On the data-driven inference of modulatory networks in climate science: An application to West African rainfall
Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, n...
Published in: | Nonlinear Processes in Geophysics |
---|---|
Main Authors: | , , , , , , , , , , |
Language: | unknown |
Published: |
2017
|
Subjects: | |
Online Access: | http://www.osti.gov/servlets/purl/1333075 https://www.osti.gov/biblio/1333075 https://doi.org/10.5194/npg-22-33-2015 |
id |
ftosti:oai:osti.gov:1333075 |
---|---|
record_format |
openpolar |
spelling |
ftosti:oai:osti.gov:1333075 2023-07-30T04:05:27+02:00 On the data-driven inference of modulatory networks in climate science: An application to West African rainfall Gonzalez, II, D. L. Angus, M. P. Tetteh, I. K. Bello, G. A. Padmanabhan, K. Pendse, S. V. Srinivas, S. Yu, J. Semazzi, Fred Kumar, Vipin Samatova, Nagiza F. 2017-11-01 application/pdf http://www.osti.gov/servlets/purl/1333075 https://www.osti.gov/biblio/1333075 https://doi.org/10.5194/npg-22-33-2015 unknown http://www.osti.gov/servlets/purl/1333075 https://www.osti.gov/biblio/1333075 https://doi.org/10.5194/npg-22-33-2015 doi:10.5194/npg-22-33-2015 54 ENVIRONMENTAL SCIENCES 2017 ftosti https://doi.org/10.5194/npg-22-33-2015 2023-07-11T09:16:09Z Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. As a result, these relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research. Other/Unknown Material North Atlantic North Atlantic oscillation SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Nonlinear Processes in Geophysics 22 1 33 46 |
institution |
Open Polar |
collection |
SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
54 ENVIRONMENTAL SCIENCES |
spellingShingle |
54 ENVIRONMENTAL SCIENCES Gonzalez, II, D. L. Angus, M. P. Tetteh, I. K. Bello, G. A. Padmanabhan, K. Pendse, S. V. Srinivas, S. Yu, J. Semazzi, Fred Kumar, Vipin Samatova, Nagiza F. On the data-driven inference of modulatory networks in climate science: An application to West African rainfall |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. As a result, these relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research. |
author |
Gonzalez, II, D. L. Angus, M. P. Tetteh, I. K. Bello, G. A. Padmanabhan, K. Pendse, S. V. Srinivas, S. Yu, J. Semazzi, Fred Kumar, Vipin Samatova, Nagiza F. |
author_facet |
Gonzalez, II, D. L. Angus, M. P. Tetteh, I. K. Bello, G. A. Padmanabhan, K. Pendse, S. V. Srinivas, S. Yu, J. Semazzi, Fred Kumar, Vipin Samatova, Nagiza F. |
author_sort |
Gonzalez, II, D. L. |
title |
On the data-driven inference of modulatory networks in climate science: An application to West African rainfall |
title_short |
On the data-driven inference of modulatory networks in climate science: An application to West African rainfall |
title_full |
On the data-driven inference of modulatory networks in climate science: An application to West African rainfall |
title_fullStr |
On the data-driven inference of modulatory networks in climate science: An application to West African rainfall |
title_full_unstemmed |
On the data-driven inference of modulatory networks in climate science: An application to West African rainfall |
title_sort |
on the data-driven inference of modulatory networks in climate science: an application to west african rainfall |
publishDate |
2017 |
url |
http://www.osti.gov/servlets/purl/1333075 https://www.osti.gov/biblio/1333075 https://doi.org/10.5194/npg-22-33-2015 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
http://www.osti.gov/servlets/purl/1333075 https://www.osti.gov/biblio/1333075 https://doi.org/10.5194/npg-22-33-2015 doi:10.5194/npg-22-33-2015 |
op_doi |
https://doi.org/10.5194/npg-22-33-2015 |
container_title |
Nonlinear Processes in Geophysics |
container_volume |
22 |
container_issue |
1 |
container_start_page |
33 |
op_container_end_page |
46 |
_version_ |
1772817369924632576 |