Applications of proxy system modeling in high resolution paleoclimatology

AbstractA proxy system model may be defined as the complete set of forward and mechanistic processes by which the response of a sensor to environmental forcing is recorded and subsequently observed in a material archive. Proxy system modeling complements and sharpens signal interpretations based solely on statistical analyses and transformations; provides the basis for observing network optimization, hypothesis testing, and data-model comparisons for uncertainty estimation; and may be incorporated as weak but mechanistically-plausible constraints into paleoclimatic reconstruction algorithms. Following a review illustrating these applications, we recommend future research pathways, including development of intermediate proxy system models for important sensors, archives, and observations; linking proxy system models to climate system models; hypothesis development and evaluation; more realistic multi-archive, multi-observation network design; examination of proxy system behavior under extreme conditions; and generalized modeling of the total uncertainty in paleoclimate reconstructions derived from paleo-observations

Climate field reconstruction uncertainty arising from multivariate and nonlinear properties of predictors

Climate field reconstructions (CFRs) of the global annual surface air temperature (SAT) field and associated global area-weighted mean annual temperature (GMAT) are derived in a collection of pseudoproxy experiments for the past millennium. Pseudoproxies are modeled from temperature (T), precipitation (P), T + P, and VS-Lite (VSL), a nonlinear and multivariate proxy system model for tree ring widths. Spatial patterns of reconstruction skill and spectral bias for the T + P and VSL-derived CFRs are similar to those previously shown using temperature-only pseudoproxies but demonstrate overall degraded skill and spectral bias for SAT reconstruction. Analysis of GMAT spectra nevertheless suggests that the true GMAT frequency spectrum is resolved by those pseudoproxies (T, T + P, and VSL) that contain some temperature information. The results suggest that mixed temperature and moisture-responding paleoclimate data may produce actual GMAT reconstructions with skill, error, and spectral characteristics like those expected from univariate and linear temperature responders, but spatially resolved CFR results should be analyzed cautiousl

Climatically controlled reproduction drives interannual growth variability in a temperate tree species.

Climatically controlled allocation to reproduction is a key mechanism by which climate influences tree growth and may explain lagged correlations between climate and growth. We used continent-wide datasets of tree-ring chronologies and annual reproductive effort in Fagus sylvatica from 1901 to 2015 to characterise relationships between climate, reproduction and growth. Results highlight that variable allocation to reproduction is a key factor for growth in this species, and that high reproductive effort ('mast years') is associated with stem growth reduction. Additionally, high reproductive effort is associated with previous summer temperature, creating lagged climate effects on growth. Consequently, understanding growth variability in forest ecosystems requires the incorporation of reproduction, which can be highly variable. Our results suggest that future response of growth dynamics to climate change in this species will be strongly influenced by the response of reproduction

An Environmentally Forced Tropical Cyclone Hazard Model

A new statistical‐dynamical model is developed for estimating the long‐term hazard of rare, high impact tropical cyclones events globally. There are three components representing the complete storm lifetime: an environmental index‐based genesis model, a beta‐advection track model, and an autoregressive intensity model. All three components depend upon the local environmental conditions, including potential intensity, relative sea surface temperature, 850 and 250 hPa steering flow, deep‐layer mean vertical shear, 850 hPa vorticity, and midlevel relative humidity. The hazard model, using 400 realizations of a 32 year period (approximately 3,000 storms per realization), captures many aspects of tropical cyclone statistics, such as genesis and track density distribution. Of particular note, it simulates the observed number of rapidly intensifying storms, a challenging issue in tropical cyclone modeling and prediction. Using the return period curve of landfall intensity as a measure of local tropical cyclone hazard, the model reasonably simulates the hazard in the western north Pacific (coastal regions of the Philippines, China, Taiwan, and Japan) and the Caribbean islands. In other regions, the observed return period curve can be captured after a local landfall frequency adjustment that forces the total number of landfalls to be the same as that observed while allowing the model to freely simulate the distribution of intensities at landfall

Climate models as a test bed for climate reconstruction methods: pseudoproxy experiments

Millennium-length, forced transient simulations with fully coupled general circulation models have become important new tools for addressing uncertainties in global and hemispheric temperature reconstructions targeting the Common Era (the last two millennia). These model simulations are used as test beds on which to evaluate the performance of paleoclimate reconstruction methods using controlled and systematic investigations known as pseudoproxy experiments (PPEs). Such experiments are motivated by the fact that any given real-world reconstruction is the product of multiple uncontrolled factors, making it difficult to isolate the impact of one factor in reconstruction assessments and comparisons. PPEs have established a common experimental framework that can be systematically altered and evaluated, and thus test reconstruction methods and their dependencies. Although the translation of PPE results into real-world implications must be done cautiously, their experimental design attributes allow researchers to test reconstruction techniques beyond what was previously possible with real-world data alone. This review summarizes the development of PPEs and their findings over the last decade. The state of the science and its implications for global and hemispheric temperature reconstructions is also reviewed, as well as near-term design improvements that will expand the utility of PPEs

Possible causes of data model discrepancy in the temperature history of the last Millennium

Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional response to volcanic eruptions, or hemispheric temperature differences, substantial disagreements between data and models have been reported. Here, we assess the potential sources of these discrepancies by comparing 1000-year hemispheric temperature reconstructions based on real-world paleoclimate proxies with climate-model-based pseudoproxies. These pseudoproxy experiments (PPE) indicate that noise inherent in proxy records and the unequal spatial distribution of proxy data are the key factors in explaining the data-model differences. For example, lower inter-hemispheric correlations in reconstructions can be fully accounted for by these factors in the PPE. Noise and data sampling also partly explain the reduced amplitude of the response to external forcing in reconstructions compared to models. For other metrics, such as inter-hemispheric differences, some, although reduced, discrepancy remains. Our results suggest that improving proxy data quality and spatial coverage is the key factor to increase the quality of future climate reconstructions, while the total number of proxy records and reconstruction methodology play a smaller role

Inference on Tree-Ring Width and Paleoclimate Using a Proxy Model of Intermediate Complexity

Forward and inverse modeling studies of the relationship between tree ring width and bivariate climate are performed using a model called VS-Lite. The monthly time-step model incorporates two simple but realistic nonlinearities in its description of the transformation of climate variability into ring width index. These features ground VS-Lite in scientific principles and make it more complex than empirically-derived statistical models commonly used to simulate tree ring width. At the same time, VS-Lite is vastly simpler and more efficient than pre-existing numerical models that simulate detailed biological aspects of tree growth. A forward modeling validation study shows that VS-Lite simulates a set of observed chronologies across the continental United States with comparable or better skill than simulations derived from a standard, linear regression based approach. This extra skill derives from VS-Lite's basis in mechanistic principles, which makes it more robust than the statistical methodology to climatic nonstationarity. A Bayesian parameterization approach is also developed that incorporates scientific information into the choice of locally optimal VS-Lite parameters. The parameters derived using the scheme are found to be interpretable in terms of the climate controls on growth, and so provide a means to guide applications of the model across varying climatologies. The first reconstructions of paleoclimate that assimilate scientific understanding of the ring width formation process are performed using VS-Lite to link the proxy data to potential climate histories. Bayesian statistical methods invert VS-Lite conditional on a given dendrochronolgy to produce probabilistic estimates of local bivariate climate. Using VS-Lite in this manner produces skillful estimates, but does not present advantages compared another set of probabilistic reconstructions that invert a simpler, linear, empirical forward model. This result suggests that future data-assimilation based reconstructions will need to integrate as many data sources as possible, both across space and proxy types, in order to benefit from information provided by mechanistic models of proxy formation

Climate field reconstruction uncertainty arising from multivariate and nonlinear properties of predictors

©2014. American Geophysical Union. All Rights Reserved. Climate field reconstructions (CFRs) of the global annual surface air temperature (SAT) field and associated global area-weighted mean annual temperature (GMAT) are derived in a collection of pseudoproxy experiments for the past millennium. Pseudoproxies are modeled from temperature (T), precipitation (P), T+P, and VS-Lite (VSL), a nonlinear and multivariate proxy system model for tree ring widths. Spatial patterns of reconstruction skill and spectral bias for the T+P and VSL-derived CFRs are similar to those previously shown using temperature-only pseudoproxies but demonstrate overall degraded skill and spectral bias for SAT reconstruction. Analysis of GMAT spectra nevertheless suggests that the true GMAT frequency spectrum is resolved by those pseudoproxies (T, T+P, and VSL) that contain some temperature information. The results suggest that mixed temperature and moisture-responding paleoclimate data may produce actual GMAT reconstructions with skill, error, and spectral characteristics like those expected from univariate and linear temperature responders, but spatially resolved CFR results should be analyzed cautiously. Key Points Uncertainties may be larger than previously estimated from PPEsReconstructed GMAT based on mixed responders is relatively spectrally unbiasedCFRs based on mixed responders should be interpreted with cautionPeer Reviewe

Bayesian parameter estimation and interpretation for an intermediate model of tree-ring width

We present a Bayesian model for estimating the parameters of the VS-Lite forward model of tree-ring width for a particular chronology and its local climatology. The scheme also provides information about the uncertainty of the parameter estimates, as well as the model error in representing the observed proxy time series. By inferring VS-Lite's parameters independently for synthetically generated ring-width series at several hundred sites across the United States, we show that the algorithm is skillful. We also infer optimal parameter values for modeling observed ring-width data at the same network of sites. The estimated parameter values covary in physical space, and their locations in multidimensional parameter space provide insight into the dominant climatic controls on modeled tree-ring growth at each site as well as the stability of those controls. The estimation procedure is useful for forward and inverse modeling studies using VS-Lite to quantify the full range of model uncertainty stemming from its parameterization