Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE
Ortega, P.; Blockley, E.W.; Køltzow, M.; Massonnet, F.; Sandu, I.; Svensson, G.; Acosta Navarro, J.C.; Arduini, G.; Batté, L.; Bazile, E.; Chevallier, M.; Cruz-García, R.; Day, J.J.; Fichefet, T.; Flocco, D.; Gupta, M.; Hartung, K.; Hawkins, E.; Hinrichs, C.; Magnusson, L.; Moreno-Chamarro, E.; Pérez-Montero, S.; Ponsoni, L.; Semmler, T.; Smith, D.; Sterlin, J.; Tjernström, M.; Välisuo, I.; Jung, T. (2022). Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE. Bull. Am. Meteorol. Soc. 103(10): E2203-E2213. https://dx.doi.org/10.1175/bams-d-22-0083.1
In: Bulletin of the American Meteorological Society. American Meteorological Society: Easton, Pa.. ISSN 0003-0007; e-ISSN 1520-0477, more
|   |
| Keyword |
|
| Author keywords |
Arctic; Sea ice; Climate prediction; Model initialization; Numerical weather prediction/forecasting |
| Authors | | Top |
- Ortega, P.
- Blockley, E.W.
- Køltzow, M.
- Massonnet, F., more
- Sandu, I.
- Svensson, G.
- Acosta Navarro, J.C.
- Arduini, G.
- Batté, L.
- Bazile, E.
|
- Chevallier, M.
- Cruz-García, R.
- Day, J.J.
- Fichefet, T., more
- Flocco, D.
- Gupta, M., more
- Hartung, K.
- Hawkins, E.
- Hinrichs, C.
- Magnusson, L.
|
- Moreno-Chamarro, E.
- Pérez-Montero, S.
- Ponsoni, L., more
- Semmler, T.
- Smith, D.
- Sterlin, J., more
- Tjernström, M.
- Välisuo, I.
- Jung, T.
|
| Abstract |
The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development. |
|
