Challenges in Weather and Climate Modeling: Model Development, Verification, and Perspectives

Dear Colleagues,

Challenges in Weather and Climate Modeling: Model Development, Verification, and Perspectives" aims to investigate the characteristics (e.g., suitability of numerical schemes, effective resolution) of Numerical Weather Prediction (NWP) and climate modeling (CM) systems, as well as the rules and evaluation criteria for these modeling systems. Additionally, this Special Issue intends to explore the potential role of machine learning (ML) and artificial intelligence (AI) methods in complimenting the conventional models or improving on the limitations of the conventional models and the impact of the characteristics of the meteorological models on the impact models (e.g., hydrology, agriculture, energy, etc.) that they are used to drive.

The topics include:

• The characteristics (e.g., numerical schemes, effective resolution, etc.) of the modeling system that make them suitable for a fifty-hour simulation versus a fifty-year simulation.
• The implications of a climate modeling system not capturing the morning minimum and afternoon maximum temperatures within the boundary layer.
• The possibility or otherwise (including the implications) of a climate modeling system obtaining a reasonable monthly mean while failing to simulate the diurnal cycle.
• The rules and evaluation criteria for NWP and climate modeling systems from both model development and model output perspectives.
• The implications of the characteristics (e.g., numerical schemes, effective resolution, etc.) of weather and climate modeling systems on impact models that use the meteorological output as input.
• Convection-permitting models and ensembles.
• The role (including strengths and weaknesses) of AI and ML approaches in generating weather and climate information particularly, at the community or sub-national scale.

Overall, this Special Issue welcomes submissions about the challenges and perspectives in Numerical Weather Prediction and climate modeling systems and the provision of weather and climate information for climate resilience.

Dr. Benjamin Lantei Lamptey
Dr. Lai Yung Ruby Leung
Dr. Jason Hickey
Guest Editors

Manuscript Submission Information

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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.

• weather and climate modeling systems
• model development
• model verification
• machine learning
• artificial intelligence
• impact models
• climate resilience
• convection-permitting models
• ensembles