Supplementary material to "Last Millennium Reanalysis with an expanded proxy database and seasonal proxy modeling" (original) (raw)
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Updating historical tree-ring records for climate reconstruction
Quaternary Science Reviews, 2010
Over the past three decades, numerous Late Holocene-long tree-ring (TR) chronologies have been developed for different parts of Europe that allow archaeological, historical and cultural wood remains to be dated with annual precision. Ironically, palaeoclimatic evidence inherent in such composites is limited as modern updates essential for calibration/verification with instrumental measurements are often inappropriate, incomplete or even missing. Here we proposes a novel approach to updating historical TR records while preventing statistical over-fit with the target data and advocate 'horizontal' splitting between historical (early) and recent (modern) TR samples prior to their standardization (detrending). This split-technique will help to overcoming unprecedented effects of increased atmospheric greenhouse-gas, biospheric fertilization, forest management, sample replication, age-structure and chronology development associated with modern proxy updates.
2005: Testing the fidelity of methods used in proxy-based reconstructions of past climate
2014
Two widely used statistical approaches to reconstructing past climate histories from climate 'proxy ' data such as tree-rings, corals, and ice cores, are investigated using synthetic 'pseudoproxy ' data derived from a simulation of forced climate changes over the past 1200 years. Our experiments suggest that both statistical approaches should yield reliable reconstructions of the true climate history within estimated uncertainties, given estimates of the signal and noise attributes of actual proxy data networks. 1.
Last Millennium Reanalysis with an expanded proxy database and seasonal proxy modeling
Climate of the Past Discussions
The Last Millennium Reanalysis utilizes an ensemble methodology to assimilate paleoclimate data for the production of annually resolved climate field reconstructions of the Common Era. Two key elements are the focus of this work: the set of assimilated proxy records, and the forward models that map climate variables to proxy measurements. Results based on an extensive proxy database and seasonal regression-based forward models are compared to the prototype reanalysis of Hakim et al. (2016), which was based on a smaller set of proxy records and simpler proxy models formulated as univariate linear regressions against annual temperature. Validation against various instrumental-era gridded analyses shows that the new reconstructions of surface air temperature, 500 hPa geopotential height and the Palmer Drought Severity Index are significantly improved, with skill scores increasing from 10% to more than 200%, depending on the variable and verification measure. Additional experiments designed to isolate the sources of improvement reveal the importance of additional proxy records, including coral records for improving tropical reconstructions; tree-ring-width chronologies, including moisture-sensitive trees, for thermodynamic and hydroclimate variables in mid-latitudes; and tree-ring density records for temperature reconstructions, particularly in high northern latitudes. Proxy forward models that account for seasonal responses, and the dual sensitivity to temperature and moisture characterizing tree-ring-width proxies, are also found to be particularly important. Other experiments highlight the beneficial role of covariance localization on reanalysis ensemble characteristics. This improved paleoclimate data assimilation system served as the basis for the production of the first publicly released NOAA Last Millennium Reanalysis.
Over the last decades, the set of mathematical rules representing the many ecophysiological processes that occur within trees were incorporated into various dendroecological models (eg. MAIDENiso). Such models use simple meteorological variables (precipitation, temperature, CO2) and simulate tree growth parameters that may be readily compared to observations (tree ring widths, stable isotope ratios). Here, we present a novel paleoclimate reconstruction method that uses such ecophysiological model, but in an inverse mode, ie. observed dendroecological variables are used as inputs and climatic variables are retrieved as outputs to produce reconstructions that have strong and sound ecophysiological basis. This novel method represents a significant scientific advance comparing to more conventional (regression-based) transfer function that cannot take into account the array of causal processes linking tree growth to climate. We tested our method on a dataset originating from the Fontaine...
Additions to the Last Millennium Reanalysis Multi-Proxy Database
Data Science Journal, 2019
Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR). The 2290 additional series include 2152 tree ring chronologies and 138 other series. They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation. A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project. The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables. Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods.
A forward modeling approach to paleoclimatic interpretation of tree-ring data
Journal of Geophysical Research, 2006
We investigate the interpretation of tree-ring data using the Vaganov-Shashkin forward model of tree-ring formation. This model is derived from principles of conifer wood growth, and explicitly incorporates a nonlinear daily timescale model of the multivariate environmental controls on tree-ring growth. The model results are shown to be robust with respect to primary moisture and temperature parameter choices. When applied to the simulation of tree-ring widths from North America and Russia from the Mann et al. (1998) and Vaganov et al. (2006) data sets, the forward model produces skill on annual and decadal timescales which is about the same as that achieved using classical dendrochronological statistical modeling techniques. The forward model achieves this without site-by-site tuning as is performed in statistical modeling. The results support the interpretation of this broad-scale network of tree-ring width chronologies primarily as climate proxies for use in statistical paleoclimatic field reconstructions, and point to further applications in climate science.
Journal of the American Statistical Association, 2020
Climate field reconstructions (CFRs) attempt to estimate spatiotemporal fields of climate variables in the past using climate proxies such as tree rings, ice cores, and corals. Data assimilation (DA) methods are a recent and promising new means of deriving CFRs that optimally fuse climate proxies with climate model output. Despite the growing application of DA-based CFRs, little is understood about how much the assimilated proxies change the statistical properties of the climate model data. To address this question, we propose a robust and computationally efficient method, based on functional data depth, to evaluate differences in the distributions of two spatiotemporal processes. We apply our test to study global and regional proxy influence in DA-based CFRs by comparing the background and analysis states, which are treated as two samples of spatiotemporal fields. We find that the analysis states are significantly altered from the climate-model-based background states due to the assimilation of proxies. Moreover, the difference between the analysis and background states increases with the number of proxies, even in regions far beyond proxy collection sites. Our approach allows us to characterize the added value of proxies, indicating where and when the analysis states are distinct from the background states. Supplementary materials for this article are available online.
Testing the Fidelity of Methods Used in Proxy-Based Reconstructions of Past Climate
Journal of Climate, 2005
Two widely used statistical approaches to reconstructing past climate histories from climate "proxy" data such as tree rings, corals, and ice cores are investigated using synthetic "pseudoproxy" data derived from a simulation of forced climate changes over the past 1200 yr. These experiments suggest that both statistical approaches should yield reliable reconstructions of the true climate history within estimated uncertainties, given estimates of the signal and noise attributes of actual proxy data networks.
Comment: Hierarchical Statistical Modeling for Paleoclimate Reconstruction
Journal of the American Statistical Association, 2010
The article by Bo Li, Douglas W. Nychka, and Caspar M. Ammann (hereafter, LNA) has several goals. It considers the important problem of reconstruction of past (over a period of more than 1,000 Years Before Present) climate from multi-proxy data, and it directly recognizes the various uncertainties in this undertaking. These uncertainties are expressed through (conditional) probability distributions in a framework known to readers of this journal as hierarchical statistical modeling. LNA use a physical-statistical model that also includes climate forcings, and their statistical inference is Bayesian. Rather than using actual multi-proxy data, LNA simulate their data. Then they design a computer simulation experiment to assess the value of including the various (simulated) proxies and the forcings. The design of the experiment, its analysis, and the conclusions obtained from it, are intended to guide climate scientists towards more precise inferences when carrying out actual paleoclimate reconstructions. Our discussion of LNA in the sections that follow considers both the scientific and statistical goals summarized above.