Recent Advances in Subseasonal to Seasonal Predictability
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".
Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 1827
Special Issue Editors
Interests: sub seasonal to seasonal prediction; monsoons; climate change and variability; impact based weather forecasting and warnings, extreme weather events, and flood modeling; drought risk forecasts; machine learning methods for bias correction of forecast; air pollution studies and regional and global modelling; Indian summer monsoon
Interests: numerical weather prediction modeling; post-processing methods; machine learning techniques; climate change and climate variability; prediction of weather and climate extremes such as floods, droughts, heatwaves, cold waves, atmospheric rivers; subseasonal to seasonal predictions; monsoon dynamics; crop modeling; development of tools for climate risk management in various sectors like agriculture
Special Issue Information
Dear Colleagues,
We invite submissions to our upcoming issue, which will focus on recent advances in subseasonal to seasonal (S2S) predictability. This area of research is crucial for improving medium- to long-term forecasts that bridge the gap between weather and climate prediction. We seek original papers that explore innovative methodologies, modeling techniques, and case studies aimed at enhancing our understanding of S2S predictability. Topics of interest include but are not limited to the role of ocean-atmosphere interactions, teleconnections, and data assimilation. We also encourage papers that showcase the application of artificial intelligence and machine learning in enhancing forecast accuracy and reliability across the S2S time scale. We encourage studies on Impact-based Forecasting (IbF) that explore the application of S2S predictions in decision-making processes across various sectors, such as agriculture, water management, public health, and disaster preparedness. Emphasis should be placed on translating forecast data into actionable insights. Additionally, we welcome studies discussing operational challenges and practical applications in fields like agriculture, water management, and disaster preparedness. Lastly, we invite research from social science perspectives, examining the societal implications of S2S forecasts, including public perception, communication strategies, and the integration of social sciences into the development and dissemination of S2S forecasts.
This issue aims to foster interdisciplinary dialog and collaboration between atmospheric scientists, social scientists, and practitioners to enhance the utility and impact of S2S forecasts.
Submit your manuscript to contribute to this important and rapidly evolving field, helping to shape the future of predictive science and its application to real-world challenges.
Dr. Seshagiri Kolusu
Dr. Murali Nageswara Rao Malasala
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-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
- subseasonal to seasonal (S2S)
- numerical weather modeling
- impact based forecasting warnings
- post-processing methods including AI and ML
- social science perspectives
- multi-sectors
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