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.

The relation between the fraction of snow cover and the spectral behavior of the surface is a critical issue that must be approached in order to retrieve the snow cover extent from remotely sensed data. Ground-based cameras are an important source of datasets for the preparation of long time series concerning the snow cover. This study investigates the support provided by terrestrial photography for the estimation of a site-specific threshold to discriminate the snow cover. The case study is located in the Italian Alps (Falcade, Italy). The images taken over a ten-year period were analyzed using an automated snow-not-snow detection algorithm based on Spectral Similarity. The performance of the Spectral Similarity approach was initially investigated comparing the results with different supervised methods on a training dataset, and subsequently through automated procedures on the entire dataset. Finally, the integration with satellite snow products explored the opportunity offered by terrestrial photography for calibrating and validating satellite-based data over a decade.

Svalbard Integrated Arctic Earth Observing System (SIOS) is an international partnership of research institutions studying the environment and climate in and around Svalbard. SIOS is developing an efficient observing system, where researchers share technology, experience, and data, work together to close knowledge gaps, and decrease the environmental footprint of science. SIOS maintains and facilitates various scientific activities such as the State of the Environmental Science in Svalbard (SESS) report, international access to research infrastructure in Svalbard, Earth observation and remote sensing services, training courses for the Arctic science community, and open access to data. This perspective paper highlights the activities of SIOS Knowledge Centre, the central hub of SIOS, and the SIOS Remote Sensing Working Group (RSWG) in response to the unprecedented situation imposed by the global pandemic coronavirus (SARS-CoV-2) disease 2019 (COVID-19). The pandemic has affected Svalbard research in several ways. When Norway declared a nationwide lockdown to decrease the rate of spread of the COVID-19 in the community, even more strict measures were taken to protect the Svalbard community from the potential spread of the disease. Due to the lockdown, travel restrictions, and quarantine regulations declared by many nations, most physical meetings, training courses, conferences, and workshops worldwide were cancelled by the first week of March 2020. The resumption of physical scientific meetings is still uncertain in the foreseeable future. Additionally, field campaigns to polar regions, including Svalbard, were and remain severely affected. In response to this changing situation, SIOS initiated several operational activities suitable to mitigate the new challenges resulting from the pandemic. This article provides an extensive overview of SIOS’s Earth observation (EO), remote sensing (RS) and other operational activities strengthened and developed in response to COVID-19 to support the Svalbard scientific community in times of cancelled/postponed field campaigns in Svalbard. These include (1) an initiative to patch up field data (in situ) with RS observations, (2) a logistics sharing notice board for effective coordinating field activities in the pandemic times, (3) a monthly webinar series and panel discussion on EO talks, (4) an online conference on EO and RS, (5) the SIOS’s special issue in the Remote Sensing (MDPI) journal, (6) the conversion of a terrestrial remote sensing training course into an online edition, and (7) the announcement of opportunity (AO) in airborne remote sensing for filling the data gaps using aerial imagery and hyperspectral data. As SIOS is a consortium of 24 research institutions from 9 nations, this paper also presents an extensive overview of the activities from a few research institutes in pandemic times and highlights our upcoming activities for the next year 2021. Finally, we provide a critical perspective on our overall response, possible broader impacts, relevance to other observing systems, and future directions. We hope that our practical services, experiences, and activities implemented in these difficult times will motivate other similar monitoring programs and observing systems when responding to future challenging situations. With a broad scientific audience in mind, we present our perspective paper on activities in Svalbard as a case study.

The occurrence of extreme warm events in the Arctic has been increasing in recent years in terms of their frequency and intensity. The assessment of the impact of these episodes on the snow season requires further observation capabilities, where spatial and temporal resolutions are key constraints. This study targeted the snow season of 2022 when a winter rain-on-snow event occurred at Ny-Ålesund in mid-March. The selected methodology was based on a multi-scale and multi-platform approach, combining ground-based observations with satellite remote sensing. The ground-based observation portfolio included meteorological measurements, nivological information, and the optical description of the surface in terms of spectral reflectance and snow-cover extent. The satellite data were obtained by the Sentinel-2 platforms, which provided ten multi-spectral acquisitions from March to July. The proposed strategy supported the impact assessment of heat waves in a periglacial environment, describing the relation and the timing between rain-on-snow events and the surface water drainage system. The integration between a wide range of spectral, time, and spatial resolutions enhanced the capacity to monitor the evolution of the surface water drainage system, detecting two water discharge pulsations, different in terms of duration and effects. This preliminary study aims to improve the description of the snow dynamics during those extreme events and to assess the impact of the produced break during the snow accumulation period.