Advancements in Climate Modeling and Prediction through Machine Learning Techniques
The popularity of Machine learning (ML) is increased in the field of weather and climate modelling. Enforcement variety from improved resolution and pre-condition to structure scheme propagation and substitute, and lately even to entire ML climate and climatology predictive models. Linear Structural Equation Models (LSES) have been used, employed and mastered, that for the timed which exceeded 25 years that towards this point have remained dormant. Rather more intensive progress of this domain of knowledge has been observed during the last decade. While proceeding entirely along this line of inquiry, it is most comfortable to use a critical approach in ML applications and the vicinity of weather and climate modelling, at least at the earlier stages.
Authors
- Goutham Deepu (ORCID: https://orcid.org/0009-0003-0305-2543)
- M Natesh
- S M Soumyasri
- J. Sudeep
- Ramakrishna Hegde (ORCID: https://orcid.org/0000-0001-7121-5648)
- S Shivashankara
Institutions
- Visvesvaraya Technological University (IN)
Publication Details
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1109/icraset63057.2024.10895739
- Primary Topic
- Air Quality Monitoring and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 0.00