The State of the Art in Climate Predictions

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Background

Climate variability originating from tropical and extratropical regions has large impacts on the human population, infrastructures and the global environment. Huge socio-economic losses are witnessed all over the world during some of the recently observed extreme events often associated with those climate phenomena. Over the years, the underlying processes have been investigated and prediction systems developed to design and implement effective mitigation measures. Considering the past and present progresses in this area of research and application, we propose this special collection to review those progresses and discuss the present state of climate prediction systems based on general circulation models as well as statistical models that are used to predict climate variability in tropical and extratropical regions, and their global teleconnections.

The developments in climate modeling and prediction systems have rapidly advanced in the last couple of decades. To keep us updated on these advancements we plan to review those progresses that provided the base for the present state of the climate prediction systems. Rapid evolutions in the computational as well as data sciences have provided the scope to present generation of climate prediction systems for further developments and skill improvements. Hence, we also aim to discuss scopes of some of those in the prediction systems and their implementations in present generation of the climate models, which would benefit the climate research community as well as young students aspiring to develop their careers in the field of climate variability and predictability.

Research articles as well review articles are invited for the following topics:
• Modeling and intra-seasonal to interannual predictability studies, including model intercomparisons, of tropical and extra-tropical climate variations (such as El Nino/Southern Oscillation, Indian Ocean dipole, Indian summer monsoon, Asian monsoon, Atlantic Nino, meridional modes etc.) and their teleconnections.
• Current state of model initializations including artificial intelligence/machine learning (AI/ML).
• Progresses in model parameterizations (e.g., convective parameterizations, ocean mixing etc.) including the use of AI/ML in those parametrizations.
• Model bias corrections.
• Progresses in decadal and longer-term climate predictions.
• Progresses in sea-ice and polar climate predictions.
• Evaluation of prediction systems.

Keywords: sea-ice, polar climate predictions, model bias corrections, climate variability, El Nino

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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