- Titel
- Multi-section reference value for the analysis of horizontally scanning aerosol lidar observations
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa2-1018393
- Quellenangabe
- Atmospheric measurement techniques
Erscheinungsjahr: 2024
Jahrgang: 17
Seiten: 397-406
ISSN: 1867-1381
E-ISSN: 1867-8548 - Erstveröffentlichung
- 2024
- Abstract (EN)
- The quantitative analysis of measurements with horizontally scanning aerosol lidar instruments faces two major challenges: the background correction can be affected by abnormal signal peaks, and the choice of a reference ex- tinction coefficient αref is complicated if aerosols are ubiq- uitous in the sampled volume. Here, we present the newly developed multi-section method for the stable solution of ex- tinction coefficient retrievals from horizontally scanning li- dar measurements. The algorithm removes irregular peaks related to signal noise based on an experimentally derived fitting model. A representative value for αref is inferred from converging retrievals along different scan axes and over mul- tiple scans of 10 to 15 min under the assumption that they are only related to ambient aerosols without distinct emis- sion sources. Consequently, αref obtained through the multi- section method reflects typical atmospheric aerosols unaf- fected by emissions and noise. When comparing αref to the PM2.5 mass concentrations at national monitoring stations near the measurement area, a significant correlation with an r2 value exceeding 0.74 was observed. The presented case studies show that the new method allows for the retrieval and visualization of spatio-temporal aerosol distributions and subsequent products such as PM2.5 concentrations.
- Andere Ausgabe
- Erstveröffentlichung
DOI: 10.5194/amt-17-397-2024 - Freie Schlagwörter (EN)
- aerosol lidar observations, Multi-section reference
- Klassifikation (DDC)
- 550
- Verlag
- Copernicus Publications, Katlenburg-Lindau
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa2-1018393
- Veröffentlichungsdatum Qucosa
- 22.01.2026
- Dokumenttyp
- Artikel
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0