Knippertz, Peter
Marsham, John H
Benedetti, Angela
Evans, Mat J
Fink, Andreas H
Kniffka, Anke
van der Linden, Roderick
Dearden, Christopher
Deetz, Konrad
Haslett, Sophie L
Keita, Sekou
Lohou, Fabienne
Maranan, Marlon
Mollard, James D. P.
Pante, Gregor
Reinares Martínez, Irene
Young, Matthew
Akpo, Aristide
Adler, Bianca
Amekudzi, Leonard
Babić, Karmen
Chaboureau, Jean-Pierre
Chiu, J. Christine
Coe, Hugh
Dione, Cheikh
Leal-Liousse, Catherine
Hill, Peter
Kalthoff, Norbert
Vogel, Bernhard
Yoboué, Véronique
2020-07-23
<p>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. </p>
https://doi.org/10.5281/zenodo.3957318
oai:zenodo.org:3957318
eng
Zenodo
https://doi.org/10.6096/dacciwa.1618
https://doi.org/10.6096/dacciwa.1686
https://doi.org/10.6096/ dacciwa.1702
https://doi.org/10.6096/dacciwa.1690
https://doi.org/10.6096/dacciwa.1659
https://doi.org/10.6096/dacciwa.1663
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.3957317
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
West Africa, weather, climate, air pollution, prediction, numerical weather prediction models, satellite data, field campaign
Key lessons from the DACCIWA project for operational meteorological services
info:eu-repo/semantics/report