European temperature records of the past five centuries based on documentary/instrumental information compared to climate simulations

Zorita, Eduardo; Moberg, Anders; Leijonhufvud, Lotta; Wilson, Rob; Brázdil, Rudolf; Dobrovolný, Petr; Luterbacher, Jürg; Böhm, Reinhard; Pfister, Christian; Riemann, D.; Glaser, Rüdiger; Söderberg, Johan; González-Rouco, J. Fidel

doi:10.1007/s10584-010-9824-7

Cited by 44 publications

(29 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This result is consistent with land surface temperatures reconstructed from tree rings, other terrestrial proxies, and documentary evidence also indicating greater regional variability than simulated by models at decadal and longer timescales (33)(34)(35). That the ECHAM5/MPIOM model simulation of the carbon cycle over the last millenium fails to reproduce the magnitude of preindustrial atmospheric CO 2 variability (20) may also result from too little natural variability.…”

Section: Discussionsupporting

confidence: 82%

Ocean surface temperature variability: Large model–data differences at decadal and longer periods

Laepple

Huybers

2014

Proc. Natl. Acad. Sci. U.S.A.

149

141

View full text Add to dashboard Cite

The variability of sea surface temperatures (SSTs) at multidecadal and longer timescales is poorly constrained, primarily because instrumental records are short and proxy records are noisy. Through applying a new noise filtering technique to a global network of late Holocene SST proxies, we estimate SST variability between annual and millennial timescales. Filtered estimates of SST variability obtained from coral, foraminifer, and alkenone records are shown to be consistent with one another and with instrumental records in the frequency bands at which they overlap. General circulation models, however, simulate SST variability that is systematically smaller than instrumental and proxy-based estimates. Discrepancies in variability are largest at low latitudes and increase with timescale, reaching two orders of magnitude for tropical variability at millennial timescales. This result implies major deficiencies in observational estimates or model simulations, or both, and has implications for the attribution of past variations and prediction of future change.sea surface temperature | climate variability | multiproxy synthesis | proxy data reconstruction V ariations in sea surface temperature (SSTs) have widespread implications for society and are the basis of most regional decadal prediction efforts (1). Magnitudes of variability in regional SSTs are inferred either using observations or simulations from general circulation models (GCMs). At synoptic and interannual timescales, there is overall agreement between observational and GCM estimates of SST variability (2-4). At decadal timescales, however, instrumental records generally show greater regional SST variability than found in the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble of GCM simulations (4) and in earlier simulations (5-7). Discrepancies are greatest at low latitudes where model−data mismatches in variance reach a factor of 2 (Fig. 1).Estimating regional SST variability at multidecadal and longer timescales presents a quandary. Discrepancies with instrumentally observed SST variability at decadal timescales calls into question the credibility of GCM estimates at longer timescales. At the same time, instrumental observations covering more than 100 y of SST variability are sparse. For example, whereas 68% of ocean grid boxes in the Climate Research Unit's instrumental compilation of SSTs have a 30-y interval with an observational density of at least 100 observations per year, only 19% of grid boxes have such coverage over a 100-y interval (8). Furthermore, SST variability observed during the last century represents contributions from natural and anthropogenic sources that are difficult to disentangle and are not necessarily representative of any other interval (9).One is inevitably led to using paleoclimate proxies to constrain multidecadal and longer-term variability. Numerous paleoclimate reconstructions document low-frequency SST variability (10-15), but the degree to which these reconstructions afford quantitative constraints of annual...

show abstract

Section: Discussionsupporting

confidence: 82%

Ocean surface temperature variability: Large model–data differences at decadal and longer periods

Laepple

Huybers

2014

Proc. Natl. Acad. Sci. U.S.A.

149

141

View full text Add to dashboard Cite

show abstract

“…Jansen et al, 2007;Brázdil et al, 2010;Luterbacher et al, 2010;Jungclaus et al, 2010;Zorita et al, 2010;Zanchettin et al, 2013). For instance, Jungclaus et al (2010) show good agreement between the full-forcing simulations in the COSMOS-Mill ensemble and the HadCRUT3v Northern Hemisphere temperature data for the 20th century.…”

Section: Discussion Of the Resultsmentioning

confidence: 86%

Climate of the last millennium: ensemble consistency of simulations and reconstructions

et al. 2013

View full text Add to dashboard Cite

Are simulations and reconstructions of past climate and its variability consistent with each other? We assess the consistency of simulations and reconstructions for the climate of the last millennium under the paradigm of a statistically indistinguishable ensemble. In this type of analysis, the null hypothesis is that reconstructions and simulations are statistically indistinguishable and, therefore, are exchangeable with each other. Ensemble consistency is assessed for Northern Hemisphere mean temperature, Central European mean temperature and for global temperature fields. Reconstructions available for these regions serve as verification data for a set of simulations of the climate of the last millennium performed at the Max Planck Institute for Meteorology.

Consistency is generally limited to some sub-domains and some sub-periods. Only the ensemble simulated and reconstructed annual Central European mean temperatures for the second half of the last millennium demonstrates unambiguous consistency. Furthermore, we cannot exclude consistency of an ensemble of reconstructions of Northern Hemisphere temperature with the simulation ensemble mean.

If we treat simulations and reconstructions as equitable hypotheses about past climate variability, the found general lack of their consistency weakens our confidence in inferences about past climate evolutions on the considered spatial and temporal scales. That is, our available estimates of past climate evolutions are on an equal footing but, as shown here, inconsistent with each other

show abstract

“…Thus, individual or site chronologies are ideally aggregated into one regional chronology that captures a regional climate signal, the same spatial resolution that climate models are intended to represent. Furthermore, the technique applied to transform tree-ring parameters to meteorological units also implies a challenge: whereas simple linear regression methods may underestimate low-frequency variability, variance matching, in the following referred to as scaling, shows better performance in retaining large-scale variations but at the expense of inflated error estimates (Esper et al, 2005b;Zorita et al, 2010;McCarrol et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Estimating 750 years of temperature variations and uncertainties in the Pyrenees by tree-ring reconstructions and climate simulations

et al. 2012

View full text Add to dashboard Cite

Abstract. Past temperature variations are usually inferred from proxy data or estimated using general circulation models. Comparisons between climate estimations derived from proxy records and from model simulations help to better understand mechanisms driving climate variations, and also offer the possibility to identify deficiencies in both approaches. This paper presents regional temperature reconstructions based on tree-ring maximum density series in the Pyrenees, and compares them with the output of global simulations for this region and with regional climate model simulations conducted for the target region. An ensemble of 24 reconstructions of May-to-September regional mean temperature was derived from 22 maximum density tree-ring site chronologies distributed over the larger Pyrenees area. Four different tree-ring series standardization procedures were applied, combining two detrending methods: 300-yr spline and the regional curve standardization (RCS). Additionally, different methodological variants for the regional chronology were generated by using three different aggregation methods. Calibration verification trials were performed in split periods and using two methods: regression and a simple variance matching. The resulting set of temperature reconstructions was compared with climate simulations performed with global (ECHO-G) and regional (MM5) climate models.The 24 variants of May-to-September temperature reconstructions reveal a generally coherent pattern of inter-annual to multi-centennial temperature variations in the Pyrenees region for the last 750 yr. However, some reconstructions display a marked positive trend for the entire length of the reconstruction, pointing out that the application of the RCS method to a suboptimal set of samples may lead to unreliable results.Climate model simulations agree with the tree-ring based reconstructions at multi-decadal time scales, suggesting solar variability and volcanism as the main factors controlling preindustrial mean temperature variations in the Pyrenees. Nevertheless, the comparison also highlights differences with the reconstructions, mainly in the amplitude of past temperature variations and in the 20th century trends. Neither proxy-based reconstructions nor model simulations are able to perfectly track the temperature variations of the instrumental record, suggesting that both approximations still need further improvements.Published by Copernicus Publications on behalf of the European Geosciences Union. 920

show abstract

European temperature records of the past five centuries based on documentary/instrumental information compared to climate simulations

Cited by 44 publications

References 67 publications

Ocean surface temperature variability: Large model–data differences at decadal and longer periods

Ocean surface temperature variability: Large model–data differences at decadal and longer periods

Climate of the last millennium: ensemble consistency of simulations and reconstructions

Estimating 750 years of temperature variations and uncertainties in the Pyrenees by tree-ring reconstructions and climate simulations

Contact Info

Product

Resources

About