Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability
Abstract: The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing ( Laepple and Huybers, 2014a , 2014b ). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled “pseudoproxies” exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database ( PAGES2K Consortium, 2013 ). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate record may exhibit larger low-frequency variability than GCMs currently simulate, indicative of incomplete physics and/or forcings.
Summary (2 min read)
2.1. GCM & PSM-Generated Pseudoproxies
- Each proxy type employs its own unique PSM.
- The complicated nature of proxy data (e.g. chronological uncertainties and impacts on phasing) precludes point-to-point comparisons of time series, and thus there is a strong case for comparing simulated proxy to the observations in the frequency domain.
3. Case Studies
- Various approaches including downscaling or bias correction can help to minimize such problems, or paleoclimate data can be aggregated to match GCM grid cell size.
- For each proxy type, the authors attempt to answer whether the mismatch arises from a lack of low-frequency variability simulated by the GCM SPEEDY-IER, or from a data-model comparison strategy problem.
- For completeness, the authors report absolute variance for all case studies and the PAGES2k data in SI Section S3.
3.1. Spectral Fingerprinting of Proxy Systems
- As a first pass, the authors forced each PSM with white noise climate inputs to assess the impact of proxy system processes alone on the shape of the spectra.
- For ice cores, speleothems, and tree ring widths, the white noise +.
- For all proxy types, the spectra revert to the shape of the white input climate signal on decadal and longer timescales.
- Under different PSM formulations these spectra could change significantly, and this non-unicity proves a large source of uncertainty.
- Shows that the corals are generally strong SST proxies (or, possibly, that the GCM completely underplays salinity variability).
- Testing the effects of parametric uncertainty for the corals provides an example of how PSMs can be used to inform data-model comparison.
- More interestingly, discrepancies exist between the simulated and observed power spectrum on decadal to centennial timescales.
- Further, if the authors instead evaluate both in terms of absolute variance, the Palmyra record exhibits larger σ at the decadal band as compared to the PSM-simulated data (SI Section S3).
- While the PSM-generated pseudo-coral captures interannual SST variability similar to observations, the PSM seems not to account for the larger variance in the observations on longer timescales, and this discrepancy remains even when uncertainties in the coral's sensitivity to salinity and δ 18 O S W are taken into account.
3.2.2. Ice Cores
- On decadal to centennial timescales, differences in the observed vs. simulated spectral slopes are more modest than for interannual, but three of the records tend to increasingly diverge at low frequencies (see Fig. 3 ).
- 18 O PRECIP vs. the observed ice core values exhibit some agreement on multi-decadal frequencies, but the model does not simulate comparable variance in the observations on longer (>centennial) timescales (see Fig. 3 ).
- This suggests that neither the GCM, the water isotope physics in the GCM, nor the PSM can account for observed low frequency variability.
- The speleothem PSM highlights the fact that on interannual to decadal timescales, the authors can essentially obtain a β value in agreement with observations simply as a function of the karst parameters.
- On longer timescales, the simulated spectra tend to flatten while the observed spectra continue to show increased lowfrequency variance, potentially indicative of climate processes resulting in a spectrum similar to what the authors would expect from a power law system (see Fig. 5 ).
3.2.5. Tree Ring Width
- Aggressive detrending methods tend to remove low frequency variability (demonstrated by Table 2 ).
- Table 2 also illustrates the RCS method is most conservative in maintaining low-frequency TRW variability.
- In general, using the same detrending method for both proxy and pseudoproxy is essential.
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Cites background from "Improved spectral comparisons of pa..."
...…interdecadal GMST variability (Brown et al., 2015, 2017; Parsons & Hakim, 2019), with both instrumental (Laepple & Huybers, 2014a) and paleoclimate (Dee et al., 2017; Laepple & Huybers, 2014b; Parsons et al., 2017) evidence suggesting that climate models may underestimate local, low‐frequency…...
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In this paper the authors bridge this gap via a forward modeling approach, coupled to an isotope-enabled GCM. The paper addresses the following questions: ( 1 ) do forward modeled “ pseudoproxies ” exhibit variability comparable to proxy data ? The authors apply their method to representative case studies, and parlay these insights into an analysis of the PAGES2k database ( ? ). The authors conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate record may exhibit larger low-frequency variability than GCMs currently simulate, indicative of ∗Corresponding author Email addresses: sylvia 11 dee @ brown. The authors find that current proxy system models ( PSMs ) can help resolve model-data discrepancies on interannual to decadal timescales, but can not account for the mismatch in variance on multi-decadal to centennial timescales.