Namib Fog Life Cycle Analysis (NaFoLiCA)
- Ansprechperson:
- Förderung:
Deutsche Forschungsgemeinschaft (DFG)
- Starttermin:
2016
- Endtermin:
2020
Overview
Fog is a central component of the Namib water cycle. Groups at KIT, as well as at the Universities of Basel and Bonn are aiming to improve the understanding of fog dynamics in the region in a three-year project, the Namib Fog Life Cycle Analysis (NaFoLiCA). The Basel group is in charge of field observations, Bonn performs numerical modeling, and we at KIT develop new techniques for the satellite remote sensing of fog in the region.
Project Summary from DFG GEPRIS:
Fog in the Namib region is an important source of water. The temporal and spatial patterns of fog occurrence are hitherto largely unknown due to absence of spatially continuous observations. Also, factors driving fog development in this coastal desert environment are not fully understood. The proposed project aims to use satellite data to characterize fog in the Namib region. This includes new developments of satellite algorithms as well as statistical analyses. In a first step, fog will be detected in satellite data, and its physical properties will be retrieved. Then, typical life cycles from fog formation to dissipation will be analyzed in this new data set. Finally, a statistical study employing information on meteorological and aerosol conditions will identify drivers of fog development.The proposed project is part of a project package that also includes ground-based observations and numerical weather prediction. Links with these component projects revolve around joining ground-based and satellite-based data for better process understanding, and using the model to constrain fog area and development mechanisms.
Field campaign September/October 2017
From 9 September to 9 October 2017 we conducted a fog measurement campaign in Namibia. Several fog events were analyzed via in-situ measurements as well as with ground-based remote sensing instrumentation. The data set collected in this way will be useful in improving satellite remote sensing of fog, as well as for numerical weather prediction.