The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. We set up the ERA-PLANET Strand 4 project “iCUPE – integrative and Comprehensive Understanding on Polar Environments” to provide novel insights and observational data on global grand challenges with an Arctic focus. We utilize an integrated approach combining in situ observations, satellite remote sensing Earth observations (EOs), and multi-scale modeling to synthesize data from comprehensive long-term measurements, intensive campaigns, and satellites to deliver data products, metrics, and indicators to stakeholders concerning the environmental status, availability, and extraction of natural resources in the polar areas. The iCUPE work consists of thematic state-of-the-art research and the provision of novel data in atmospheric pollution, local sources and transboundary transport, the characterization of arctic surfaces and their changes, an assessment of the concentrations and impacts of heavy metals and persistent organic pollutants and their cycling, the quantification of emissions from natural resource extraction, and the validation and optimization of satellite Earth observation (EO) data streams. In this paper we introduce the iCUPE project and summarize initial results arising out of the integration of comprehensive in situ observations, satellite remote sensing, and multi-scale modeling in the Arctic context.

For atmospheric boundary-layer (ABL) studies, unmanned aircraft systems (UAS) can provide new information in addition to traditional in-situ measurements, or by ground- or satellite-based remote sensing techniques. The ability of fixed-wing UAS to transect the ABL in short time supplement ground-based measurements and the ability to extent the data horizontally and vertically allows manifold investigations. Thus, the measurements can provide many new possibilities for investigating the ABL. This study presents the new mark of the Multi-Purpose Airborne Sensor Carrier (MASC-3) for wind and turbulence measurements and describes the subsystems designed to improve the wind measurement, to gain endurance and to allow operations under an enlarged range of environmental conditions. The airframe, the capabilities of the autopilot Pixhawk 2.1, the sensor system and the data acquisition software, as well as the post-processing software, provide the basis for flight experiments and are described in detail. Two flights in a stable boundary-layer and a close comparison to a measurement tower and a Sodar system depict the accuracy of the wind speed and direction measurements, as well as the turbulence measurements. Mean values, variances, covariance, turbulent kinetic energy and the integral length scale agree well with measurements from a meteorological measurement tower. MASC-3 performs valuable measurements of stable boundary layers with high temporal resolution and supplements the measurements of meteorological towers and sodar systems.

The wind field in Arctic fjords is strongly influenced by glaciers, local orography and the interaction between sea and land. Ny-Ålesund, an important location for atmospheric research in the Arctic, is located in Kongsfjorden, a fjord with a complex local wind field that influences measurements in Ny-Ålesund. Using wind measurements from UAS (unmanned aircraft systems), ground measurements, radiosonde and reanalysis data, characteristic processes that determine the wind field around Ny-Ålesund are identified and analysed. UAS measurements and ground measurements show, as did previous studies, a south-east flow along Kongsfjorden, dominating the wind conditions in Ny-Ålesund. The wind measured by the UAS in a valley 1 km west of Ny-Ålesund differs from the wind measured at the ground in Ny-Ålesund. In this valley, we identify a small-scale catabatic flow from the south to south-west as the cause for this difference. Case studies show a backing (counterclockwise rotation with increasing altitude) of the wind direction close to the ground. A katabatic flow is measured near the ground, with a horizontal wind speed up to 5 m s-1. Both the larger-scale south-east flow along the fjord and the local katabatic flows lead to a highly variable wind field, so ground measurements and weather models alone give an incomplete picture. The comparison of UAS measurements, ground measurements and weather conditions analysis using a synoptic model is used to show that the effects measured in the case studies play a role in the Ny-Ålesund wind field in spring.

Atmospheric aerosols affect human health and influence atmospheric and biological processes. Dust can be transported long distances in the atmosphere, and the mechanisms that influence dust transport are not fully understood. To improve the database for numerical models that simulate dust transport, measurements are needed that cover both the vertical distribution of the dust and its size distribution. In addition to measurements with crewed aircraft, uncrewed aircraft systems (UASs) provide a particularly suitable platform for this purpose. In this paper, we present a payload for the small fixed-wing UAS of the type Multiple-Purpose Airborne Sensor Carrier 3 (MASC-3) for aerosol particle measurements that is based on the optical particle counter (OPC) OPC-N3 (Alphasense, United Kingdom), modified by the addition of a dryer and a passive aspiration system (OPC-Pod). Based on field tests with a reference instrument in Mannheim, Germany, wind tunnel tests, and a comparison measurement with the UAS-mounted aerosol particle measurement Universal Cloud and Aerosol Sounding System (UCASS) during a dust event over Cyprus, we show that the OPC-Pod can measure particle number concentrations in the range of 0.66–31 μm as well as particle size distributions. The agreement of the OPC-Pod with UCASS is good. Both instruments resolve a vertical profile of the Saharan dust event, with a prominent dust layer between 1500 and 2800 m MSL, with particle number concentrations up to 35 cm⁻³ for particles between 0.66 and 31 μm.

This investigation presents a modelling strategy for wind-energy studies in complex terrains using computational fluid dynamics (CFD). A model, based on an unsteady Reynolds Averaged Navier-Stokes (URANS) approach with a modified version of the standard k-ε model, is applied. A validation study based on the Leipzig experiment shows the ability of the model to simulate atmospheric boundary layer characteristics such as the Coriolis force and shallow boundary layer. By combining the results of the model and a design of experiments (DoE) method, we could determine the degree to which the slope, the leaf area index, and the forest height of an escarpment have an effect on the horizontal velocity, the flow inclination angle, and the turbulent kinetic energy at critical positions. The DoE study shows that the primary contributor at a turbine-relevant height is the slope of the escarpment. In the second step, the method is extended to the WINSENT test site. The model is compared with measurements from an unmanned aircraft system (UAS). We show the potential of the methodology and the satisfactory results of our model in depicting some interesting flow features. The results indicate that the wakes with high turbulence levels downstream of the escarpment are likely to impact the rotor blade of future wind turbines.

The Weather Research and Forecasting (WRF) Model has been coupled with a URANS Model to simulate the passage of a cold front over the WINSENT site, a wind energy test-site under development. It is located on a hill near a steep, forested terrain edge. A high spatial resolution is necessary to simulate the flow over this complex site accurately for which reason the WRF model is run at high resolution in LES mode coupled to a URANS model with an even higher resolution. A forest parametrization is implemented in both models to account for the drag caused by the trees. The main result is that the WRF model without forest parametrization overestimates the wind speed in the lowest 100 m above ground on average by about 3 ms⁻¹. Introducing the forest parametrization reduces the bias considerably, but overcompensates the error at 45 m above ground, leading to a small negative bias. The URANS model further improves the flow simulation and provides a nearly bias free simulation compared to observation. Observations are taken with a 100-m high met-mast at five different levels. In addition, wind measurements taken with an Unmanned Aircraft System provide data along a cross-section that intersects the terrain edge.