<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Key lessons from the DACCIWA project for operational meteorological services

descriptionPublicationkeyboard_double_arrow_right Report , Book , Other literature type 01 Jul 2020 Germany English Publisher:ZenodoFunded by:EC | DACCIWA

Authors: Knippertz, Peter; Marsham, John H; Benedetti, Angela; Evans, Mat J; Fink, Andreas H; Kniffka, Anke; van der Linden, Roderick; +23 Authors

doi: 10.5281/zenodo.3957318 , 10.5281/zenodo.3957317

Key lessons from the DACCIWA project for operational meteorological services

- Summary
- Subjects
- Metrics

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.

Country

Germany

Related Organizations

French National Centre for Scientific Research
France
University of Reading
United Kingdom
Karlsruhe Institute of Technology
Germany
Kwame Nkrumah University of Science and Technology
Ghana
University of Leeds
United Kingdom

View all View all

Keywords

info:eu-repo/classification/ddc/000, 550, 000, ddc:000, air pollution, information & general works, prediction, life_on_land, sustainable_cities_and_communities, Computer science, numerical weather prediction models, West Africa, weather, climate, air pollution, prediction, numerical weather prediction models, satellite data, field campaign, weather, West Africa, field campaign, climate, satellite data, good_health_and_well_being, climate_action, affordable_and_clean_energy

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	1
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average