Key lessons from the DACCIWA project for operational meteorological services
Knippertz, Peter
1; Marsham, John H.; Benedetti, Angela; Evans, Mat J.; Fink, Andreas H.
1; Kniffka, Anke 1; van der Linden, Roderick 1; Dearden, Christopher; Deetz, Konrad 1; Haslett, Sophie L.; Keita, Sekou; Lohou, Fabienne; Maranan, Marlon; Mollard, James D. P.; Pante, Gregor 1; Reinares Martínez, Irene; Young, Matthew; Akpo, Aristide; Adler, Bianca 1;
1; Marsham, John H.; Benedetti, Angela; Evans, Mat J.; Fink, Andreas H.
1; Kniffka, Anke 1; van der Linden, Roderick 1; Dearden, Christopher; Deetz, Konrad 1; Haslett, Sophie L.; Keita, Sekou; Lohou, Fabienne; Maranan, Marlon; Mollard, James D. P.; Pante, Gregor 1; Reinares Martínez, Irene; Young, Matthew; Akpo, Aristide; Adler, Bianca 1; Abstract:
This document describes the conclusions of the EU-funded project Dynamics- Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) directly relevant to operational meteorological services. DACCIWA produced the most comprehensive observational dataset of the atmosphere over densely populated southern West Africa to date and used this dataset to foster our understanding of atmospheric processes, and to evaluate dynamical models and satellite data. With this document DACCIWA aims to help improve atmospheric predictions across time-scales, which are important for the development of greater resilience of the West African population to hazardous weather and climate change.
| Zugehörige Institution(en) am KIT | Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO) |
| Publikationstyp | Forschungsdaten |
| Publikationsjahr | 2020 |
| Identifikator | KITopen-ID: 1000178171 |
| Lizenz | Creative Commons Namensnennung 4.0 International |
| Schlagwörter | West Africa, weather, climate, air pollution, prediction, numerical weather prediction models, satellite data, field campaign |
| Nachgewiesen in | OpenAlex |
| Globale Ziele für nachhaltige Entwicklung |