High-resolution rainfall maps from commercial microwave links for a data-scarce region in West Africa

  • We present high-resolution rainfall maps from commercial microwave link (CML) data in the city of Ouagadougou, Burkina Faso. Rainfall was quantified based on data from 100 CMLs along unique paths and interpolated to achieve rainfall maps with a 5-min temporal and 0.55-km spatial resolution for the monsoon season of 2020. Established processing methods were combined with newly developed filtering methods, minimizing the loss of data availability. The rainfall maps were analyzed qualitatively both at a 5-min and aggregated daily scales. We observed high spatiotemporal variability on the 5-min scale that cannot be captured with any existing measurement infrastructure in West Africa. For the quantitative evaluation, only one rain gauge with a daily resolution was available. Comparing the gauge data with the corresponding CML rainfall map pixel showed a high agreement, with a Pearson correlation coefficient > 0.95 and an underestimation of the CML rainfall maps of ∼10%. Because the CMLsWe present high-resolution rainfall maps from commercial microwave link (CML) data in the city of Ouagadougou, Burkina Faso. Rainfall was quantified based on data from 100 CMLs along unique paths and interpolated to achieve rainfall maps with a 5-min temporal and 0.55-km spatial resolution for the monsoon season of 2020. Established processing methods were combined with newly developed filtering methods, minimizing the loss of data availability. The rainfall maps were analyzed qualitatively both at a 5-min and aggregated daily scales. We observed high spatiotemporal variability on the 5-min scale that cannot be captured with any existing measurement infrastructure in West Africa. For the quantitative evaluation, only one rain gauge with a daily resolution was available. Comparing the gauge data with the corresponding CML rainfall map pixel showed a high agreement, with a Pearson correlation coefficient > 0.95 and an underestimation of the CML rainfall maps of ∼10%. Because the CMLs closest to the gauge have the largest influence on the map pixel at the gauge location, we thinned out the CML network around the rain gauge synthetically in several steps and repeated the interpolation. The performance of these rainfall maps dropped only when a radius of 5 km was reached and approximately one-half of all CMLs were removed. We further compared ERA5 and GPM IMERG data with the rain gauge and found that they had much lower correlation than data from the CML rainfall maps. This clearly highlights the large benefit that CML data can provide in the data-scarce but densely populated African cities.show moreshow less

Download full text files

Export metadata

Statistics

Number of document requests

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Moumouni Djibo, Christian ChwalaORCiDGND, Maximilian GrafORCiDGND, Julius Polz, Harald KunstmannORCiDGND, François Zougmoré
URN:urn:nbn:de:bvb:384-opus4-1097130
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/109713
ISSN:1525-755XOPAC
ISSN:1525-7541OPAC
Parent Title (English):Journal of Hydrometeorology
Publisher:American Meteorological Society
Place of publication:Boston, MA
Type:Article
Language:English
Year of first Publication:2023
Publishing Institution:Universität Augsburg
Release Date:2023/12/05
Tag:Atmospheric Science
Volume:24
Issue:10
First Page:1847
Last Page:1861
DOI:https://doi.org/10.1175/jhm-d-23-0015.1
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Geographie
Fakultät für Angewandte Informatik / Institut für Geographie / Lehrstuhl für Regionales Klima und Hydrologie
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)