Mid-Holocene climate change over China: model–data discrepancy
The mid-Holocene period (MH) has long been an ideal target for the validation of general circulation model (GCM) results against reconstructions gathered in global datasets. These studies aim to test GCM sensitivity, mainly to seasonal changes induced by the orbital parameters (longitude of the peri...
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Veröffentlicht in: | Climate of the past 2019-07, Vol.15 (4), p.1223-1249 |
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Zusammenfassung: | The mid-Holocene period (MH) has long been an ideal target for the validation
of general circulation model (GCM) results against reconstructions gathered in
global datasets. These studies aim to test GCM sensitivity, mainly to
seasonal changes induced by the orbital parameters (longitude of the
perihelion). Despite widespread agreement between model results and data on
the MH climate, some important differences still exist. There is no consensus
on the continental size (the area of the temperature anomaly) of the MH
thermal climate response, which makes regional quantitative reconstruction
critical to obtain a comprehensive understanding of the MH climate patterns.
Here, we compare the annual and seasonal outputs from the most recent
Paleoclimate Modelling Intercomparison Project Phase 3 (PMIP3) models with an
updated synthesis of climate reconstruction over China, including, for the
first time, a seasonal cycle of temperature and precipitation. Our results
indicate that the main discrepancies between model and data for the MH
climate are the annual and winter mean temperature. A warmer-than-present
climate condition is derived from pollen data for both annual mean
temperature (∼0.7 K on average) and winter mean temperature
(∼1 K on average), while most of the models provide both
colder-than-present annual and winter mean temperature and a relatively
warmer summer, showing a linear response driven by the seasonal forcing. By
conducting simulations in BIOME4 and CESM, we show that surface processes
are the key factors creating the uncertainties between models and data. These
results pinpoint the crucial importance of including the non-linear responses
of the surface water and energy balance to vegetation changes. |
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ISSN: | 1814-9332 1814-9324 1814-9332 |
DOI: | 10.5194/cp-15-1223-2019 |