Recent Advances on Weather and Climate Simulation and Prediction
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Air, Climate Change and Sustainability".
Deadline for manuscript submissions: 10 August 2027 | Viewed by 28
Editors
Interests: numerical weather and climate modeling/prediction; impact of climate changes on weather extremes; air quality modeling and prediction; satellite and radar data assimilation; machine learning in atmospheric science; radar-based nowcasting; wind and solar energy forecasting; tropical cyclones prediction
Special Issues, Collections and Topics in MDPI journals
Interests: probabilistic forecasting and the translation of weather-related uncertainty into operational risk for utilities and power markets; grounded in numerical weather prediction and physics-informed machine learning methods; climate risk and wildfire modeling; risk assessment for critical infrastructure and grid resilience under extreme weather; decision-relevant forecasting bridging atmospheric prediction and real-world action; the integration of weather intelligence into energy trading; portfolio management; renewable energy integration
Interests: regional weather and climate modelling; data assimilation; weather and climate extremes; indian monsoons
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Weather and climate simulation are undergoing significant transformation, driven by high-resolution numerical modeling and the rapid emergence of machine learning (ML)-based approaches. Increased computational capacity has enabled convection-permitting, kilometer-scale simulations that explicitly resolve processes such as deep convection, orographic forcing, and land–atmosphere interactions, substantially improving the representation of severe weather and local-scale variability. In parallel, ML-based global and regional forecasting systems now approach or exceed traditional NWP performance at a fraction of the computational cost, while ML-driven super-resolution methods bridge coarse model output and the fine scales needed for regional applications. These advances also carry direct implications for renewable energy systems, which depend on accurate wind, solar, and hydrological forecasts for grid integration and market operations.
This Special Issue invites original research and review articles across the following themes:
- High-Resolution Weather Modeling — convection-permitting and kilometer-scale NWP, model dynamics, and physical parameterizations.
- ML-Based High-Resolution Weather Modeling — foundation, diffusion-based, and transformer architectures for high-resolution prediction, compared with traditional NWP.
- ML-Based Climate Modeling — machine learning methods for global and regional climate simulation.
- Super-Resolution — statistical and generative ML techniques bridging coarse and fine-scale model output.
- Data Assimilation — integrating observational and remote sensing data to improve initial conditions and forecast accuracy.
- Renewable Energy Prediction — wind, solar, and hydropower forecasting, including uncertainty quantification for grid integration and markets.
Dr. Chandrasekar Radhakrishnan
Dr. Tyler McCandless
Dr. Attada Raju
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly 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
- high-resolution numerical weather prediction
- convection-permitting modeling
- machine learning weather forecasting
- AI-based climate modeling
- super-resolution downscaling
- data assimilation
- renewable energy forecasting
- severe weather prediction
- ensemble forecasting
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