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Dataset . 2022
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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Global Soil Moisture-Air Temperature Interactions from Linear and Nonlinear Granger Causalities

Authors: Bhatti, Asher S.; Hagan, Daniel F. T; Wang, Guojie; Ullah, Waheed; Nooni, Isaac K; Amakwah, Solomon; Zhou, Feihong;

Global Soil Moisture-Air Temperature Interactions from Linear and Nonlinear Granger Causalities

Abstract

These datasets were generated to assess linear and nonlinear Granger causalities in the submitted manuscript, Global Soil Moisture-Air Temperature Interactions from Linear and Nonlinear Granger Causalities by Bhatti et al. submitted to AGU-GRL. Nonlinear GC here is achieved with the Kernel Granger causality by Marinazzo et al. (2008). The data was used to develop theoretical experiments that help validate the strengths and limitations of both the linear Granger causality and the Kernel Granger causality before applying to real world datasets

The manuscript is yet to be peer reviewed. Therefore, the data should be used with caution as review comments could require some changes in the experiment setup.

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Keywords

Kernel Granger Causality, Soil moisture-air temperature interaction, Granger Causality, Nonlinear causality

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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