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Observing the pre-convective environment and convection initiation with Doppler Lidar and cloud radar in the Al Hajar Mountains of the United Arab Emirates
- Source :
- Meteorologische Zeitschrift, Vol 31, Iss 2, Pp 149-170 (2022)
- Publication Year :
- 2022
- Publisher :
- Borntraeger, 2022.
-
Abstract
- In this study, we present multi-season measurements from a remote mountain peak observatory in the United Arab Emirates (UAE). During the campaign, Doppler lidar and cloud radar were employed using coordinated scan patterns, to study seedable convective clouds, and identify pre-convection initiation clear-air signatures. The instruments were employed for approximately two years in an extreme environment with a high vantage point for observing valley wind flows and convective cells. The instruments were configured to run synchronized plan position indicator (PPI) scans at 0°, 5°, and 45° elevation angles and vertical cross-section range height indicator (RHI) scans at 0°, 30°, 60°, 90°, 120°, and 150° azimuth angles. Using this output imagery, along with local C‑band radar and satellite data, we were able to identify and analyse several convective cases. To illustrate this synergy of measurements, we present two cases in unstable conditions – the 5 and 6 September 2018. In both cases, we observed areas of convergence/divergence to the south-west of the observatory, associated with wind flow around a peak 2 km to the south-west. The extension of these deformations were visible in the atmosphere as high as 3 km above sea level. Subsequently, we observed convective cells developing in the same directions – apparently connected with these phenomena. The cloud radar Doppler images provided detailed observations of cloud hydrometeor dynamics. In both convective cases, pre-convective signatures were apparent before CI, in the form of convergence, wind shear structures, and updrafts. These results demonstrate the potential of these synergetic observations for understanding convection initiation processes and in the future, to provide cloud seeding guidance via early detection of CI events.
Details
- Language :
- English
- ISSN :
- 09412948
- Volume :
- 31
- Issue :
- 2
- Database :
- Directory of Open Access Journals
- Journal :
- Meteorologische Zeitschrift
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.b95967cfab074e4686841b6898cb8ef7
- Document Type :
- article
- Full Text :
- https://doi.org/10.1127/metz/2021/1100