Automated time-height-resolved airmass source attribution for profiling remote sensing applications

Abstract

Abstract. Height resolved airmass source attribution is crucial for the evaluation of profiling ground-based remote sensing observations. This work presents an approach 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 airmass 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 airmass source is presented and two exemplary applications are described. Firstly, the airmass source information is used for the interpretation of airmass sources for three case studies with lidar observations from Limassol (Cyprus), Punta Arenas (Chile) and ship-borne off Cabo Verde. Secondly, airmass source statistics are calculated for two 8-week campaigns to assess potential observation biases of lidar-based aerosol statistics.

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.…”

Advection of Biomass Burning Aerosols towards the Southern Hemispheric Mid-Latitude Station of Punta Arenas as Observed with Multiwavelength Polarization Raman Lidar

“…HYS-PLIT model calculates backward and forward trajectories of air masses for simulations of dispersion and deposition at a given location. In order to identify the aerosol sources and to create some statistical basis of the aerosol conditions during DACAPO-PESO, we used ensemble backward trajectories combined with a land cover classification for a temporally and vertically resolved air mass source attribution TRACE [30,31]. A simplified version of the MODIS land cover [32] is used.…”