On the certainty framework for causal network discovery with application to tropical cyclone rapid intensification
| dc.contributor.author | DeCaria, Michael, author | |
| dc.contributor.author | van Leeuwen, Peter Jan, advisor | |
| dc.contributor.author | Chiu, Christine, committee member | |
| dc.contributor.author | Barnes, Elizabeth, committee member | |
| dc.contributor.author | Ebert-Uphoff, Imme, committee member | |
| dc.date.accessioned | 2022-05-30T10:21:02Z | |
| dc.date.available | 2022-05-30T10:21:02Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Causal network discovery using information theoretic measures is a powerful tool for studying new physics in the earth sciences. To make this tool even more powerful, the certainty framework introduced by van Leeuwen et al. (2021) adds two features to the existing information theoretic literature. The first feature is a novel measure of relative strength of driving processes created specifically for continuous variables. The second feature consists of three decompositions of mutual information between a process and its drivers. These decompositions are 1) coupled influences from combinations of drivers, 2) information coming from a single driver coupled with a specific number of other drivers (mlinks), and 3) total influence of each driver. To represent all the coupled influences, directed acyclic hypergraphs replace the standard directed acyclic graphs (DAGs). The present work furthers the interpretation of the certainty framework. Measuring relative strength is described thermodynamically. Two-driver coupled influence is interpreted using DAGs, introducing the concept of separability of drivers' effects. Coupled influences are proved to be a type of interaction information. Also, total influence is proved to be nonnegative, meaning the total influences constitute a nonnegative decomposition of mutual information. Furthermore, a new reference distribution for calculating self-certainty is introduced. Finally, the framework is generalized for variables that are continuous with one discrete mode, for which partial Shannon entropy is introduced. The framework was then applied to the rapid intensification of Hurricane Patricia (2015). The hourly change in maximum tangential windspeed was used as the target. The four drivers were outflow layer (OL) maximum radial windspeed (uu), boundary layer (BL) radial windspeed at radius of maximum wind (RMW) (ul), equivalent potential temperature at BL RMW (θe), and the temperature difference between the OL and BL (ΔT). All variables were azimuthally averaged. The drivers explained 45.5% of the certainty. The certainty gain was 35.8% from θe, 24.5% from ΔT, 24.0% from uu, and 15.7% from ul. The total influence of θe came mostly from inseparable effects, while the total influence of uu came mostly from separable effects. Physical mechanisms, both accepted in current literature and suggested from this application, are discussed. | |
| dc.format.medium | born digital | |
| dc.format.medium | masters theses | |
| dc.identifier | DeCaria_colostate_0053N_16996.pdf | |
| dc.identifier.uri | https://hdl.handle.net/10217/235152 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | |
| dc.relation.ispartof | 2020- | |
| dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
| dc.subject | information theory | |
| dc.subject | observational analysis | |
| dc.subject | tropical cyclones | |
| dc.subject | nonnegative decomposition | |
| dc.subject | causal discovery | |
| dc.subject | process interactions | |
| dc.title | On the certainty framework for causal network discovery with application to tropical cyclone rapid intensification | |
| dc.type | Text | |
| dcterms.rights.dpla | This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| thesis.degree.discipline | Atmospheric Science | |
| thesis.degree.grantor | Colorado State University | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science (M.S.) |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- DeCaria_colostate_0053N_16996.pdf
- Size:
- 2.26 MB
- Format:
- Adobe Portable Document Format