Measuring and modelling directional effects in the frame of TIRAMISU (Thermal InfraRed Anisotropy Measurements in India and Southern eUrope)

Low-cost optical particle counters (OPCs) offer new opportunities to monitor dust particles from wind soil erosion. Their price, size, and power consumption are lower than those of traditional OPCs. We tested the ability of the low-cost OPC-N3 from Alphasense to estimate dust emission flux during erosion events in Jordan. N3 estimated the dust flux well, with differences of less than 30 % compared to a traditional OPC. Our results confirm the potential of low-cost OPCs for dust erosion research.

Mineral dust particles emitted from dry soils are of various sizes, yet the abundance of very large particles is not well understood. Here we measured the dust size distribution from fine to giant particles at an emission source during a field campaign in Jordan (J-WADI) using multiple instruments. Our findings show that large particles make up a significant part of the total dust mass. This knowledge is essential to improve climate models and to predict dust impacts on climate and environment.

High-accuracy precision maps of the surface temperature of snow were acquired with an uncooled thermal-infrared camera during winter 2021–2022 and spring 2023. The accuracy – i.e., mean absolute error – improved from 1.28 K to 0.67 K between the seasons thanks to an improved camera setup and temperature stabilization. The dataset represents a major advance in the validation of satellite measurements and physical snow models over a complex topography.

We reviewed optical remote sensing time series (TS) studies for monitoring vegetation productivity across ecosystems. Methods were categorized into trend analysis, land surface phenology, and assimilation into statistical or dynamic vegetation models. Due to progress in machine learning, TS processing methods will diversify, while modelling strategies will advance towards holistic processing. We propose integrating methods into a digital twin to improve the understanding of vegetation dynamics.