Deep Learning Algorithms for Weather Forecasting and Climate Prediction

Dear Colleagues,

Human society and natural ecosystems are vulnerable to weather and climate change, which have considerable impacts. Therefore, there is an urgent need for useful and credible information for weather and climate services. In recent years, deep learning is widely used in meteorological research and have made great progress in tasks such as weather forecasting and climate prediction. However, deep learning still has two problems: the first is the poor generalization ability of models, which often underestimate or even miss extreme events, and the second is the lack of physical consistency, weak interpretability, and poor credibility of "black box" models. Recent advances such as graph convolutional networks, attention mechanisms, and full residual encoder–decoders have helped to enhance learning using limited samples, reducing overfitting and bias. In addition, introducing a priori physical knowledge in deep learning models by designing special network structures or loss functions can improve the forecasting skill and interpretability of AI.

This Special Issue aims to promote the publication of original research and reviews that focus on deep learning algorithms for weather forecasting and climate prediction. Submissions are welcome covering a wide range of topics, including, but not limited to:

1. the application of deep learning in climate prediction;
2. the application of deep learning in weather forecasting, such as NAO, tropical cyclone, precipitation, etc;
3. the comparison of different methods to illustrate the effectiveness of deep learning;
4. the interpretation of the models and results.

Dr. Shijin Yuan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• climate prediction
• severe weather forecasting
• spatio-temporal data analysis
• artificial intelligence and its interpretability
• machine learning
• intelligent algorithm development
• data assimilation