Geoscience Reference
In-Depth Information
Keywords Temperature trends
Holocene
Proxy data
Earth system models
Climate variability
Data-model comparison
1 Introduction
In order to examine sea-surface temperature (SST) trends caused by growing
emissions of greenhouse gases and how they induce a signi
cant impact on the
Earth
s climate, we need the knowledge about the variability of the natural system.
Unfortunately, the instrumental record with a large-scale coverage of data goes
back only to the time when human industrialisation started. Information beyond the
instrumental record covering the last 150 years can only be obtained indirectly from
two strategies. On the one hand, they can be derived from proxies that record past
climate and environmental conditions. On the other hand, the past climate can be
simulated using comprehensive models of the climate system under appropriate
external forcing. Numerical climate models are clearly able to simulate a broad suite
of phenomena in the current climate system, but their reliability on longer time-
scales requires additional evaluation. Only climate records derived from paleoen-
vironmental proxies enable the test of these models because they provide records of
climate variations that have actually occurred in the past.
'
2 Materials and Methods
a. Data: The proxy data work undertaken was focused on updating the global
database for proxy-derived Holocene SST records, i.e., an SST synthesis based
on alkenone-derived SST estimation, and a synthesis effort compiling the SST
records derived from foraminiferal Mg/Ca was carried out (Leduc et al.
2010a
).
b. Complex models: We use and evaluate a suite of atmosphere-ocean circulation
models to evaluate the temperature evolution. We concentrate on ECHO-G
(Lorenz and Lohmann
2004
) and COSMOS (Fischer and Jungclaus
2010
,
2011
;
Pfeiffer and Lohmann
2013
), but use also data from time slice experiments as
compiled in PMIP2 and PMIP3 (Lohmann et al.
2013
).
c. Conceptual model and theoretical framework: A concept for the physical
understanding of insolation-driven temperature variability on orbital timescales
is developed. Based at this concept, the temperature evolution of the intergla-
cials related to local insolation forcing is estimated (Laepple and Lohmann
2009
).
d. Data-model and intermodel comparisons: We used several statistical techniques
to compare data with models. We also participated on model intercomparisons
(e.g., Lunt et al.
2013
).
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