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Special Issue "Advanced Numerical Techniques for Modeling and Data Assimilation of Atmosphere and Oceans"
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".
Deadline for manuscript submissions: 30 November 2023 | Viewed by 1280
Special Issue Editors
Interests: numerical methods; modeling; data assimilation; machine learning/artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: extreme temperature events; precipitation; large-scale circulation and climate variability
Special Issue Information
This Special Issue explores “advanced” or “novel” numerical modeling and data assimilation techniques to assess weather, specifically the climate of the atmosphere and oceans. The aim is to provide a platform for presenting and testing new ideas and methods where authors will be able to express their creativity without restrictions and verifications so necessary for establishing scientific rigor. The regular process of creating, testing, and transitioning into operations of new ideas is often connected with practical limitations that can obstruct and discourage such creative efforts. The objective of this Special Issue is, therefore, to strongly encourage creative endeavors. We are looking for techniques that may bring challenges, but can potentially lead to fundamental breakthroughs, i.e., methods which are still in a relatively early experimental stage, but promise major advancements, and even paradigm shifts. The examples may include, but are not limited to:
- new approaches to quasi-uniform gridding of the sphere;
- unstructured and moving meshes;
- grid adaptation techniques;
- parallelization in time;
- exponential time integration;
- discontinuous Galerkin methods;
- nonlinear data assimilation;
- data assimilation techniques based on the non-Gaussian statistics;
- methods for improving preconditioning in variational data assimilation;
- ML/AI as emulation for standard techniques in weather forecasting and data assimilation;
- application of recent advancements in ML/AI, such as “next generation” of reservoir computing or deep learning clustering for modeling and data assimilation;
- multigrid techniques;
- evolutionary programing;
- application of quantum computing.
Dr. Miodrag Rancic
Dr. Ivana Tosic
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 2000 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.
- numerical methods
- weather and climate prediction
- data assimilation
- novel techniques and approaches
- emulations by machine learning and artificial intelligence