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Forcing data, evaluation data, model output and analysis scripts used in LPJ-GUESS/LSM description paper

Authors: Martin-Belda, David;

Forcing data, evaluation data, model output and analysis scripts used in LPJ-GUESS/LSM description paper

Abstract

This archive contains: - model_output.tar.gz: Model output - extracted_fluxes.tar.gz: Sensible heat, latent heat and CO2 fluxes extracted from the FLUXNET2015 dataset, used to evaluate the model output - extracted_climate.tar.gz: Climate data extracted from the FLUXNET2015 dataset, used to force the simulations - scripts.tar.gz: Python scripts used to analyze the data and produce the results reported in the model description paper The climate forcing data has been extracted from the FLUXNET2015 dataset [1]. Input and output data is stored in netCDF files. Evaluation data is stored in python serialized files (pickle). [1] Pastorello, G., Trotta, C., Canfora, E. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci Data 7, 225 (2020). https://doi.org/10.1038/s41597-020-0534-3

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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