Internationale Baumringexperten: Mittelalterliche Wärmeperiode war heißer als gedacht. Klimamodelle scheitern bei Simulation

Allmählich nimmt das Millenniumsklima Fahrt auf. Am 15. Februar 2016 erschien in den Quaternary Science Reviews eine Arbeit eines Team um Rob Wilson, in dem die Temperaturentwicklung der nördlichen Hemisphäre auf Basis von Baumringen rekonstruiert wird. Und wer hätte es gedacht, die Forscher fanden eine Mittelalterliche Wärmeperiode von 900-1170 n.Chr., die länger und heißer als in den Vorgängerrekonstruktionen war. Das ist erfreulich, man scheint sich nun schrittweise der Realität anzupassen. Die dunklen Zeiten des Hockey Stick sind endgültig vorüber. Höchst bemerkenswert ist zudem die Feststellung der Autoren, dass die aktuellen Klimamodelle die Entwicklung der Mittelalterlichen Wärmeperiode nicht nachvollziehen können. Es muss also etwas Bedeutendes in den Modellen fehlen – eine wichtige Erkenntnis. Zukunftsmodellierungen auf Basis derselben Klimamodelle müsen entsprechend mit einer gesunden Portion Skepsis gesehen werden. Hier die Kurzfassung der Arbeit:

Last millennium northern hemisphere summer temperatures from tree rings: Part I: The long term context
Large-scale millennial length Northern Hemisphere (NH) temperature reconstructions have been progressively improved over the last 20 years as new datasets have been developed. This paper, and its companion (Part II, Anchukaitis et al. in prep), details the latest tree-ring (TR) based NH land air temperature reconstruction from a temporal and spatial perspective. This work is the first product of a consortium called N-TREND (Northern Hemisphere Tree-Ring Network Development) which brings together dendroclimatologists to identify a collective strategy for improving large-scale summer temperature reconstructions. The new reconstruction, N-TREND2015, utilises 54 records, a significant expansion compared with previous TR studies, and yields an improved reconstruction with stronger statistical calibration metrics. N-TREND2015 is relatively insensitive to the compositing method and spatial weighting used and validation metrics indicate that the new record portrays reasonable coherence with large scale summer temperatures and is robust at all time-scales from 918 to 2004 where at least 3 TR records exist from each major continental mass. N-TREND2015 indicates a longer and warmer medieval period (∼900–1170) than portrayed by previous TR NH reconstructions and by the CMIP5 model ensemble, but with better overall agreement between records for the last 600 years. Future dendroclimatic projects should focus on developing new long records from data-sparse regions such as North America and eastern Eurasia as well as ensuring the measurement of parameters related to latewood density to complement ring-width records which can improve local based calibration substantially.

Innerhalb weniger Wochen ist dies bereits die zweite Arbeit, die den Mißstand fehlschlagender Klimamodellierungen beklagt. Vor kurzem war es die Universität Gießen, die eklatante Unterschiede zwischen realer und simulierter Temperaturentwicklung während der letzten 2000 Jahre in Europa fand. Dies ist höchsterfreulich. Können wir den Betrieb dieses Blog also bald einstellen? Dies wäre zu hoffen, wenn sich der Klimarealismus nun endlich durchsetzen könnte.

Natürlich gibt es auch in der Wilson-Studie einige Problemchen. Die Moderne Wärmeperiode wird als deutlich wärmer als die Mittelalterliche Wärmeperiode dargestellt. Allerdings ist hier wohl vor allem die Auswahl der (wenigen) Proxy-Kurven Schuld. Es ließen sich also je nach Bedarf auch ganz andere Schluss-Segmente produzieren (Stichwort: Happy End vs. Tragic End). Siehe Beiträge auf Bishop Hill und WUWT. Ab der zweiten Hälfte des 20. Jahrhunderts tritt zudem eine störende Divergenz zwischen Baumringen und der Temperatur auf, was eine verlässliche Klimaaussage in diesem Zeitabschnitt schwierig macht.

Generell ist der Baumring-Studie jedoch sicher zu trauen, auch wenn Baumringe nicht ganz pflegeleicht sind und es böse Fallen gibt, die es zu vermeiden gilt. In einer Pressemitteilung vom 27. Januar 2016 wies die University of Otago auf diese Komplikationen hin:

Uncertainties in tree-ring-based climate reconstructions probed
Current approaches to reconstructing past climate by using tree-ring data need to be improved on so that they can better take uncertainty into account, new research led out of New Zealand’s University of Otago suggests.

Tree growth rings are commonly used as climate proxies because they can be well-dated and the width of each ring is influenced by the climatic conditions of the year it grew in. In a paper appearing in the Journal of the American Statistical Association, statistics and tree ring researchers from Otago, the US and UK examined the statistical methods and procedures commonly used to reconstruct historic climate variables from tree-ring data.

The research was led by Dr Matthew Schofield of Otago’s Department of Mathematics and Statistics. His co-authors on the paper are departmental colleague Professor Richard Barker, Professor Andrew Gelman of Columbia University, Director of the Tree Ring Lab at Columbia Professor Ed Cook, and Emeritus Professor Keith Briffa of the University of East Anglia, UK. Dr Schofield says that their approach was to explore two areas where currently used approaches may not adequately account for these uncertainties. The first area involves the pre-processing of tree-ring data to remove non-climate related factors believed to be largely unrelated to climate effects on tree growth. Such factors include tree age, as the older a tree gets the less wide its rings tend to grow. “This is convenient to do and the resulting tree-ring ‘chronologies’ are treated as relating to only the climate variables of interest. However, it assumes perfect removal of the non-climatic effects from the tree-ring data and ignores any uncertainty in removing this information,” Dr Schofield says.

The second area of uncertainty the researchers studied involves the particular modelling assumptions used in order to reconstruct climate from tree rings. Many of the assumptions are default choices, often chosen for convenience or manageability. “This has made it difficult to evaluate how sensitive reconstructions are to alternate modelling assumptions,” he says. To test this sensitivity, the researchers developed a unified statistical modelling approach using Bayesian inference that simultaneously accounts for non-climatic and climatic variability. The team reconstructed summer temperature in Northern Sweden between 1496 and 1912 from ring measurements of 121 Scots Pine trees.

They found that competing models fit the Scots Pine data equally well but still led to substantially different predictions of historical temperature due to the differing assumptions underlying each model. While the periods of relatively warmer and cooler temperatures were robust between models, the magnitude of the resulting temperatures was highly dependent on the model being used. This suggests that there is less certainty than implied by a reconstruction developed using any one set of assumptions.

Am 23. März 2016 legte dann eine Gruppe um Juhani Rinne in Climate of the Past Discussions nach. Abschnitte mit spärlichen Daten bzw. Datenlücken würden zu falschen Trendaussagen führen. Hier der Abstract:

A universal error source in past climate estimates derived from tree rings
Recently it has been shown that climate estimates derived from tree rings often tend to show erroneous long-term oscillations, i.e. there are spectral biases at low frequencies. The result is independent of parameter studied (precipitation or temperature) or measured proxy (tree ring widths or maximum latewood densities). In order to find reasons for such universal errors, a new reconstruction method is introduced where no age dependence of the tree rings is determined. The aim, however, is not to generate better reconstructions but to study error variances of long-term oscillations. It is shown that paucities and data gaps due to missing trees increase the risk for erroneous low-frequency variability. A general approximate formula is introduced in order to estimate the presence of such a risk. A case study using Torneträsk data from Northern Sweden illustrates how longer periods with missing trees cause paucities and gaps leading to erroneous climatic oscillations. Systematic underestimation of the temperature around AD 1600 and after 1950 (“divergence”) is in the study case explained by such data gaps and paucities.