scholarly journals Evaluating climate field reconstruction techniques using improved emulations of real-world conditions

2014 ◽  
Vol 10 (1) ◽  
pp. 1-19 ◽  
Author(s):  
J. Wang ◽  
J. Emile-Geay ◽  
D. Guillot ◽  
J. E. Smerdon ◽  
B. Rajaratnam

Abstract. Pseudoproxy experiments (PPEs) have become an important framework for evaluating paleoclimate reconstruction methods. Most existing PPE studies assume constant proxy availability through time and uniform proxy quality across the pseudoproxy network. Real multiproxy networks are, however, marked by pronounced disparities in proxy quality, and a steep decline in proxy availability back in time, either of which may have large effects on reconstruction skill. A suite of PPEs constructed from a millennium-length general circulation model (GCM) simulation is thus designed to mimic these various real-world characteristics. The new pseudoproxy network is used to evaluate four climate field reconstruction (CFR) techniques: truncated total least squares embedded within the regularized EM (expectation-maximization) algorithm (RegEM-TTLS), the Mann et al. (2009) implementation of RegEM-TTLS (M09), canonical correlation analysis (CCA), and Gaussian graphical models embedded within RegEM (GraphEM). Each method's risk properties are also assessed via a 100-member noise ensemble. Contrary to expectation, it is found that reconstruction skill does not vary monotonically with proxy availability, but also is a function of the type and amplitude of climate variability (forced events vs. internal variability). The use of realistic spatiotemporal pseudoproxy characteristics also exposes large inter-method differences. Despite the comparable fidelity in reconstructing the global mean temperature, spatial skill varies considerably between CFR techniques. Both GraphEM and CCA efficiently exploit teleconnections, and produce consistent reconstructions across the ensemble. RegEM-TTLS and M09 appear advantageous for reconstructions on highly noisy data, but are subject to larger stochastic variations across different realizations of pseudoproxy noise. Results collectively highlight the importance of designing realistic pseudoproxy networks and implementing multiple noise realizations of PPEs. The results also underscore the difficulty in finding the proper bias-variance tradeoff for jointly optimizing the spatial skill of CFRs and the fidelity of the global mean reconstructions.

2013 ◽  
Vol 9 (3) ◽  
pp. 3015-3060 ◽  
Author(s):  
J. Wang ◽  
J. Emile-Geay ◽  
D. Guillot ◽  
J. E. Smerdon ◽  
B. Rajaratnam

Abstract. Pseudoproxy experiments (PPEs) have become an essential framework for evaluating paleoclimate reconstruction methods. Most existing PPE studies assume constant proxy availability through time and uniform proxy quality across the pseudoproxy network. Real multi-proxy networks are, however, marked by pronounced disparities in proxy quality, and a steep decline in proxy availability back in time, either of which may have large effects on reconstruction skill. Additionally, an investigation of a real-world global multi-proxy network suggests that proxies are not exclusively indicators of local climate; rather, many are indicative of large-scale teleconnections. A suite of PPEs constructed from a millennium-length general circulation model simulation is thus designed to mimic these various real-world characteristics. The new pseudoproxy network is used to evaluate four climate field reconstruction (CFR) techniques: truncated total least square embedded within the regularized EM algorithm (RegEM-TTLS), the Mann et al. (2009) implementation of RegEM-TTLS (M09), canonical correlation analysis (CCA), and Gaussian graphical models embedded within RegEM (GraphEM). Each method's risk properties are also assessed via a 100-member noise ensemble. Contrary to expectation, it is found that reconstruction skill does not vary monotonically with proxy availability, but rather is a function of the type of climate variability (forced events vs. internal variability). The use of realistic spatiotemporal pseudoproxy characteristics also exposes large inter-method differences. Despite the comparable fidelity in reconstructing the global mean temperature, spatial skill varies considerably between CFR techniques. Both GraphEM and CCA efficiently exploit teleconnections, and produce consistent reconstructions across the ensemble. RegEM-TTLS and M09 appear advantageous for reconstructions on highly noisy data, but are subject to larger stochastic variations across different realizations of pseudoproxy noise. Results collectively highlight the importance of designing realistic pseudoproxy networks and implementing multiple noise realizations of PPEs. The results also underscore the difficulty in finding the proper bias-variance tradeoff for jointly optimizing the spatial skill of CFRs and the fidelity of the global mean reconstructions.


2007 ◽  
Vol 20 (4) ◽  
pp. 765-771 ◽  
Author(s):  
Markus Jochum ◽  
Clara Deser ◽  
Adam Phillips

Abstract Atmospheric general circulation model experiments are conducted to quantify the contribution of internal oceanic variability in the form of tropical instability waves (TIWs) to interannual wind and rainfall variability in the tropical Pacific. It is found that in the tropical Pacific, along the equator, and near 25°N and 25°S, TIWs force a significant increase in wind and rainfall variability from interseasonal to interannual time scales. Because of the stochastic nature of TIWs, this means that climate models that do not take them into account will underestimate the strength and number of extreme events and may overestimate forecast capability.


2016 ◽  
Vol 12 (5) ◽  
pp. 1181-1198 ◽  
Author(s):  
Daniel J. Lunt ◽  
Alex Farnsworth ◽  
Claire Loptson ◽  
Gavin L. Foster ◽  
Paul Markwick ◽  
...  

Abstract. During the period from approximately 150 to 35 million years ago, the Cretaceous–Paleocene–Eocene (CPE), the Earth was in a “greenhouse” state with little or no ice at either pole. It was also a period of considerable global change, from the warmest periods of the mid-Cretaceous, to the threshold of icehouse conditions at the end of the Eocene. However, the relative contribution of palaeogeographic change, solar change, and carbon cycle change to these climatic variations is unknown. Here, making use of recent advances in computing power, and a set of unique palaeogeographic maps, we carry out an ensemble of 19 General Circulation Model simulations covering this period, one simulation per stratigraphic stage. By maintaining atmospheric CO2 concentration constant across the simulations, we are able to identify the contribution from palaeogeographic and solar forcing to global change across the CPE, and explore the underlying mechanisms. We find that global mean surface temperature is remarkably constant across the simulations, resulting from a cancellation of opposing trends from solar and palaeogeographic change. However, there are significant modelled variations on a regional scale. The stratigraphic stage–stage transitions which exhibit greatest climatic change are associated with transitions in the mode of ocean circulation, themselves often associated with changes in ocean gateways, and amplified by feedbacks related to emissivity and planetary albedo. We also find some control on global mean temperature from continental area and global mean orography. Our results have important implications for the interpretation of single-site palaeo proxy records. In particular, our results allow the non-CO2 (i.e. palaeogeographic and solar constant) components of proxy records to be removed, leaving a more global component associated with carbon cycle change. This “adjustment factor” is used to adjust sea surface temperatures, as the deep ocean is not fully equilibrated in the model. The adjustment factor is illustrated for seven key sites in the CPE, and applied to proxy data from Falkland Plateau, and we provide data so that similar adjustments can be made to any site and for any time period within the CPE. Ultimately, this will enable isolation of the CO2-forced climate signal to be extracted from multiple proxy records from around the globe, allowing an evaluation of the regional signals and extent of polar amplification in response to CO2 changes during the CPE. Finally, regions where the adjustment factor is constant throughout the CPE could indicate places where future proxies could be targeted in order to reconstruct the purest CO2-induced temperature change, where the complicating contributions of other processes are minimised. Therefore, combined with other considerations, this work could provide useful information for supporting targets for drilling localities and outcrop studies.


2007 ◽  
Vol 112 (D12) ◽  
Author(s):  
Michael E. Mann ◽  
Scott Rutherford ◽  
Eugene Wahl ◽  
Caspar Ammann

2011 ◽  
Vol 7 (1) ◽  
pp. 249-263 ◽  
Author(s):  
A. Voigt ◽  
D. S. Abbot ◽  
R. T. Pierrehumbert ◽  
J. Marotzke

Abstract. We study the initiation of a Marinoan Snowball Earth (~635 million years before present) with the state-of-the-art atmosphere-ocean general circulation model ECHAM5/MPI-OM. This is the most sophisticated model ever applied to Snowball initiation. A comparison with a pre-industrial control climate shows that the change of surface boundary conditions from present-day to Marinoan, including a shift of continents to low latitudes, induces a global-mean cooling of 4.6 K. Two thirds of this cooling can be attributed to increased planetary albedo, the remaining one third to a weaker greenhouse effect. The Marinoan Snowball Earth bifurcation point for pre-industrial atmospheric carbon dioxide is between 95.5 and 96% of the present-day total solar irradiance (TSI), whereas a previous study with the same model found that it was between 91 and 94% for present-day surface boundary conditions. A Snowball Earth for TSI set to its Marinoan value (94% of the present-day TSI) is prevented by doubling carbon dioxide with respect to its pre-industrial level. A zero-dimensional energy balance model is used to predict the Snowball Earth bifurcation point from only the equilibrium global-mean ocean potential temperature for present-day TSI. We do not find stable states with sea-ice cover above 55%, and land conditions are such that glaciers could not grow with sea-ice cover of 55%. Therefore, none of our simulations qualifies as a "slushball" solution. While uncertainties in important processes and parameters such as clouds and sea-ice albedo suggest that the Snowball Earth bifurcation point differs between climate models, our results contradict previous findings that Snowball Earth initiation would require much stronger forcings.


2009 ◽  
Vol 22 (20) ◽  
pp. 5421-5432 ◽  
Author(s):  
Duncan Ackerley ◽  
Eleanor J. Highwood ◽  
David J. Frame ◽  
Ben B. B. Booth

Abstract A large ensemble of general circulation model (GCM) integrations coupled to a fully interactive sulfur cycle scheme were run on the climateprediction.net platform to investigate the uncertainty in the climate response to sulfate aerosol and carbon dioxide (CO2) forcing. The sulfate burden within the model (and the atmosphere) depends on the balance between formation processes and deposition (wet and dry). The wet removal processes for sulfate aerosol are much faster than dry removal and so any changes in atmospheric circulation, cloud cover, and precipitation will feed back on the sulfate burden. When CO2 is doubled in the Hadley Centre Slab Ocean Model (HadSM3), global mean precipitation increased by 5%; however, the global mean sulfate burden increased by 10%. Despite the global mean increase in precipitation, there were large areas of the model showing decreases in precipitation (and cloud cover) in the Northern Hemisphere during June–August, which reduced wet deposition and allowed the sulfate burden to increase. Further experiments were also undertaken with and without doubling CO2 while including a future anthropogenic sulfur emissions scenario. Doubling CO2 further enhanced the increases in sulfate burden associated with increased anthropogenic sulfur emissions as observed in the doubled CO2-only experiment. The implications are that the climate response to doubling CO2 can influence the amount of sulfate within the atmosphere and, despite increases in global mean precipitation, may act to increase it.


2010 ◽  
Vol 6 (5) ◽  
pp. 1853-1894 ◽  
Author(s):  
A. Voigt ◽  
D. S. Abbot ◽  
R. T. Pierrehumbert ◽  
J. Marotzke

Abstract. We study the initiation of a Marinoan Snowball Earth (635 million years before present) with the most sophisticated atmosphere-ocean general circulation model ever used for this purpose, ECHAM5/MPI-OM. A comparison with a pre-industrial control climate shows that the change of surface boundary conditions from present-day to Marinoan, including a shift of continents to low latitudes, induces a global mean cooling of 4.6 K. Two thirds of this cooling can be attributed to increased planetary albedo, the remaining one third to a weaker greenhouse effect. The Marinoan Snowball Earth bifurcation point for pre-industrial atmospheric carbon dioxide is between 95.5 and 96% of the present-day total solar irradiance (TSI), whereas a previous study with the same model found that it was between 91 and 94% for present-day surface boundary conditions. A Snowball Earth for TSI set to its Marinoan value (94% of the present-day TSI) is prevented by quadrupling carbon dioxide with respect to its pre-industrial level. A zero-dimensional energy balance model is used to predict the Snowball Earth bifurcation point from only the equilibrium global mean ocean potential temperature for present-day TSI. We do not find stable states with sea-ice cover above 55%, and land conditions are such that glaciers could not grow with sea-ice cover of 55%. Therefore, none of our simulations qualifies as a "slushball" solution. In summary, our results contradict previous claims that Snowball Earth initiation would require "extreme" forcings.


2018 ◽  
Author(s):  
Tine Nilsen ◽  
Johannes P. Werner ◽  
Dmitry V. Divine

Abstract. The Bayesian hierarchical model BARCAST (Bayesian Algorithm for Reconstructing Climate Anomalies in Space and Time) climate field reconstruction (CFR) technique, and idealized input data are used in the pseudoproxy experiments of this study. Ensembles of targets are generated from fields of long-range memory stochastic processes using a novel approach. The range of experiment setups include input data with different levels of persistence and levels of proxy noise, but without any form of external forcing. The input data are thereby a simplistic alternative to standard target data extracted from general circulation model (GCM) simulations. Ensemble-based temperature reconstructions are generated, representing the European landmass for a millennial time period. Hypothesis testing in the spectral domain is then used to investigate if the field and spatial mean reconstructions are consistent with either the fractional Gaussian noise (fGn) null hypothesis used for generating the target data, or the autoregressive model of order one (AR(1)) null hypothesis which is the assumed temperature model for this reconstruction technique. The study reveals that the resulting field and spatial mean reconstructions are consistent with the fGn hypothesis for most of the parameter configurations. There are local differences in reconstructed scaling characteristics between individual grid cells, and a generally better agreement with the fGn model for the spatial mean reconstruction than at individual locations. The discrepancy from an fGn is most evident for the high-frequency part of the reconstructed signal, while the long-range memory is better preserved at frequencies corresponding to decadal time scales and longer. Selected experiment setups were found to give reconstructions consistent with the AR(1) model. Reconstruction skill is measured on an ensemble member basis using selected validation metrics. Despite the mismatch between the BARCAST temporal covariance model and the model of the target, the ensemble mean was in general found to be consistent with the target data, while the estimated confidence intervals are more affected by this discrepancy. Our results show that the use of target data with a different spatiotemporal covariance structure than the BARCAST model assumption can lead to a potentially biased CFR reconstruction and associated confidence intervals, because of the wrong model assumptions.


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