Back to Search
Start Over
Prediction of cloud fractional cover using machine learning
- Source :
- Big Data and Cognitive Computing, Volume 5, Issue 4, Big Data and Cognitive Computing, Vol 5, Iss 62, p 62 (2021)
- Publication Year :
- 2021
- Publisher :
- MDPI, 2021.
-
Abstract
- Climate change is stated as one of the largest issues of our time, resulting in many unwanted effects on life on earth. Cloud fractional cover (CFC), the portion of the sky covered by clouds, might affect global warming and different other aspects of human society such as agriculture and solar energy production. It is therefore important to improve the projection of future CFC, which is usually projected using numerical climate methods. In this paper, we explore the potential of using machine learning as part of a statistical downscaling framework to project future CFC. We are not aware of any other research that has explored this. We evaluated the potential of two different methods, a convolutional long short-term memory model (ConvLSTM) and a multiple regression equation, to predict CFC from other environmental variables. The predictions were associated with much uncertainty indicating that there might not be much information in the environmental variables used in the study to predict CFC. Overall the regression equation performed the best, but the ConvLSTM was the better performing model along some coastal and mountain areas. All aspects of the research analyses are explained including data preparation, model development, ML training, performance evaluation and visualization.
- Subjects :
- Technology
Computer science
Climate change
Cloud computing
Machine learning
computer.software_genre
VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420
Management Information Systems
VDP::Mathematics and natural science: 400::Information and communication science: 420
Artificial Intelligence
Climate science
Projection (set theory)
statistical downscaling
Statistical downscaling
business.industry
climate science
Deep learning
Global warming
deep learning
Regression analysis
Cloud fractional covers
Computer Science Applications
machine learning
cloud fractional cover
Memory model
Artificial intelligence
business
computer
Information Systems
Downscaling
Subjects
Details
- Language :
- English
- ISSN :
- 25042289
- Database :
- OpenAIRE
- Journal :
- Big Data and Cognitive Computing, Volume 5, Issue 4, Big Data and Cognitive Computing, Vol 5, Iss 62, p 62 (2021)
- Accession number :
- edsair.doi.dedup.....ca290474234849a13527c5e6cca82a0b