Analog Forecasting of Extreme‐Causing Weather Patterns Using Deep Learning
Abstract Numerical weather prediction models require ever‐growing computing time and resources but, still, have sometimes difficulties with predicting weather extremes. We introduce a data‐driven framework that is based on analog forecasting (prediction using past similar patterns) and employs a nov...
Main Authors: | Ashesh Chattopadhyay, Ebrahim Nabizadeh, Pedram Hassanzadeh |
---|---|
Format: | Article |
Language: | English |
Published: |
American Geophysical Union (AGU)
2020-02-01
|
Series: | Journal of Advances in Modeling Earth Systems |
Subjects: | |
Online Access: | https://doi.org/10.1029/2019MS001958 |
Similar Items
-
Evaluating South African Weather Service information on Idai tropical cyclone and KwaZulu-Natal flood events
by: Mary-Jane M. Bopape, et al.
Published: (2021-03-01) -
WWOSC 2014: Research Needs for Better Health Resilience to Weather Hazards
by: Michel Jancloes, et al.
Published: (2015-03-01) -
Survey on the Application of Deep Learning in Extreme Weather Prediction
by: Wei Fang, et al.
Published: (2021-05-01) -
Summary of a workshop on extreme weather events in a warming world organized by the Royal Swedish Academy of Sciences
by: Deliang Chen, et al.
Published: (2020-01-01) -
Crop Diversification in Coping with Extreme Weather Events in China
by: Ji-kun HUANG, et al.
Published: (2014-04-01)