Climate Field Reconstruction Methods Research Articles

A pseudoproxy assessment of why climate field reconstruction methods perform the way they do in time and space

Abstract. Spatiotemporal paleoclimate reconstructions that seek to estimate climate conditions over the last several millennia are derived from multiple climate proxy records (e.g., tree rings, ice cores, corals, and cave formations) that are heterogeneously distributed across land and marine environments. Assessing the skill of the methods used for these reconstructions is critical as a means of understanding the spatiotemporal uncertainties in the derived reconstruction products. Traditional statistical measures of skill have been applied in past applications, but they often lack formal null hypotheses that incorporate the spatiotemporal characteristics of the fields and allow for formal significance testing. More recent attempts have developed assessment metrics to evaluate the difference of the characteristics between two spatiotemporal fields. We apply these assessment metrics to results from synthetic reconstruction experiments based on multiple climate model simulations to assess the skill of four reconstruction methods. We further interpret the comparisons using analysis of empirical orthogonal functions (EOFs) that represent the noise-filtered climate field. We demonstrate that the underlying features of a targeted temperature field that can affect the performance of CFRs include the following: (i) the characteristics of the eigenvalue spectrum, namely the amount of variance captured in the leading EOFs; (ii) the temporal stability of the leading EOFs; (iii) the representation of the climate over the sampling network with respect to the global climate; and (iv) the strength of spatial covariance, i.e., the dominance of teleconnections, in the targeted temperature field. The features of climate models and reconstruction methods identified in this paper demonstrate more detailed assessments of reconstruction methods and point to important areas of testing and improving real-world reconstruction methods.

Calibration Uncertainties of Tropical Pacific Climate Reconstructions over the Last Millennium

AbstractSeveral climate field reconstruction methods assume stationarity between the leading patterns of variability identified during the instrumental calibration period and the reconstruction period. We examine how and to what extent this restrictive assumption may generate uncertainties in reconstructing past tropical Pacific climate variability. Based on the Last Millennium (850–2005 CE) ensemble simulations conducted with the Community Earth System Model and by developing a series of pseudoproxy reconstructions for different calibration periods, we find that the overall reconstruction skill for global and more regional-scale climate indices depends significantly on the magnitude of externally forced global mean temperature variability during the chosen calibration period. This effect strongly reduces the fidelity of reconstructions of decadal to centennial-scale tropical climate variability, associated with the interdecadal Pacific oscillation (IPO) and centennial-scale temperature shifts between the Medieval Climate Anomaly (MCA) and the Little Ice Age (LIA). In contrast, our pseudoproxy-based analysis demonstrates that reconstructions of interannual El Niño–Southern Oscillation (ENSO) variability are more robust and less affected by changes in calibration period.

Pseudo-proxy evaluation of climate field reconstruction methods of North Atlantic climate based on an annually resolved marine proxy network

Abstract. Two statistical methods are tested to reconstruct the interannual variations in past sea surface temperatures (SSTs) of the North Atlantic (NA) Ocean over the past millennium based on annually resolved and absolutely dated marine proxy records of the bivalve mollusk Arctica islandica. The methods are tested in a pseudo-proxy experiment (PPE) setup using state-of-the-art climate models (CMIP5 Earth system models) and reanalysis data from the COBE2 SST data set. The methods were applied in the virtual reality provided by global climate simulations and reanalysis data to reconstruct the past NA SSTs using pseudo-proxy records that mimic the statistical characteristics and network of Arctica islandica. The multivariate linear regression methods evaluated here are principal component regression and canonical correlation analysis. Differences in the skill of the climate field reconstruction (CFR) are assessed according to different calibration periods and different proxy locations within the NA basin. The choice of the climate model used as a surrogate reality in the PPE has a more profound effect on the CFR skill than the calibration period and the statistical reconstruction method. The differences between the two methods are clearer for the MPI-ESM model due to its higher spatial resolution in the NA basin. The pseudo-proxy results of the CCSM4 model are closer to the pseudo-proxy results based on the reanalysis data set COBE2. Conducting PPEs using noise-contaminated pseudo-proxies instead of noise-free pseudo-proxies is important for the evaluation of the methods, as more spatial differences in the reconstruction skill are revealed. Both methods are appropriate for the reconstruction of the temporal evolution of the NA SSTs, even though they lead to a great loss of variance away from the proxy sites. Under reasonable assumptions about the characteristics of the non-climate noise in the proxy records, our results show that the marine network of Arctica islandica can be used to skillfully reconstruct the spatial patterns of SSTs at the eastern NA basin.

Evaluation of CMIP5 models over the northern North Atlantic in the context of forthcoming paleoclimatic reconstructions

We evaluated 11 coupled climate model simulations regarding the spatial structures of sea-surface temperature (SST) variability in the North Atlantic, during the second half of the twentieth century. The subset of models includes CCSM4, CSIRO, CanESM and MPI-ESM, participating in the fifth phase of the Climate Model Intercomparison Project. The evaluation was performed to determine the potential of these models to be used at a later stage as test beds for the evaluation of climate field reconstruction methods that will use the extremely long-lived bivalve mollusk Arctica islandica, an outstanding paleoclimate archive for the boreal and temperate North Atlantic (Schöne, Glob Planet Change 111:199–225, 2013). Several validation metrics such as the mean bias, variance, spatial and temporal co-variability and trends of the North Atlantic summer SSTs showed that some of the models can be used to test paleoclimatic reconstructions. However, most models showed shortcomings in simulating the Atlantic Multidecadal Oscillation. Concerning the co-variability of summer SSTs between proxy sites and the whole North Atlantic SST field, we found that these proxy locations contain a SST signal that might represent a (basin-wide) signal for the north-eastern North Atlantic basin.

Model-dependent spatial skill in pseudoproxy experiments testing climate field reconstruction methods for the Common Era

The spatial skill of four climate field reconstruction (CFR) methods is investigated using pseudoproxy experiments (PPEs) based on five last millennium and historical simulations from the Coupled and Paleo Model Intercomparison Projects Phases 5 and 3 (CMIP5/PMIP3) data archives. These simulations are used for the first time in a PPE context, the frameworks of which are constructed to test a recently assembled multiproxy network and multiple CFR techniques. The experiments confirm earlier findings demonstrating consistent methodological performance across the employed methods and spatially dependent reconstruction errors in all of the derived CFRs. Spectral biases in the reconstructed fields demonstrate that CFR methods can alone alter the ratio of spectral power at all locations in the field, independent of whether there are any spectral biases inherent in the underlying pseudoproxy series. The patterns of spectral biases are model dependent and indicate the potential for regions in the derived CFRs to be biased by changes in either low or high-frequency spectral power. CFR methods are also shown to alter the pattern of mean differences in the tropical Pacific during the Medieval Climate Anomaly and the Little Ice Age, with some model experiments indicating that CFR methodologies enhance the statistical likelihood of achieving larger mean differences between independent 300-year periods in the region. All of the characteristics of CFR performance are model dependent, indicating that CFR methods must be evaluated across multiple models and that conclusions from PPEs should be carefully connected to the spatial statistics of real-world climatic fields.

Performance of climate field reconstruction methods over multiple seasons and climate variables

Studies of climate variability require long time series of data but are limited by the absence of preindustrial instrumental records. For such studies, proxy‐based climate reconstructions, such as those produced from tree‐ring widths, provide the opportunity to extend climatic records into preindustrial periods. Climate field reconstruction (CFR) methods are capable of producing spatially‐resolved reconstructions of climate fields. We assessed the performance of three commonly used CFR methods (canonical correlation analysis, point‐by‐point regression, and regularized expectation maximization) over spatially‐resolved fields using multiple seasons and climate variables. Warm‐ and cool‐season geopotential height, precipitable water, and surface temperature were tested for each method using tree‐ring chronologies. Spatial patterns of reconstructive skill were found to be generally consistent across each of the methods, but the robustness of the validation metrics varied by CFR method, season, and climate variable. The most robust validation metrics were achieved with geopotential height, the October through March temporal composite, and the Regularized Expectation Maximization method. While our study is limited to assessment of skill over multidecadal (rather than multi‐centennial) time scales, our findings suggest that the climate variable of interest, seasonality, and spatial domain of the target field should be considered when assessing potential CFR methods for real‐world applications.

Spatial performance of four climate field reconstruction methods targeting the Common Era

The spatial skill of four climate field reconstruction (CFR) methods is investigated using pseudoproxy experiments (PPEs) based on two millennial-length general circulation model simulations. Results indicate that presently available global and hemispheric CFRs for the Common Era likely suffer from spatial uncertainties not previously characterized. No individual method produced CFRs with universally superior spatial error statistics, making it difficult to advocate for one method over another. Northern Hemisphere means are shown to be insufficient for evaluating spatial skill, indicating that the spatial performance of future CFRs should be rigorously tested for dependence on proxy type and location, target data and employed methodologies. Observed model-dependent methodological performance also indicates that CFR methods must be tested across multiple models and conclusions from PPEs should be carefully evaluated against the spatial statistics of real-world climatic fields. Citation: Smerdon, J. E., A. Kaplan, E. Zorita, J. F. Gonzalez-Rouco, and M. N. Evans (2011), Spatial performance of four climate field reconstruction methods targeting the Common Era, Geophys. Res. Lett., 38, L11705, doi: 10.1029/2011GL047372.

Paleoclimate Reconstructions of Tropical Sea Surface Temperatures from Precipitation Proxies: Methods, Uncertainties, and Nonstationarity

AbstractProxy-based paleoclimate reconstructions of tropical sea surface temperature (SST) fields may lead to better constraints of tropical climate variability in climate model projections. In this study, the authors quantify uncertainties associated with two popular SST anomaly reconstruction methods that have been applied over the last millennium. The first reconstruction method exploits the high correlation between the leading modes of variability of global precipitation and SSTs; the second method uses a multiregression model that exploits the multiple modes of covariability between precipitation and SSTs. Regardless of the proxy network density, the first method has skill only in the tropical eastern Pacific and misses some ENSO events. By contrast, the multiregression approach demonstrates high skill throughout the tropical Indo-Pacific region and predicts all ENSO events correctly. The advantage of the multiregression method lies in the second mode of covariability between SSTs and precipitation, which explains nearly 15% of the covariability between the two variables. However, when the period 1950–2000 is considered, the authors find that the nonstationarity in the second mode of covariability between SST and precipitation leads to a significant reduction of skill in the Indian Ocean and the warm pool region. This change suggests that the underlying stationarity assumption common in most climate field reconstruction methods needs to be treated more carefully, particularly in the tropics.

Comment on “Robustness of proxy‐based climate field reconstruction methods” by Michael E. Mann et al.

] Mann et al. [2007a] (hereafter M07a) test the climatefield reconstruction (CFR) method known as regularizedexpectation maximization (RegEM) using pseudoproxiesderived from millennial simulations of past climate. Thesesimulations were derived from two General CirculationModels (GCMs) driven with natural and anthropogenicforcings: the National Center for Atmospheric ResearchClimate System Model (CSM) [Boville et al., 2001] andthe Hamburg Atmosphere-Ocean Coupled CirculationModel (ECHO-g) [Legutke and Voss, 1999]. There has beensome discussion about the amplitude of millennial changesin simulations from these two GCMs [Goosse et al., 2005;Mann et al., 2005; Osborn et al., 2006; Gonza´lez-Rouco etal., 2006], particularly with regard to how it may impact theassessment of CFR methods in pseudoproxy experiments[Mannetal.,2005;Mann,2007;Zoritaetal.,2007;Mannetal., 2007a, 2007b].[

Reply to comment by Jason E. Smerdon et al. on “Robustness of proxy‐based climate field reconstruction methods”

[1] Smerdon et al. [2008] correctly conclude that the initial regridding method used by Mann et al. [2007] (hereafter M07) to map ECHO-g output to the resolution of surface observation data resulted in enhanced variability of the Northern Hemisphere (NH) mean series compared to the original model output (Figure 1a of Smerdon et al. [2008]). They also correctly conclude that the gridding method has no effect whatsoever on the conclusions of M07 because those conclusions were primarily based on results using the CSM model, and because the ECHO-g Figure 1. Results of experiments ‘‘y’’ (red line) and ‘‘z’’ (blue line) (a) from M07 and (b) using the regridding method described here. The use of the alternative regridding method does not change the results and conclusion of M07. JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 113, D18107, doi:10.1029/2008JD009964, 2008 Click Here for Full Article

Robustness of proxy‐based climate field reconstruction methods

We present results from continued investigations into the fidelity of covariance‐based climate field reconstruction (CFR) approaches used in proxy‐based climate reconstruction. Our experiments employ synthetic “pseudoproxy” data derived from simulations of forced climate changes over the past millennium. Using networks of these pseudoproxy data, we investigate the sensitivity of CFR performance to signal‐to‐noise ratios, the noise spectrum, the spatial sampling of pseudoproxy locations, the statistical representation of predictors used, and the diagnostic used to quantify reconstruction skill. Our results reinforce previous conclusions that CFR methods, correctly implemented and applied to suitable networks of proxy data, should yield reliable reconstructions of past climate histories within estimated uncertainties. Our results also demonstrate the deleterious impact of a linear detrending procedure performed recently in certain CFR studies and illustrate flaws in some previously proposed metrics of reconstruction skill.

Climate reconstruction using ‘Pseudoproxies’

We test the performance of proxy‐based climate field reconstruction methods using sets of synthetic proxy climate indicators. ‘Pseudoproxies’ are constructed through the degradation of instrumental surface temperature data by additive noise with variable statistical properties. Experiments are performed using pseudoproxy networks of varying spatial and seasonal representation and with varying noise attributes. Implications for sampling strategies for improved paleoclimate reconstructions are discussed.