Automated time–height-resolved air mass source attribution for profiling remote sensing applications

Abstract

Abstract. Height-resolved air mass source attribution is crucial for the evaluation of profiling ground-based remote sensing observations, especially when using lidar (light detection and ranging) to investigate different aerosol types throughout the atmosphere. Lidar networks, such as EARLINET (European Aerosol Research Lidar Network) in the frame of ACTRIS (Aerosol, Clouds and Trace Gases), observe profiles of optical aerosol properties almost continuously, but usually, additional information is needed to support the characterization of the observed particles. This work presents an approach explaining how backward trajectories or particle positions from a dispersion model can be combined with geographical information (a land cover classification and manually defined areas) to obtain a continuous and vertically resolved estimate of an air mass source above a certain location. Ideally, such an estimate depends on as few as possible a priori information and auxiliary data. An automated framework for the computation of such an air mass source is presented, and two applications are described. First, the air mass source information is used for the interpretation of air mass sources for three case studies with lidar observations from Limassol (Cyprus), Punta Arenas (Chile) and ship-borne off Cabo Verde. Second, air mass source statistics are calculated for two multi-week campaigns to assess potential observation biases of lidar-based aerosol statistics. Such an automated approach is a valuable tool for the analysis of short-term campaigns but also for long-term data sets, for example, acquired by EARLINET.

Californian Wildfire Smoke Over Europe: A First Example of the Aerosol Observing Capabilities of Aeolus Compared to Ground‐Based Lidar

“…The time-height cross-section of airmass source (Figure 3, Radenz et al, 2021) generalizes the findings from the single time and height analysis as shown in Figure 2. Air parcel positions are calculated every 3 h and for height intervals of 500 m. At each step, the residence time is summed up for each region, whenever particles were below the reception height during the backward simulation.…”

Contrasting ice formation in Arctic clouds: surface-coupled vs. surface-decoupled clouds

“…An enhanced fraction of ice-containing clouds could be attributed to blowing snow as on the one hand, the lifted snow can be interpreted by the lidar as an ice cloud. On the other hand blowing snow particles can act as seeds for ice crystals via the secondary ice multiplication processes (Rogers and Vali, 1987). Yet, an influence of blowing snow on the results can be ruled out.…”

Hemispheric contrasts in ice formation in stratiform mixed-phase clouds: Disentangling the role of aerosol and dynamics with ground-based remote sensing

“…The free troposphere is dominated by marine aerosol from the Southern Ocean and was reported to show no changes compared to the pre-industrial conditions (Hamilton et al, 2014). Nevertheless, events of aerosol long-range transport also occur occasionally (Foth et al, 2019;Floutsi et al, 2021). The boundary layer is laden with a mixture of marine and continental aerosol, as Punta Arenas is located 230 km inland from the Pacific coast.…”

“…Hence, the free tropospheric aerosol is predominantly of marine origin with low concentrations overall. First results of the DACAPO-PESO campaign regarding events of significant aerosol load (Ohneiser et al, 2020;Floutsi et al, 2021), liquid cloud microphysics (Jimenez et al, 2020) and integrated water vapor observations (Bromwich et al, 2020) are already published. Observations at Leipzig were performed before October 2016 and between the deployments to Limassol and Punta Arenas.…”