A Last Glacial Maximum forcing dataset for ocean modelling
Model simulations of the Last Glacial Maximum (LGM; ∼ 21 000 years before present) can aid the interpretation of proxy records, can help to gain an improved mechanistic understanding of the LGM climate system, and are valuable for the evaluation of model performance in a different climate state. Oce...
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Veröffentlicht in: | Earth system science data 2020-11, Vol.12 (4), p.2971-2985 |
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Zusammenfassung: | Model simulations of the Last Glacial Maximum (LGM;
∼ 21 000 years before present) can aid the interpretation of
proxy records, can help to gain an improved mechanistic understanding of the LGM
climate system, and are valuable for the evaluation of model performance in
a different climate state. Ocean-ice only model configurations forced by
prescribed atmospheric data (referred to as “forced ocean models”)
drastically reduce the computational cost of palaeoclimate modelling
compared to fully coupled model frameworks. While feedbacks between the
atmosphere and ocean and sea-ice compartments of the Earth system are not
present in such model configurations, many scientific questions can be
addressed with models of this type. Our dataset supports simulations of the
LGM in a forced ocean model set-up while still taking advantage of the
complexity of fully coupled model set-ups. The data presented here are
derived from fully coupled palaeoclimate simulations of the Palaeoclimate
Modelling Intercomparison Project phase 3 (PMIP3). The data are publicly
accessible at the National Infrastructure for Research Data (NIRD) Research Data Archive at
https://doi.org/10.11582/2020.00052 (Morée and Schwinger, 2020). They
consist of 2-D anomaly forcing fields suitable for use in ocean models that
employ a bulk forcing approach and are optimized for use with CORE forcing
fields. The data include specific humidity, downwelling long-wave and
short-wave radiation, precipitation, wind (v and u components), temperature,
and sea surface salinity (SSS). All fields are provided as climatological
mean anomalies between LGM and pre-industrial (PI) simulations. These anomaly
data can therefore be added to any pre-industrial ocean forcing dataset in
order to obtain forcing fields representative of LGM conditions as simulated
by PMIP3 models. Furthermore, the dataset can be easily updated to reflect
results from upcoming and future palaeo-model intercomparison activities. |
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ISSN: | 1866-3516 1866-3508 1866-3516 |
DOI: | 10.5194/essd-12-2971-2020 |