Applications of Artificial Intelligence in Atmospheric Sciences

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 86

Special Issue Editors


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Guest Editor
Surrey Institute for People-Centred AI and Global Centre for Clean Air Research (GCARE), Institute for Sustainability, School of Computer Science and Electronic Engineering, University of Surrey, Guildford GU2 7XH, UK
Interests: smart buildings; smart homes; indoor air quality; airborne dispersion; nature-based solutions; low-cost sensors; air monitoring; big data; artificial intelligence; computational modeling
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Sanitary and Environmental Engineering, Federal University of Minas Gerais. Av. Antônio Carlos, 6.627, Belo Horizonte 31270-901, MG, Brazil
Interests: air pollution; air particulate matter; air quality; air quality modeling; air pollution control and modeling applications
Special Issues, Collections and Topics in MDPI journals

grade E-Mail Website
Guest Editor
Global Center for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Surrey GU2 7XH, UK
Interests: low-cost sensing; air pollution modelling; pollution mitigation; atmospheric science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Current state-of-the-art (SOTA) atmospheric models, such as numerical weather prediction (NWP) models, usually require large computing power since they rely on complex physical equations and parametrisations to simulate and understand spatiotemporal atmospheric phenomena. Currently, artificial intelligence (AI) techniques are used for this purpose with improved forecasting performance, but with a fraction of the computational cost of traditional techniques, leveraging large volumes of historical atmospheric data and advanced AI techniques to build atmospheric models for different spatiotemporal scales. In fact, even world-leading weather agencies, such as the MetOffice in the UK and the European Centre for Medium-Range Weather Forecasts (ECMWF), are developing AI solutions to improve atmospheric modelling performance, presenting competitive performance with SOTA NWP.

Therefore, this Special Issue aims to explore the intersection of AI and atmospheric sciences to tackle pressing challenges in climate change, weather forecasting, clean air, and renewable energy, among others, providing a platform for researchers to showcase cutting-edge research and to foster the development and adoption of AI solutions to address key challenges in atmospheric sciences, with the potential to help achieve the United Nation’s Sustainable Development Goals (UNSDG) 3, 7, 11, and 13. Authors are invited to submit original research articles and reviews that highlight the transformative potential of novel AI techniques in various aspects of atmospheric sciences, including (but not limited to) the following:

  • Weather and extreme weather event forecasting;
  • Air pollution monitoring, management, and forecasting;
  • Renewable energy prediction and optimisation;
  • Regional downscaling;
  • Physics-informed neural networks to simulate atmospheric flow;
  • Foundation models for atmospheric challenges;
  • Climate change and resilience;
  • Indoor and outdoor modelling;
  • The airborne dispersion of contaminants and their impact on indoor and outdoor environments;
  • The inventory estimation of emissions;
  • Land use change assessment;
  • Impacts of air quality on human health;
  • Other related areas.

Dr. Erick G. Sperandio Nascimento
Dr. Taciana Toledo De Almeida Albuquerque
Prof. Dr. Prashant Kumar
Guest Editors

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.

Keywords

  • artificial intelligence
  • atmospheric science
  • machine learning
  • deep learning
  • climate change
  • air pollution
  • clean air
  • renewable energy
  • clean energy
  • weather
  • extreme weather
  • physics-informed neural networks

Published Papers

This special issue is now open for submission.
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