05 Oct 2022
05 Oct 2022
Status: this preprint is currently under review for the journal AMT.

The Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations

Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn Heike Kalesse-Los et al.
  • Leipzig Institute for Meteorology (LIM), University of Leipzig, Leipzig, Germany

Abstract. Combined continuous long-term ground-based remote-sensing observations with vertically pointing cloud radar and ceilometer are well-suited to identify precipitation evaporation fall streaks (so-called virga). Here we introduce the functionality and workflow of a new open-source tool, the Virga-Sniffer which was developed within the frame of RV Meteor observations during the ElUcidating the RolE of Cloud–Circulation Coupling in ClimAte (EUREC4A) field experiment in Jan–Feb 2020 in the Tropical Western Atlantic. The Virga-Sniffer Python package is highly modular and configurable and can be applied to multilayer cloud situations. In the simplest approach, it detects virga from time-height fields of cloud radar reflectivity and time series of ceilometer cloud base height. In addition, optional parameters like lifting condensation level, a surface rain flag as well as time-height fields of cloud radar mean Doppler velocity can be added to refine virga event identifications. The netcdf-output files consist of Boolean flags of virga- and cloud detection, as well as base- and top heights and depth for the detected clouds and virga. The performance of the Virga-Sniffer was assessed by comparing its results to the Cloudnet target classification resulting from using the CloudnetPy processing chain. 88 % of the pixel identified as virga by the Virga Sniffer correspond to Cloudnet classifications of precipitation. The remaining 12 % of virga pixel correspond to Cloudnet-classifications of aerosols and insects (about 7 %), cloud droplets (3 %), or clear-sky (about 1 %). Some discrepancies of the virga identification and the Cloudnet target classification can be attributed to applied temporal smoothing. Additionally, it was found that Cloudnet mostly classified aerosols and insects at virga edges which points to a misclassification caused by CloudnetPy internal thresholds. For the RV Meteor observations during EUREC4A, about 50 % of all detected clouds with bases below the trade inversion were found to produce precipitation that evaporates before reaching the ground. The most important virga-producing clouds were either anvils of convective cells or stratocumulus clouds. 36 % of the detected virga originated from trade wind cumuli. Small virga with depths below 200 m most frequently occurred from shallow clouds with depths below 500 m, while virga depths above 1 km were mainly associated with clouds of larger depths, ranging between 500 and 1000 m. Virga depth showed no strong dependency on column-integrated liquid water path. The presented results substantiate the importance of low-level precipitation evaporation in the Atlantic lower winter trades. Possible applications of the Virga-Sniffer within the frame of EUREC4A include detailed studies of precipitation evaporation with a focus on cold pools or cloud organization, or distinguishing moist processes based on water vapor isotopic observations. However, we envision extended use of the Virga-Sniffer for other cloud regimes or scientific foci as well.

Heike Kalesse-Los et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-252', Raphaela Vogel, 07 Nov 2022
  • RC2: 'Comment on amt-2022-252', Anonymous Referee #2, 14 Nov 2022
  • RC3: 'Comment on amt-2022-252', Anonymous Referee #3, 17 Nov 2022

Heike Kalesse-Los et al.

Heike Kalesse-Los et al.


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Short summary
The Virga-Sniffer, a new modular open-source Python package tool to characterize precipitation evaporation (so-called virga) from ceilometer cloud base height and vertically-pointing cloud radar reflectivity time-height fields is described. Results of its first application to RV Meteor observations during the EUREC4A field experiment in Jan–Feb 2020 are shown. About half of all detected clouds with bases below the trade inversion height were found to produce virga.