):  
Jessica A. Badgeley ◽  
Eric J. Steig ◽  
Gregory J. Hakim ◽  
Tyler J. Fudge
Keyword(s):  
Data Assimilation ◽  
Spatial Patterns ◽  
Climate Model ◽  
Ice Core ◽  
Ice Sheet ◽  
Proxy Data ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Climate Model Simulations ◽  
Paleoclimate Data

Abstract. Reconstructions of past temperature and precipitation are fundamental to modeling the Greenland Ice Sheet and assessing its sensitivity to climate. Paleoclimate information is sourced from proxy records and climate-model simulations; however, the former are spatially incomplete while the latter are sensitive to model dynamics and boundary conditions. Efforts to combine these sources of information to reconstruct spatial patterns of Greenland climate over glacial–interglacial cycles have been limited by assumptions of fixed spatial patterns and a restricted use of proxy data. We avoid these limitations by using paleoclimate data assimilation to create independent reconstructions of mean-annual temperature and precipitation for the last 20 000 years. Our method uses oxygen isotope ratios of ice and accumulation rates from long ice-core records and extends this information to all locations across Greenland using spatial relationships derived from a transient climate-model simulation. Standard evaluation metrics for this method show that our results capture climate at locations without ice-core records. Our results differ from previous work in the reconstructed spatial pattern of temperature change during abrupt climate transitions; this indicates a need for additional proxy data and additional transient climate-model simulations. We investigate the relationship between precipitation and temperature, finding that it is frequency dependent and spatially variable, suggesting that thermodynamic scaling methods commonly used in ice-sheet modeling are overly simplistic. Our results demonstrate that paleoclimate data assimilation is a useful tool for reconstructing the spatial and temporal patterns of past climate on timescales relevant to ice sheets.

scholarly journals Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 1: Theory

2012 ◽  
Vol 8 (4) ◽  
pp. 1339-1353 ◽  
Author(s):  
R. Sundberg ◽  
A. Moberg ◽  
A. Hind
Keyword(s):  
Climate Model ◽  
Distance Measure ◽  
Last Millennium ◽  
Proxy Data ◽  
Simulation Data ◽  
Model Simulations ◽  
Climate Proxy ◽  
Statistical Framework ◽  
Climate Model Simulations ◽  
Instrumental Records

Abstract. A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.

Variability of the Azores High and regional hydroclimate over the past millennium

2020 ◽  
Author(s):  
Caroline Ummenhofer ◽  
Nathaniel Cresswell-Clay ◽  
Diana Thatcher ◽  
Alan Wanamaker ◽  
Rhawn Denniston
Keyword(s):  
Climate Model ◽  
Hadley Circulation ◽  
Meridional Overturning Circulation ◽  
Ice Age ◽  
Last Millennium ◽  
Atlantic Sector ◽  
Model Simulations ◽  
The Past ◽  
Climate Model Simulations ◽  
Azores High

<p>The subtropical dry zones, including the broader Mediterranean region, are likely to experience considerable changes in hydroclimate in a warming climate. An expansion of the atmosphere’s meridional overturning circulation, the Hadley circulation, over recent decades has been reported, with implications for regional hydroclimate. Yet, there exists considerable disagreement in magnitude and even sign of these trends among different metrics that measure various aspects of the Hadley circulation, as well as discrepancies in trends between different analysis periods and reanalysis products during the 20<sup>th</sup> century. In light of these uncertainties, it is therefore of interest to explore variability and trends in subtropical hydroclimate and its dominant driver, the Hadley Circulation. We focus on the North Atlantic sector and explore variability in the Azores High, the manifestation of the Hadley Circulation’s downward branch, and hydroclimate across the Iberian Peninsula using a combination of observational/reanalysis products, state-of-the-art climate model simulations, and hydroclimatically-sensitive stalagmite records over the past 1200 yr. The Last Millennium Ensemble (LME) with the Community Earth System Model provides thirteen transient simulations covering the period 850 to 2005 A.D. with prescribed external forcing (e.g. greenhouse gas, solar, volcanic, land use, orbital, and aerosol) and smaller subsets with individual forcing only. The LME is shown to accurately simulate the variability and trends in the Azores High when compared to observational records from the 20<sup>th</sup> century. We evaluate variability in the Azores High (e.g., size, intensity, position) in relation to other key metrics that measure different aspects of the Hadley circulation throughout the course of the last millennium, as well as during key periods, such as the Little Ice Age or Medieval Climate Anomaly. The smaller subsets of LME simulations with individual forcing factors (e.g., solar, volcanic) allow for an attribution of past changes in regional hydroclimate to external drivers. Results from the climate model simulations are compared with hydroclimate reconstructed from stalagmites from Portuguese caves.</p>

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