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A statistical-dynamical modeling approach for the simulation of local paleo proxy records using GCM output


Reichert,  Bernhard K.
MPI for Meteorology, Max Planck Society;

Bengtsson,  Lennart
MPI for Meteorology, Max Planck Society;

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Reichert, B. K., Bengtsson, L., & Åkesson, O. (1998). A statistical-dynamical modeling approach for the simulation of local paleo proxy records using GCM output. Report / Max-Planck-Institut für Meteorologie, 274.

Cite as: https://hdl.handle.net/21.11116/0000-0005-8049-8
Recent proxy data obtained from ice core measurements, dendrochronology and valley
glaciers provide important information on the evolution of the regional or local climate. General
Circulation Models integrated over a long period of time could help to understand the (external
and internal) forcing mechanisms of natural climate variability. For a systematic interpretation
of in situ paleo proxy records, a combined method of dynamical and statistical modeling is
proposed. Local ,paleo records' can be simulated from GCM output by first undertaking a
model-consistent statistical downscaling and then using a process-based forward modeling
approach to obtain the behavior of valley glaciers and the growth of trees under specific
conditions. The simulated records can be compared to actual proxy records in order to
investigate whether e.g. the response of glaciers to climatic change can be reproduced by
models and to what extent climate variability obtained from proxy records (with the main focus
on the last millennium) can be represented. For statistical downscaling to local weather
conditions, a multiple linear forward regression model is used. Daily sets of observed weather
station data and various large-scale predictors at 7 pressure levels obtained from ECMWF re-
analyses are used for development of the model. Daily data give the closest and most robust
relationships due to the strong dependence on individual synoptic-scale patterns. For some local
variables, the performance of the model can be further increased by developing seasonal
specific statistical relationships. The model is validated using both independent and restricted
predictor data sets. The model is applied to a long integration of a mixed layer GCM experiment
simulating pre-industrial climate variability. The dynamical-statistical local GCM output within
a region around Nigardsbreen glacier, Norway is compared to nearby observed station data for
the period 1868-1993. Patterns of observed variability on the annual to decadal scale and the
mean temperature change due to pre-industrial climatic conditions are realistically simulated for
this location. The local output produced by the described method will be used to force a process-
based model for the production of ,synthetic' proxy data, e.g. the simulation of a valley glacier.