3 resultados para LPJ-GUESS model

em Publishing Network for Geoscientific


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This data sets contains LPJ-LMfire dynamic global vegetation model output covering Europe and the Mediterranean for the Last Glacial Maximum (LGM; 21 ka) and for a preindustrial control simulation (20th century detrended climate). The netCDF data files are time averages of the final 30 years of the model simulation. Each netCDF file contains four or five variables: fractional cover of 9 plant functional types (PFTs; cover), total fractional coverage of trees (treecover), population density of hunter-gatherers (foragerPD; only for the "people" simulations), fraction of the gridcell burned on 30-year average (burnedf), and vegetation net primary productivity (NPP). The model spatial resolution is 0.5-degrees For the LGM simulations, LPJ-LMfire was driven by the PMIP3 suite of eight GCMs for which LGM climate simulations were available. Also provided in this archive is the result of an LPJ-LMfire run that was forced by the average climate of all GCMs (the "GCM-mean" files), and the average of each of the individual LPJ-LMfire runs over the eight LGM scenarios individually (the "LPJ-mean" files). The model simulations are provided that include the influence of human presence on the landscape (the "people" files), and in a "world without humans" scenario (the "natural" files). Finally this archive contains the preindustrial reference simulation with and without human influence ("PI_reference_people" and "PI_reference_nat", respectively). There are therefore 22 netCDF files in this archive: 8 each of LGM simulations with and without people (total 16) and the "GCM mean" simulation (2 files) and the "LPJ mean" aggregate (2 files), and finally the two preindustrial "control" simulations ("PI"), with and without humans (2 files). In addition to the LPJ-LMfire model output (netCDF files), this archive also contains a table of arboreal pollen percent calculated from pollen samples dated to the LGM at sites throughout (lgmAP.txt), and a table containing the location of archaeological sites dated to the LGM (LGM_archaeological_site_locations.txt).

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In a feasibility study, the potential of proxy data for the temperature and salinity during the Last Glacial Maximum (LGM, about 19 000 to 23 000 years before present) in constraining the strength of the Atlantic meridional overturning circulation (AMOC) with a general ocean circulation model was explored. The proxy data were simulated by drawing data from four different model simulations at the ocean sediment core locations of the Multiproxy Approach for the Reconstruction of the Glacial Ocean surface (MARGO) project, and perturbing these data with realistic noise estimates. The results suggest that our method has the potential to provide estimates of the past strength of the AMOC even from sparse data, but in general, paleo-sea-surface temperature data without additional prior knowledge about the ocean state during the LGM is not adequate to constrain the model. On the one hand, additional data in the deep-ocean and salinity data are shown to be highly important in estimating the LGM circulation. On the other hand, increasing the amount of surface data alone does not appear to be enough for better estimates. Finally, better initial guesses to start the state estimation procedure would greatly improve the performance of the method. Indeed, with a sufficiently good first guess, just the sea-surface temperature data from the MARGO project promise to be sufficient for reliable estimates of the strength of the AMOC.

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We are investigating the late Holocene rise in CO2 by performing four experiments with the climate-carbon-cycle model CLIMBER2-LPJ. Apart from the deep sea sediments, important carbon cycle processes considered are carbon uptake or release by the vegetation, carbon uptake by peatlands, and CO 2 release due to shallow water sedimentation of CaCO3. Ice core data of atmospheric CO2 between 8 ka BP and preindustrial climate can only be reproduced if CO2 outgassing due to shallow water sedimentation of CaCO3 is considered. In this case the model displays an increase of nearly 20 ppmv CO2 between 8 ka BP and present day. Model configurations that do not contain this forcing show a slight decrease in atmospheric CO2. We can therefore explain the late Holocene rise in CO2 by invoking natural forcing factors only, and anthropogenic forcing is not required to understand preindustrial CO2 dynamics.