Deliverable 1.8 - Recent progress and ways forward for Arctic observing capacities

Version 1 15 November 2025 101003472 | Arctic PASSION Deliverable 1.8 Recent progress and ways forward for Arctic observing capacities 2 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101003472 Work package WP1 - ESTABLISHING AN ADAPTIVE AND MORE COMPLETE ARCTIC OBSERVING SYSTEM Lead beneficiary Norwegian Polar Institute (WP1) UiT The Arctic University of Norway (Task 1.3) Lead authors Anna Nikolopoulos (UiT) and Arild Sundfjord (NPI) Contributing authors (in alphabetical order of their institutions) Anna Irrgang, Tillmann Lübker, and Marcel Nicolaus Alfred Wegener Institute for Polar and Marine Research (AWI), Germany Maribeth S. Murray Arctic Institute of North America, University of Calgary (AINA), Canada Andrew Flemming British Antarctic survey (BAS), United Kingdom Gorm Dybkjær, Steffen M. Olsen Danish Meteorological Institute (DMI), Denmark Ilaria Crotti, Srdan Dobricic EC Joint Research Centre (JRC-ISPRA), Italy Kirsikka Heinilä Finnish Environment Institute (FEI/Syke), Finland Katriina Veijola Finnish Meteorological Institute (FMI), Finland Malene Simon Hegelund Greenland Institute of Natural Resources (GINR), Greenland Caroline Coch, Margareta Johansson INTERACT Non-Profit Association (INPA), Sweden Vito Vitale Italian National Research Council, Institute of Polar Sciences (CNR-ISP), Italy Nuncio Murukesh National Centre for Polar and Ocean Research (NCPOR), India Øystein Godøy Norwegian Meteorological Institute (MET), Norway Sebastian Gerland, Mats Granskog Norwegian Polar Institute (NPI), Norway Ilkka Matero, Heikki Lihavainen Svalbard Integrated Arctic Earth Observing System (SiOS), Norway Tero Mustonen Snowchange Cooperative (Snowchange), Finland Marit Reigstad, Bodil Bluhm UiT The Arctic University of Norway (UiT), Norway Tian Li, Jonathan Bamber University of Bristol (UBristol), United Kingdom Status: Final (v1) Dissemination level: PUBLIC 3 Table of Contents Executive Summary ......................................................................................................................................... 4 1. Introduction ........................................................................................................................................ 5 2. Land and Land ice ................................................................................................................................ 7 2.1. Community Based Monitoring and Citizen Science .............................................................................. 7 2.2. Land Monitoring Sites ......................................................................................................................... 9 2.3. Wildfire: Definition of Shared Arctic Variables .................................................................................. 11 2.4. Wildfire: Web mapping service (Arctic Service INFRA) ...................................................................... 12 2.5. Permafrost: Observing best practices ................................................................................................ 13 2.6. Permafrost: Land surface change (Arctic Service ALEX) ..................................................................... 14 2.7. Permafrost: Definition of Shared Arctic Variables ............................................................................. 15 2.8. Lake Ice Arctic Service ....................................................................................................................... 17 2.9. Land ice ............................................................................................................................................. 19 3. Ocean and Sea ice ............................................................................................................................. 22 3.1. Ocean: In situ observations ............................................................................................................... 23 3.2. Sea ice: In situ observations .............................................................................................................. 25 3.3. Sea Ice: Remote sensing activities ..................................................................................................... 28 3.4. Sea ice: Shipping Safety (Arctic Service POLARIS) .............................................................................. 29 3.5. Sea Ice: Definition of Shared Arctic Variables .................................................................................... 30 3.6. Distributed Biological Observatories ................................................................................................. 31 3.7. Coastal community-based monitoring (Arctic Service) ...................................................................... 34 4. Atmosphere ...................................................................................................................................... 36 4.1. Air Quality (Arctic Service AURORAE) ................................................................................................ 36 4.2. WMO GTS datasets made available ................................................................................................... 38 4.3. Radiation observations over the ocean ........................................................................................... 399 5. Establishing a comprehensive Arctic observing system ..................................................................... 42 5.1. Priorities for enhancing Arctic observations ...................................................................................... 43 5.2. Technical and practical solutions ....................................................................................................... 45 5.3. Organisational improvements ........................................................................................................... 47 5.4. Long-term sustainability .................................................................................................................... 49 Appendix 1. References ................................................................................................................................. 51 Appendix 2. Abbreviations, Acronyms and Links............................................................................................ 55 The institutions indicated for each section in Chapter 2-4 were the leading partners for each activity, and contributors to this report. Within the text, ( ) indicate references, either to project deliverables or to general references, while [ ] refer to related sections in this report. URL links are generally not included in the free text but instead given in Appendix 2. 4 Executive Summary This report presents the progress and insights from the observational activities in the EU Horizon 2020 Arctic PASSION project and offers recommendations for advancing a long-term, integrated observing system that better supports societal needs, scientific understanding, and informed decision-making in a time of rapid environmental change. The observation-related tasks of the project spanned the interconnected domains of Land/Land ice, Ocean/Sea ice, and Atmosphere. These efforts brought together diverse partners and perspectives to assess current practices, identify gaps, and propose practical steps toward a more coordinated, inclusive, and sustainable Arctic observing system that delivers data of the necessary relevance, quality, and accessibility. In doing so, the project also contributed to closing some of the identified gaps, through targeted activities, strengthened collaborations, and shared learning. A central message from our work is that long-term, internationally coordinated funding is essential— not only to maintain existing monitoring efforts, but to develop Arctic observing systems that are responsive to societal needs and capable of supporting operational services and long-term planning. We also highlight the need to improve information flow across the full data lifecycle—from planning and observing to data processing, analysis, sharing, and synthesis. Strengthening these connections will help ensure that Arctic observations are accessible, relevant, and actionable for a wide range of users. While many valuable observations are already being made, they still remain fragmented, short-term, or difficult to access and integrate. To address these challenges, we recommend: - Sustaining and expanding long-term observations across disciplines and regions to ensure continuity in tracking and understanding the rapid ongoing changes in the Arctic climate, environment and ecosystems. - Fostering collaboration and shared commitments among nations, communities, and organizations to reduce fragmentation, optimize resources, ensure timely data sharing and increase impact. - Continuing to harmonise data collection and processing, and strengthen open, user-friendly data platforms that meet FAIR and CARE principles. This will enhance data accessibility and reusability, improve complementarity across observing system components, facilitate data use for validation, and ensure that Arctic data is used and shared in accordance with the rights and interests of Indigenous Peoples and other data rights holders. Further detail and context behind these recommendations, along with a number of more specific suggestions for action, are presented in the full report. 5 1. Introduction The key motivation behind Arctic PASSION (EU Horizon 2020 project; https://arcticpassion.eu) has been to contribute to the co-creation and implementation of a coherent, integrated Arctic observing system. By refining operability, expanding pan-Arctic scientific and community-based monitoring and improving inclusion of Indigenous and local knowledge systems, the aim has been to overcome known shortcomings in the present observing system. Arctic PASSION has also worked to streamline the access and interoperability of Arctic data systems and services, and to strengthen the economic viability and sustainability of the observing system. Arctic PASSION consisted of ten work packages dedicated to different aspects of the Arctic observing system. Most of the project’s observational activities were carried out within Work Package 1 (WP1; Establishing an adaptive and more complete Arctic observing system) which aimed to develop an inclusive and integrative framework of observations for a comprehensive Arctic observing system of systems, i.e., across components and domains. These efforts focused on coordinating, enhancing and building upon existing observing infrastructures and networks to provide the most vital observations for understanding how the Arctic system functions and evolves. Several of the Arctic Services developed within Work Package 4 (WP4; Innovating user-driven Arctic EuroGEO services) also depended on observation-related inputs. These Arctic services were established to increase the flow of information and knowledge in areas of societal and economic relevance presently inadequately served: Food security, Emergency preparedness, Wildfire and pollution risk reduction, Environmental change information and infrastructure, Transport and safe shipping. Their development followed priorities of the Arctic Council and its Working Groups, the Arctic Science Ministerial, and the Arctic Observing Summit. Figure 1. Land-Sea-Air cross-section illustrating the observational components in Arctic PASSION, undertaken mainly in Work Packages 1 and 4. The numbers refer to the sections in Chapters 2-4. The Arctic Services and data produced in the project are available through https://arcticpassion.eu/data/ or through the individual references listed in Appendix 2 (Image courtesy of H. Abbas/GridA). 6 As the concluding deliverable for WP1, this report summarizes progress and experiences made in Arctic PASSION regarding Arctic observational activities (primarily in WP1 but also in WP4) and provides our recommendations for how to move further towards establishing a holistic long-term observing system serving societal needs and meeting continuing and emerging challenges. These recommendations build on, and expand, existing Arctic-focused roadmap processes, addressing immediate gaps and longer-term targets to enhance the observing system across disciplines, considering societal needs, operational services, and long-term management. We focus on activities for obtaining the observations as such (observing methodologies, including their coordination). By observing methodologies, we mean all types of observing and knowledge systems; in situ (on site), remote sensing (satellite), Community-Based Monitoring (CBM), Indigenous and local knowledge. Other factors crucial for building and operating the end-to-end observing system like data management, production of services, end-user uptake, and funding systems are beyond the scope of this report; they are rather the focus of Work Package 8 and deliverable report 'Final Synthesis and Roadmap for further evolution of the pan-AOSS' (D8.2) with its approach on the observing system in its entirety. The Arctic PASSION contributions to this observational scope, and lessons learned, are first summarized in Chapters 2-4 as components in their natural domain (Land/Land ice, Ocean/Sea ice, and Atmosphere; Figure 1). The concluding Chapter 5 highlights our key messages from these outlined activities with onward recommendations regarding Priorities for enhancing observations [5.1], Technical solutions to overcome observing challenges [5.2], and Organisational improvements resolving fragmentation across the system components themselves, as well as across of nations, communities and organizations [5.3], while aiming to improve the Long-term sustainability [5.4]. In Chapter 5 we also relate our key messages to recommendations made by other recent projects (e.g., KEPLER, INTAROS) and organizations (e.g., EU PolarNet-2, Copernicus Polar Task Force). While reference literature is cited throughout the text, web links to sources are compiled in Appendix 2 - Abbreviations, Acronyms and Links. 7 2. Land and Land ice Arctic PASSION has aimed to unite, expand, and improve existing systems for monitoring key Arctic climate and ecosystem variables. For the terrestrial domain, WP1 served to explore how Community Based Monitoring (CBM) networks can expand observations, improve baselines, identify new indicators, and monitor local impacts, in a sustainable way [2.1]. WP1 also expanded and harmonised terrestrial monitoring through the INTERACT network [2.2]. In support of the Sustaining Arctic Observing Networks (SAON) Roadmap for Arctic Observing and Data Systems (ROADS) process, the identification and implementation of Shared Arctic Variables (SAVs) were key elements in the Arctic PASSION project. The objective was to define SAVs on Wildfire [2.3], Permafrost [2.7], and for the marine realm Sea Ice [3.7], representing three of the broader areas of concern in Arctic monitoring and decision-making (Starkweather et al., 2021). The SAV definition work followed ROADS and the input from participants in the biennial Arctic Observing Summits (AOS), acknowledging shared benefits of the observing system as an essential guiding principle. The process was shared between WP1 and WP6 and helped identify current and additional observational needs across themes through Expert Panels and open workshops (D1.2; D6.3). Arctic PASSION WP4 served to create a set of pilot Arctic Services, and several of these were related to the terrestrial scope. Within the theme of Wildfire, the INFRA web mapping service was developed to facilitate the access to relevant information from diverse sources and products [2.4]. For Permafrost, the Arctic Landscape EXplorer (ALEX) portal was developed and successfully launched, providing interactive maps of recent information on land surface changes, hot spots of disturbance, and potential areas of active permafrost thaw and erosion [2.6]. The work with this Permafrost Arctic Service also led to the development and publication of best practice guidelines for permafrost measurements, as part of WMO Guide No.8. The Lake Ice Service for Arctic Climate and Safety addressed the demand for a more unified and accessible system for lake ice conditions by integrating Earth Observation-derived data, in situ measurements from governmental networks, and communitybased monitoring [2.8]. With respect to Land ice, Arctic PASSION focused on variables not adequately covered through existing programmes, primarily coordinated by ESA. Focus was on Meltwater production and runoff, and Iceberg calving fluxes - two components that have significant impacts on the climate system as well as on activities crucial to coastal communities such as ship traffic and fisheries [2.9]. An important task in this work was to produce operational data pipelines with data flexibility and redundancy built in, to make the workflow independent of single point failures. 2.1. Community Based Monitoring and Citizen Science Snowchange Cooperative (Snowchange) 2.1.1. Background Through community-based monitoring initiatives, Arctic residents conduct or are involved in ongoing observing and monitoring activities. Arctic Indigenous Peoples have been observing the environment for millennia, and this type of monitoring often incorporates Indigenous knowledge and traditional knowledge, which may be used independently from or in partnership with formal scientific monitoring methods. 8 The role and applications of CBM have existed in the Arctic for decades. The wider adoption of these systems that embrace, support and engage with the Indigenous Peoples and local observations largely has happened because of the Indigenous land claims and other equity mechanisms in the North American Arctic. It is important to recognize that "Arctic observing" and CBM are built on a history of non-Arctic infrastructures and institutions. 2.1.2. Evolution and lessons learned through Arctic PASSION A broader assessment, by a network of Indigenous and local communities across the Arctic (D1.1; Snowchange cooperative) highlighted gaps in Arctic observations, including spatial and temporal scales of change and diverse knowledge systems. The assessment specifically aimed to address divergence in CBM observations across the Arctic and explore how CBM networks can expand observational coverage, strengthen baselines, identify and monitor new indicators and local impacts, and ensure the sustainability of CBM initiatives. The focus of the assessment was on structural frameworks and gaps in inclusion mechanisms, for example initiatives created beyond the commonly represented North American Arctic region, the role of nomadic societies in CBM, and culturally grounded practices and rights. A combination of methods was used to identify and address the gaps in CBM work; literature surveys, documentation of Indigenous best practices, targeted evaluations (e.g., ICC 2015; Holmberg, 2022) and a set of community examples from Arctic PASSION Indigenous partners. These examples were successively expanded to a pan-regional context, under awareness that the divergence across geographies remains an issue. Also, since 2022 the Russian war on Ukraine has altered the Russian CBM efforts and our capacity to connect about the situation and progress made there. In parallel to this work, the Arctic Service Event Database of Community Based Monitoring was created. This is a co-developed database of socio-ecologically relevant events focusing on significant ecosystem changes. The database includes oral/linguistic, temporal and spatial scales and dimensions, including those unique to Indigenous Knowledge and Local Knowledge. In doing so, it strengthens and diversifies monitoring capacity and supports adaptation and risk mitigation. The service is available through the Snowchange Arctic Seas portal [Appendix 2]. 2.1.3. Ways forward Arctic community-based monitoring in the 2020s is being reshaped by the combined forces of accelerating change in natural ecosystems, climate, and weather, alongside an increasing reliance on technology. These dynamics are influencing how Indigenous Peoples and other Arctic residents observe, interpret, and respond to their environments. Going forward, it is important to remain aware of past assumptions and problems associated with CBM efforts and to learn from them. Additionally, the Russian war on Ukraine has altered the methods of inter-community exchanges, for example under the Arctic Council and many other fora. To keep advancing the pan-Arctic observational system, CBM should be increasingly utilized for addressing shortcomings in instrument-based observation system across the marine, atmospheric, cryosphere and terrestrial domains (D1.1). Priority should be given to the following actions: • Expand community-based monitoring of change through observations led by those with deep cultural and local knowledge. This includes capturing signals outside formal systems such as smaller seismic events, past extreme weather, and species migrations, and establishing mechanisms to highlight “significant change” as interpreted by CBM co-researchers. 9 • Ensure ethical collaboration by implementing Free, Prior and Informed Consent (FPIC), respecting intellectual property rights, and safeguarding ownership of shared observations. These practices build trust and reinforce the validity of Indigenous contributions. • Dialogue with Indigenous knowledge through respectful exploration of hindcasting methods for historical records, place names, and gendered ways of knowing, together with the concept of “Arctic Crashes” (Krupnik et al. 2020) as potential indicators of regime shifts and tipping points. This approach helps identify areas of convergence and divergence between scientific and Indigenous perspectives. 2.2. Land Monitoring Sites INTERACT Non-Profit Association (INPA) 2.2.1. Background The effort to connect terrestrial Arctic research sites dates to the 1960s, when the International Biological Programme (IBP) linked researchers and sites across the tundra biome. The programme (1964–1974) included participants from Canada, the United States, and the western Soviet Union during the ongoing Cold War (Bliss et al. 1981). A network of nine research stations around the North Atlantic, SCANNET, was initiated by former IBP participants with the objective of monitoring environmental changes in real time. The four-year SCANNET project was funded under the EU's 5th Framework Programme (Callaghan et al., 2004). Although SCANNET's funding eventually ended, collaboration among the stations continued, and new sites joined the network based on three criteria: 1) long-term stability, with secured operation yearround and from year to year, 2) multidisciplinary activities, and 3) the capacity to host visiting scientists. By 2011, the network had grown to 33 stations across 12 countries and secured EU funding under the 7th Framework Programme, becoming INTERACT. Its aim was to create a comprehensive infrastructure for Arctic terrestrial research, including boreal and alpine stations. The network expanded to 77 stations by 2016 (marking the start of INTERACT's second funding phase) and to 86 stations in 2020 with the third phase supported by EU Horizon 2020 funding. By early 2022, over 90 stations were part of INTERACT, collectively hosting more than 15,000 scientists annually and contributing to over 150 international networks. Due to the Russian invasion of Ukraine, collaboration with 21 Russian stations was suspended (Johansson and Callaghan, 2025). To ensure long-term sustainability beyond EU funding, members of the INTERACT Steering Committee established the INTERACT Non-Profit Association (INPA) in 2020. When the INTERACT project formally ended in late 2024, all stations joined INPA, which continues to support a network of Arctic, sub-Arctic, boreal, and alpine research infrastructures (Johansson and Callaghan, 2025). To improve data accessibility and support remote research, INTERACT launched a dedicated Data Portal in 2021, offering free virtual access (VA) to metadata and datasets from participating stations. By the end of 2024, 18 stations provided VA through the portal, which hosted over 1,900 datasets, ranging from near real-time observations to digitized historical records. The portal enables online discovery and use of Arctic environmental data, aligning with FAIR data principles and promoting open science. 16 The Permafrost Expert Panel has two regional foci: Tuktoyaktuk in the Northwest Territories, Canada, and the Norwegian Archipelago in Svalbard. The panel comprises Indigenous Peoples, the communities of Tuktoyaktuk in Northwest Territories, Canada, and Longyearbyen, Svalbard as well as engineers, natural scientists, medical scientists, and social scientists [2.3] [3.5]. Using the International Arctic Observations Assessment Framework (IDA, 2017) and other evaluation tools, the panel has assessed the societal benefits of its work and aims to deliver outcomes that support both local adaptation strategies and broader scientific goals. 2.7.2. Evolution and lessons learned through Arctic PASSION Arctic PASSION supported the work to identify SAVs for Permafrost. The definition process progressed to the end of the second phase of the ROADS-defined process (Starkweather, 2021), with two SAVs proposed by the Permafrost Expert Panel: Permafrost temperature and Active layer thickness. These two properties have also been defined as Essential Climate Variables (ECVs) by the Global Climate Observing Systems (GCOS). The SAVs are expanding the scope on both observational capacities and stakeholder needs, incorporating the perspectives from Indigenous Peoples, medical sciences and social sciences. Monitoring these properties enables both the tracking of ongoing changes in the terrain, and development of awareness around expected future changes including risks to existing structures and considerations for future infrastructure development. A third SAV was identified related to changes in wellbeing resulting from changes in the permafrost and other parts of the environment. This SAV is not as well-defined as the other two at this point, but self-perceived human health-related indicators are proposed to be considered further. One key asset identified while developing these SAVs is the opportunity for better information exchange between the different communities and stakeholders. It has become clear that the local actors rarely know of all the different monitoring efforts being carried out on the permafrost theme by authorities and scientists. Better awareness is expected to help drive collaboration and inclusion. Early involvement of Indigenous Peoples is essential, and dedicated funding is needed to support their participation in the Expert Panel. Building relationships with previously uninvolved communities and stakeholders requires time and repeated engagement. However, convening diverse disciplines around a shared theme enables joint identification of current needs, exploration of relevant observations, and consideration of how communities can contribute to data collection while benefiting from the resulting services. Organizing panel activities and meeting opportunities with participants from across the Arctic (Alaska, Europe and Asia) is challenging, both with respect to high travels costs for in-person meetings, and with respect to finding commonly suitable hours for online meetings. The approach of regional Expert Panels is logistically more feasible. 2.7.3. Ways forward The SAV development work aims to provide direct guidelines and tools for local communities seeking advice and inspiration on how to address permafrost changes. For permafrost it is important that the Expert Panel’s work continues beyond Arctic PASSION, and participants have discussed how to achieve this (D6.3). Support is currently being sought to carry forward further work on the permafrost SAVs. The Arctic Circle Assembly in Reykjavik serves as an important venue for gathering feedback from the ROADS Advisory Panel to the Phase II documents and for outlining the next phase, including concrete next steps for the Expert Panel. The first draft of the Phase III document is expected to be ready by the end of Arctic PASSION. 17 2.8. Lake Ice Arctic Service Finnish Environment Institute (FEI/Syke) 2.8.1. Background The Arctic faces significant challenges due to climate change. As the lake ice cover period shortens, it has become essential to develop a comprehensive observing system to meet the growing need for timely and accurate information on ice conditions. Communities and industries operating in the Arctic, especially those relying on ice for transportation and livelihood, have been calling for an integrated approach to lake ice data. This information must be easily accessible and updated frequently, as ice conditions can change rapidly. Monitoring lake ice is crucial not only for safety but also for early adaptation to environmental changes driven by rising temperatures. The sensitivity of lake ice to temperature fluctuations and long-term trends underscores the importance of monitoring for both climate adaptation and practical decision-making in the Arctic. Although ice data is already available from several Earth Observation (EO) products, this information is scattered across different services, often making it difficult to use it in a coherent way. Local communities have resorted to informal solutions, such as WhatsApp groups, to share observations on ice conditions. However, these methods are unsystematic, lack verification, and are not integrated into formal decision-making processes. There has been a clear demand for a more unified and accessible system that can consolidate these fragmented data sources and provide actionable insights. 2.8.2. Evolution and lessons learned through Arctic PASSION The Lake Ice Service for Arctic Climate and Safety established during Arctic PASSION addresses this gap by integrating EO-derived data, in situ measurements from governmental networks, and community-based monitoring. These data are then visualized in an easily understandable format, providing a comprehensive view of lake ice conditions. One of the service’s innovative features is the ability for users to make observations based on satellite images, such as identification of cracks in the ice cover, and report these through the service. This contributes to a growing database of local knowledge and observations that are essential for safety and adaptation. Photo (Esa Nikunen, Syke´s Image bank): Heading out across the frozen lake to set winter nets – a traditional Arctic fishing practice. 18 The Lake Ice Service relies on a combination of observations and technical solutions to provide accurate and timely information on lake ice conditions (Figure 2). Key data sources include: Optical Satellite Imagery: Provides high and moderate-resolution true colour images as well as Copernicus lake-ice extent data. These images are used to track lake ice extent and the changes in ice coverage but are limited by cloud cover and the polar night. SAR Imagery: Sentinel-1 Synthetic Aperture Radar (SAR) data is used to complement optical data by penetrating cloud cover and providing observations during the polar night, which is critical in Arctic regions. Water Temperature Maps: These maps provide insights into the thermal dynamics of lakes and help predict when ice formation may occur. On-site Observations: Data from governmental Ice Thickness Stations in Finland provide continuous, high-precision measurements of ice thickness, which is a crucial factor in assessing ice stability and safety. Community-based Monitoring: Observations from residents, including from Indigenous communities, offer real-time, localized insights that complement satellite data, making the service more responsive and contextually relevant. All data sources were integrated into the service during the project. New observation routines were incorporated to enhance the service’s reliability and coverage. One significant addition was the integration of community-based observations. This allowed for real-time reporting of ice conditions directly from the field, such as identifying cracks in the ice, which satellite data alone might miss. Additionally, the development of the Highlighting Interesting Phenomena (HISP) tool enabled users to report unusual ice conditions directly through satellite images, and thereby plan routes, alert others, and contribute to a growing database of local knowledge. Figure 2. Screen capture of the Lake Ice Service representing northern Fennoscandia on 22 May 2024. Copernicus Continental Europe Lake Ice Extent data at front and Sentinel2/MSI, and Sentinel-3/OLCI true colour images at background. The orange circles represent on-site ice thickness observations and by clicking one of them, the user gets information that appears in the popup window on the map. 19 Some challenges and gaps were identified during the process: • SAR imagery, while essential for coverage during the polar night, can be challenging to interpret, particularly regarding ice thickness and stability. There is a need for further development in SAR data interpretation to improve its accessibility and usability for non-expert users. • While the network of Ice Thickness Stations in Finland provides valuable data, the geographical coverage could be expanded to include more remote areas and smaller lakes that are not currently monitored in detail. 2.8.3. Ways forward For the future, it is essential to ensure the sustainability of the observations upon which the Lake Ice Service depends. Expanding both satellite and in situ observation networks, particularly in remote and poorly monitored areas, will enhance the accuracy and comprehensiveness of the service. Furthermore, incorporating Copernicus Higher-Resolution Water Snow Ice (HR-WSI) data, expected to be available by 2026, will offer more detailed insights into smaller water bodies and enable more effective monitoring during the polar night, which is crucial for the Arctic. The Lake Ice Service will continue operating within Syke’s Tarkka platform, ensuring the long-term availability of both near-real-time and historical lake ice information. The service will also continue to evolve in close collaboration with users to better meet their needs and support decision-making. Continued collaboration with Indigenous and other Arctic communities will be important for keeping the service relevant and useful. The Lake Ice Service should be integrated more thoroughly into a broader Arctic observing system which includes both natural and socio-economic data, facilitating better decision-making across sectors. Linking ice data with weather, hydrology, and transportation systems could help create a more comprehensive and resilient observing system. 2.9. Land ice University of Bristol (UBristol) 2.9.1. Background /Previous recommendations and needs One of the consequences of the intensive Arctic warming is increasing loss of land ice. Changes in Arctic land ice challenge the sustainability of ecosystems and coastal communities within and beyond the Arctic. Between 2003 and 2019, the Greenland Ice Sheet (GrIS) lost about twice as much mass as the Antarctic Ice Sheet. Glaciers and ice caps (GICs) in Alaska, the Canadian Arctic Archipelago, Iceland, Svalbard, and the Russian Arctic Islands – and peripheral GICs in Greenland were responsible for approximately 71% of the global GIC mass loss during the same period. As a result, Arctic land ice loss is currently a major contributor to global sea level rise, which has profound and long-lasting impacts on the Earth system and globally on coastal communities. Arctic land ice loses mass through two processes: decreasing surface mass balance and increasing solid ice discharge. The negative surface mass balance can result in growing liquid meltwater discharge into the Arctic seas. The meltwater discharge at the ice-ocean interface of marine-terminating glaciers can also exert feedback mechanisms on solid ice discharge by influencing calving and ice dynamics. In the meantime, glacier calving can increase solid ice discharge by accelerating the ice flow and thinning the glacier ice. There is a need for an improved satellite observing system for Arctic land ice to serve operational to long-term planning and policy needs. Specifically, this means developing a comprehensive monitoring concept for Arctic land ice, utilizing data from the Copernicus programme and Sentinel satellite series 20 funded by the EC, accompanied by third-party science missions supported by NASA, DLR, CNES and other national space agencies. 2.9.2. Evolution and lessons learned through Arctic PASSION Our observational activities in Arctic PASSION have focused on monitoring surface meltwater production and calving front change dynamics by utilizing different Earth Observation datasets and climate model outputs. GIC mass balance monitoring programmes have been supported by ESA and NASA, although continuity is not guaranteed. Existing data products of meltwater production along Arctic coastlines often lack the detail needed in space and time as they rely on regional climate model (RCM) outputs. To improve this, a new scalable method was developed to downscale RCM data. This approach was applied to the MAR model, to create a high-resolution (250 m, daily) pan-Arctic discharge dataset for the period of 1950-2022. The dataset includes regions like the Canadian Arctic Archipelago, Greenland, Iceland, Svalbard, and the Russian Arctic Islands. By combining RCM outputs with high-resolution Digital Elevation Models (DEMs), the method generates detailed coastal meltwater estimates and separates the sources such as tundra, ice surfaces, and ice below the snowline. Compared to earlier runoff products, this dataset captures narrow, low-lying glaciers thanks to its finer resolution. The approach is well suited for operational use and could be offered as a near real-time (NRT) service using MAR forecast data, similar to the GrIS system run by the Geological Survey of Denmark and Greenland. Frontal ablation is a key component of the total mass balance of marine-terminating glaciers, which includes iceberg calving and frontal melting. This process can be quantified by tracking the glacier calving front using satellite images. The existing calving front datasets are limited to either a small sample of glaciers or to low temporal resolutions in calving front observations. Calving front mapping of glaciers has primarily relied on manual delineation from optical satellite imagery. In the meantime, the growing availability of extensive satellite datasets imposes a capacity challenge for manual delineation. This was addressed by using a novel deep learning model Charting Outlines by Recurrent Adaptation (COBRA) that can map calving fronts automatically at large spatial scales from multisource satellite images, including Landsat, Terra-ASTER, Sentinel-2 optical images, and Sentinel-1 SAR images. We applied this deep learning framework to 149 marine-terminating glaciers in Svalbard, one of the fastest-warming places on Earth, and produced a new high-resolution calving front dataset containing nearly 125,000 glacier calving front traces over the period of 1985-2023. The data pipeline for this mapping also has the potential for operationalisation providing NRT calving fronts as well as spatially differentiated calving fluxes. The GrIS is a leading contributor to global sea level rise, and it has been losing significant mass, albeit with large interannual variations. The current remote sensing methods for measuring the GrIS mass balance have difficulty in separating mass changes caused by surface mass balance loss or dynamical mass loss, making interpretation of the driving mechanism difficult. To solve this problem, a Bayesian hierarchical model (BHM) framework was used to incorporate multiple satellite and in situ datasets, aiming to improve the mass balance estimates with a finer temporal resolution between 2002 and 2023 and to partition the contribution between surface processes and ice dynamics. The BHM can simultaneously assimilate the diverse observations with different spatio-temporal resolutions and reduce the uncertainties and assumptions when generating the reconciled mass balance. 21 2.9.3. Ways forward Diverse high-resolution satellite observations and accurate regional climate model outputs are needed to establish a comprehensive and integrated Arctic land ice observing system. The EC Copernicus programme provides for some of the operational observational needs but not all. Current approaches are still reliant on non-operational science-focused missions such as the ESA Earth Explorer missions and the joint NASA-DLR GRACE missions. Future observational activities, in general, lack redundancy and are therefore vulnerable to funding cycles and hardware failure. For this reason, multi-sensor and diverse approaches are desirable. The hydrological routing and runoff integration procedure used in our meltwater discharge downscaling algorithm is highly simplified, assuming the surface meltwater is instantaneously transported to the coastline. A better understanding of this process can further reduce the uncertainties in the meltwater discharge dataset. This would require accurate surface meltwater observations, either from in situ measurements or from satellite observations, which can be used to constrain the regional climate model runoff simulations and to improve the modelling of runoff routing at the glacier surface. Understanding the glacier calving mechanism has been a long-standing challenge in glaciology. The existing glacier calving laws are overly simplified due to a lack of high-resolution glacier calving front datasets over a large spatial scale. The unprecedented spatial coverage and temporal resolution offered by our Svalbard glacier calving front dataset represent a step forward in addressing this challenge. A holistic glacier calving front observing system relies on publicly available optical and SAR images from multiple satellite platforms, as well as advanced automated calving front mapping algorithms. This also applies to the BHM framework for addressing the GrIS mass balance, which requires multiple satellite observations for elevation changes or mass changes of the ice sheet, including altimetry, gravimetry, GPS observations, and regional climate model outputs as prior information. Recommendations for intermediate goals (1-3 years): • Develop a scalable AI-driven tool for near-real-time glacier calving front monitoring using satellite data publicly available from NASA, ESA and other space agencies. Commercial satellite imagery does exist but would be prohibitively expensive for operational applications. This development aligns with the initiatives like the ESA AI4EO program and the NASA Earth System Observatory. • Develop a comprehensive meltwater discharge in situ observation network and high-resolution modelling framework for Arctic glaciers and ice caps. This aligns with current EU-funded projects, like LIQUIDICE. • Develop a collaborative framework for data harmonisation for Arctic glaciers and ice sheets integrating national and international initiatives. Recommendations for long-term goals (5+ years): • Build an integrated digital twin for Arctic land ice that combines Earth Observation data, numerical models, and Artificial Intelligence. This aligns with the EU Destination Earth and the ESA DTE initiatives. 22 3. Ocean and Sea ice In recent decades variability in sea ice extent, concentration and absence of sea ice over longer periods and the loss of multi-year ice has characterized the Arctic Ocean and adjacent seas. The effects of these changes have influenced all aspects of life. The decline in multi-year ice and year-to-year changes in seasonal sea ice cover create risks, challenges and opportunities that affect all Arctic communities, pan-Arctic sectors, and global actors alike; therefore, continued, coordinated observation is crucial to understand the long-term trajectory and plan for and mitigate impacts. Loss of sea ice also has global consequences, affecting biodiversity across a large portion of the planet, influencing the decision making of multinational and national corporations around transport, fisheries and development in the Arctic, and climate impacts for areas far removed. In the marine realm, Arctic PASSION prioritized the expansion of in situ long-term observations, including new deep-ocean moorings in the central Arctic Ocean and enhancing coordination of drifting sea ice buoys in the European sector of the Arctic Ocean. Moorings were placed at new strategic locations [3.1], and several annual deployments of various drifting sea-ice buoys were carried out [3.2]. Within the scope of sea-ice buoys, considerable progress was made in harmonizing data processing for snow and ice thickness data from drifting mass balance buoys in the central Arctic Ocean, improving data quality and comparability from such observatories. Satellite observations remain essential for monitoring sea ice and upper-ocean conditions, offering broad spatial coverage and frequent updates. However, in the high Arctic, persistent sea ice cover, frequent cloudiness, low solar angles, and polar night conditions limit the effectiveness of many satellite sensors, particularly for under-ice and subsurface observations. These limitations underscore the importance of complementary in situ measurements to fill spatial and temporal gaps and to capture processes occurring beneath the surface. A comprehensive observation system therefore requires satellite observations and traditional ground-based (in situ) observations to be effectively integrated. For this integration to be successful, onsite data must be of sufficient quality and in formats compatible with satellite data referencing. As part of WP1, three satellite datasets for sea-ice were co-developed and produced through collaboration with both internal and external partners and projects [3.3]. Within the scope of changing sea ice conditions, historical patterns of ship activity and risk were assessed to understand trends and needs in Arctic ship operations. A new shipping service was developed in WP4 applying the IMO POLARIS forecast methodology, based on sea ice forecasts by operational sea ice models [3.4] from WP1. Arctic PASSION contributed to the SAON ROADS process for identification and implementation of Shared Arctic Variables (SAVs) [2.3][2.7]. For Sea Ice SAVs [3.5], the work progressed through the establishment of a Sea Ice Expert Panel. The purpose of this panel is to improve the coordination and relevance of sea ice observation in the Baffin Bay region while prioritizing societal benefit in the SAV identification and selection process. The support from Arctic PASSION led to the establishment of the Atlantic-Arctic Distributed Biological Observatory (A-DBO), as part of a suite of interdisciplinary marine observing networks across the Arctic Ocean tracking the impact of changing environmental drivers on the Arctic marine ecosystems [3.6]. WP1 also supported the development and expansion of community-based monitoring (CBM) in Qaanaaq, Greenland, and surrounding communities both through increased dialogue with the communities about their requests and needs from science, and through joint development of the practical deployment methods for handling scientific instrumentation [3.7]. 23 3.1. Ocean: In situ observations Norwegian Polar Institute (NPI), Alfred Wegener Institute for Polar and Marine Research (AWI) 3.1.1. Background Obtaining Arctic marine observations with sufficient temporal and spatial coverage, requires interdisciplinary measurements using a variety of platforms, sensors, and methods, spanning coastal areas, shelf seas, continental slopes, and deep ocean basins - from the sea surface (including sea ice and snow cover) to the seafloor. Many institutions, funded through internal, national or competition-based sources, contribute to the Arctic observation efforts. To ensure cost efficiency and deliver consistent, user-friendly data and actionable knowledge, the entire data providing chain - from planning observation campaigns and long-term platform deployments, to processing and sharing data - must be well coordinated and harmonised. 3.1.2. Evolution and lessons learned through Arctic PASSION Through coordination and with partial funding from Arctic PASSION WP1, long-term deep-ocean moorings were deployed in the central Arctic Ocean (D1.7). The mooring locations were selected to capture emerging ‘Atlantification’ in the Nansen Basin and contrasting features of the Amundsen Basin, filling a geographical gap in the region (Figure 3). Core variables to target were identified and agreed upon and common sensor depths were identified for facilitating data comparison across these deep central Arctic Ocean basins. Two moorings in the western Nansen and Amundsen Basins (Nansen-22, Amundsen-22) were deployed in summer 2022 and serviced/re-deployed in 2024; at the time of writing having collected data over a three-year period. The ambition is to continue operating the two moorings for the foreseeable future, to establish long-term time series in key locations. For other locations, subject to 1–2-year mooring deployments during Arctic PASSION, the goal was to learn more about the environmental conditions at these locations before deciding on additional new long-term locations. The new Arctic PASSION moorings were equipped with essential sensors and samplers, such as radiation and chl-a sensors and upward-looking sea ice thickness sonars, which all are typical components in similar mooring systems. Collecting key ECVs at the same locations throughout the seasonal cycle and over several years will provide a much better basis for understanding variability and change in the central Arctic Ocean. The new in situ datasets will be especially valuable for numerical ocean and sea ice reanalysis models and, hence, also contribute to the improvement of operational models. For more info about the deployments, instrumentation, and data availability, see report D1.7. The inflow and outflow exchanges of the Arctic Ocean are reasonably well covered through long-term multi-institution monitoring programmes at the key gateways; Fram Strait and the Barents Sea opening, the Bering Strait area, and Davis Strait/Baffin Bay. Other parts of the interior Arctic Ocean have also been subject to dedicated continuous observations, e.g. the NABOS (UAF-IARC) and K-AWARE (KOPRI) programmes north of the Siberian shelf seas, multi-year moorings in the Chukchi Sea within ArCS I, II and now III (NIPR, JAMSTEC and others), and the US/Canadian Beaufort Gyre observing system (BGOS; WHOI, YALE, UW, DFO-IOS and others). In addition to filling geographical gaps in the Atlantic-influenced part of the Arctic Ocean, the Arctic PASSION mooring deployments are 24 Figure 3. Map showing the locations of NPI and AWI moorings deployed within Arctic PASSION 2022-2024. The coloured arrows show the main pathways of warm Atlantic water (red shades) and the cold polar waters (blue shades). aligned with the site selection and instrumentation for the ongoing EU-funded High Arctic Ocean Observing System project (HiAOOS), which also strengthens environmental observations in the Nansen and Amundsen Basins. Although progress has been made with respect to coordination of field campaigns, harmonisation of procedures and prioritizing of key variables, the Arctic Ocean is still severely under-observed. Key interfaces like land-coast and sea ice-upper ocean and regional hotspots of rapid change should be covered by continuous, long-term, inter-disciplinary monitoring programmes. 3.1.3. Ways forward Coordination of observational activities with ice-capable research vessels in the Arctic is difficult. Different institutions have different planning horizons and different priorities regarding long-term monitoring, emerging research topics, and under-studied regions. During the second half of Arctic PASSION, annual meetings between chief scientists of campaigns to the central Arctic Ocean were held, with coordination also from the HiAOOS project, to identify synergies and plan mutually beneficial collaboration. In the future this should be a larger annual venue where also longer-term cruise plans are discussed to ensure optimal use of resources, ideally even before plans are submitted to funding agencies. The pan-Arctic DBO network [3.6] is a long-term network comprising many of the key institutions conducting science expeditions in the high Arctic, and this network could take responsibility for providing such an annual venue. Given that ocean moorings and drifting sea ice platforms are deployed and serviced by research vessels, planning of such operations could also be coordinated in concert with cruise information and planning meetings. Locations, sensor selection and design of long-term ocean moorings must be known for planning the design and deployment of drifting sea ice platforms such that the two types of instrumentation together provide the best possible coverage of key variables in the water column – including the under-ice layer into which moorings normally do not extend to capture due to the risk of equipment 25 loss from deep sea ice keels. We recommend holding open annual meetings among those operating Arctic Ocean scientific campaigns, moorings, and sea ice platforms. Ideally, these meetings should include multi-year planning horizons to allow new proposals to align with existing programmes and schedules. The shortfall of sustained, international and coordinated funding for in situ observations in the central Arctic Ocean combined with the high operational costs makes it difficult to establish comprehensive long-term monitoring programmes. From time to time, voluntary coordination efforts among the key actors improve the efficiency and ‘value for money’ but do not solve the fundamental problem which is the absence of sustained funding schemes. This issue cannot be addressed only by the observing community but must also be raised to the appropriate entities by users of such observational data. 3.2. Sea ice: In situ observations Alfred Wegener Institute for Polar and Marine Research (AWI), Norwegian Polar Institute (NPI) 3.2.1. Background Drifting sea-ice buoys are used to track the spatial and temporal evolution of the sea ice and its snow cover. They are deployed during expeditions and left behind to drift with the sea ice. They report their measurements through satellite communication in near real-time. Depending on the suite of sensors deployed, these drifting sensor platforms can allow monitoring of atmosphere, snow, sea ice, and ocean parameters when manned observations are not possible. Such buoys come in different forms and levels of complexity. The simplest versions contain only GPS and temperature loggers to track the drift of the ice pack. More complex buoys also report physical properties of snow, sea ice, and ocean. Most sea ice buoys comprise a string of thermistors (temperature sensors) that capture the temporal evolution of temperature through the snow cover and sea ice, and into the underlying water mass. This allows for identification of the snow-sea ice interface and the snow-water interface, as well as capturing episodes of water intrusion and subsequent freezing at the snow-sea ice interface. Even more advanced drifting platforms comprise sensors measuring properties of the upper part of the water column, either at fixed depths on strings or in profiling units. Data from sea ice buoys were also collected from fast ice in NW Greenland, of which the main parts are recorded in the vicinity of the DMI field facilities in Qaanaaq (NW Greenland), hereafter Qaanaaq Winter Observatory (QWO). This data set includes simultaneous data from Automatic Weather Stations (AWS) and Ice Mass Balance (IMB) buoys. The QWO data focus on surface temperature, but the data set also comprises several other related parameters, like air temperature and snow/ice interface temperature and snow albedo. This data set has so far been recorded over 12 years (20142025). 3.2.2. Evolution and lessons learned through Arctic PASSION As part of Arctic PASSION, several drifting sea ice buoys or platforms with different combinations of instruments were deployed in the central Arctic Ocean: Sea-ice mass balance buoys: These sea ice buoys comprise a string of thermistors (temperature sensors) that capture the temporal evolution of temperature through the air, snow, and sea ice, and into the underlying water mass. In Arctic PASSION we used thermistor string buoys with active heating cycles (SIMBA; Jackson et al., 2013). Data analysis allows the identification of the snow-sea ice and the 32 environmental and ecosystem changes along the Pacific Arctic inflow shelves, and their impacts on marine mammals, seabirds, and local communities. The DBO concept aligns well with earlier recommendations such as those from EU-PolarNet 2 (Lymer et al., 2024). These recommendations highlight the need to share observing infrastructures and coordinate activities, connections in time and space, and standardisation. They also highlight data, international collaboration and societal relevance (including education), as well as funding and societal benefits where long-term sustainability and dedicated action groups are suggested elements. In 2016, a workshop supported by the IASC Marine Working Group, evaluated the need for a DBO in the Atlantic sector of the Arctic, and concluded that there was strong interest, and need, for enhanced coordinating capacity among relevant science communities. 3.6.2. Evolution and lessons learned through Arctic PASSION Arctic PASSION provided capacity and momentum to establish an Atlantic-Arctic DBO (A-DBO), aimed at improving coordination of existing observational activities in this region. Building on recommendations from the 2016 workshop, a set of transects was agreed upon with key stations representing ongoing long-term monitoring under various national and institutional responsibilities. To facilitate and strengthen collaboration among science communities working in the Atlantic-Arctic gateway, the focus was on creating meeting places to build the foundation for a continued A-DBO network. A landing page was established early as the main channel for information sharing, and a first set of shared tools for planning and reporting observational data was also developed (D1.3; Appendix 2). During Arctic PASSION, bi-annual meetings were organised and the following successes achieved: 1) Establishing an organisational structure of the A-DBO that includes relevant institutions and science communities, 2) Formulating a vision of collaboration to optimize the observational capacity, with ambitions to improve harmonisation of methods and data, 3) Engaging a broader science community, including early-career professionals, to strengthen both disciplinary and interdisciplinary networks and support discussions on priority science questions and key features to monitor, 4) Promoting and contributing to the establishment of an expanded, pan-Arctic DBO network including the Pacific DBO, the A-DBO, and two complementary DBOs being established in the Siberian Seas and in the Baffin Bay/Davis Strait region, 5) Developing a vision and ambition for the pan-Arctic network of DBOs, and 6) Connecting to other relevant Arctic marine observational networks and initiatives such as the Synoptic Arctic Survey (SAS), the EuroGOOS Arctic ROOS, and the ongoing process to develop an Arctic Ocean Regional Alliance (ArORA). 3.6.3. Ways forward With the rapid and multiple environmental changes taking place globally and regionally, some of which are propagating deep into the central Arctic Ocean, it is urgent to strengthen and optimize the observational capacity. There is great potential in a more synergetic use of existing structures and resources. Increased collaboration and harmonisation across programmes providing long-term time series and shorter-term, project-based activities will increase the value and reduce the fragmented nature of current observational efforts. This requires continuous attention and encouragement. At present, few incentives beyond the scientific reward exist. There is a need for sustained and prioritized funding to facilitate collection of more and better observations including biologically relevant measurements across the Pan-Arctic domain. There is also a need for dedicated support to synthesise data and results targeting the larger Arctic region. Such synthesis activities will highlight the need for harmonised data practices and motivate the work on 33 data publications along the FAIR/CARE guidelines to increase the longevity and extended use of existing data. Intermediate goals (1-3 years) recommendations: • Support networks like the DBOs through sustainable funding to create meeting places and counteract fragmentation. • Support early career professionals with travel funds, mobility grants and research projects to enhance scientific outcomes and foster international collaboration across existing time series datasets. • Establish closer contact with rights holders and stakeholders to ensure inclusion of variables or samples that are particularly important for society and certain user groups. • Encourage greater use and funding of ecologically relevant sensors and sensor development to expand and improve ecosystem observations. • Promote data management practices that support identification, harvesting and harmonised use of data across storage platforms (e.g., the SIOS, SAON, PANGAEA databases). • Strengthen collaboration with remote sensing and modelling communities to improve access to data needed for validation, evaluation and model input • Support synthesizing research efforts using data across different observatories and observational approaches – providing valuable context for both planning and implementing the upcoming International Polar Year. Figure 5. The pan-Arctic network of DBOs sampling locations overlaid on the Arctic Ocean bathymetry and a schematic of the main circulation pathways. Red/pink/green shades are used for inflowing waters from the Atlantic and Pacific Oceans and blue shades for outflowing surface polar waters. The indicated coastal communities are those where special efforts are made to co-develop coastal observation systems. See https://arcticpassion.eu/adbo/ for more information on the A-DBO. 34 Long-term goals (5+ years) recommendations: • Develop international agreements on joint observational contributions to pan-Arctic observatories. • Prioritize long-term funding for nationally and institutionally driven collection of time series, encouraging national funding agencies and governments to support shared and collaborative responsibilities. • Promote stronger links between research activities and existing observational networks and structures as these provide temporal and spatial context for new observations. • Optimize observational strategies to detect changes and trends, including those relevant to societal needs and nature conservation. • Harmonize observations across sites to capture site specific features and enable reliable comparisons. • Continue advancing FAIR and CARE data handling practices to improve the usability and accessibility of collected data. 3.7. Coastal community-based monitoring (Arctic Service) Danish Meteorological Institute (DMI), Greenland Institute of Natural Resources (GINR) 3.7.1. Background Indigenous communities in Northern Greenland rely on narwhal hunt and the narwhal is very sensitive to underwater noise. The decrease in sea ice due to global warming leads to thinner and less sea ice, which is of real safety and food security concerns to communities as they rely on sea ice for hunting and transport. Decreasing sea ice also leads to higher ambient noise levels from natural and anthropogenic sources, which is a major concern for families relying on hunting the sound sensitive narwhal. Indigenous communities near the North Water Polynya (Pikialasorsuaq) are experiencing increasing tourism, research and exploration activities. Through the Pikialasorsuaq commission, the communities have expressed a need for more involvement and training in resource management and planning activities in the area including scientific monitoring. Increasing ambient noise in relation to sea ice loss and increased shipping and other anthropogenic activities has been identified as a major concern in PAME and AMAP working groups. 3.7.2. Evolution and lessons learned through Arctic PASSION Arctic PASSION contributed to the development and expansion of community-based monitoring (CBM) in Qaanaaq and surrounding communities. This Arctic Service to monitor the marine climate and noisescape in coastal zones was co-created with the communities of Qaanaaq, Savissivik, Siorapaluk and Qerqertat in NW Greenland. The CBM activities include community meetings and dialogue forums, to identify and include local requests and science needs in monitoring. The scientific activities include monitoring of physical parameters such as snow and sea ice characteristics, sea water salinity and temperature, as well as ambient noise levels and monitoring marine mammals’ sound with passive acoustic recorders. The latter activity has a special focus on narwhals because of the importance of narwhal to the local communities and their culture. Meetings and field activities are carried out 2-6 times per year. 35 The development of new deployment methods for advanced monitoring instrumentation through sea ice with dog sledges combines Indigenous knowledge and skills with scientific methods. This approach has worked out very well, and will continue to be applied in the future. Members of the communities will get regular training in the technical and practical tasks of operating the monitoring network of bottom-moored instrumentation. Analysis of the collected data revealed that narwhals have a stronger link to the edge of the sea ice on their summer migrations than first expected. They are so closely linked that there may be unknown food sources associated to the melting sea ice edge. This new knowledge can lead to a better understanding of how disappearing sea ice affect marine ecology, narwhals and communities. Community meetings and dialogues have helped to expose new scientific questions, such as finding ways to identify subpopulations of narwhals, both morphologically and genetically. This is a new project which has evolved from the CBM community meetings. Another example is a concern raised by community members over international scientists deploying active acoustic scientific instruments in narwhal hunting grounds. We have investigated this and found the sources of concern and presented it to the Greenland Government. The community concern raised during the dialogues has led to an increased awareness in the Greenland management bodies about using active acoustics for marine monitoring purposes in traditional hunting areas. 3.7.3. Ways forward The now established CBM program in Qaanaaq will continue the basic monitoring with bottom moored loggers in a collaboration with the community. The site has been designated as part of the Baffin Bay Distributed Biological Observatory (DBO) and will continue to evolve within the DBO community [3.6]. It serves as a strong example of how DBO sites can be relevant to local communities and aligned with their needs. The pilot Arctic Service will in the future seek to develop into the Pikialasorsuami Nasiffik, a local driven science hub where researchers can contact the community to present plans, request local assistance and provide results from scientific projects. The local community can deliver community science needs and suggest involvement in activities. A connection is currently being developed between the Qaanaaq CBM to the Grise Fjord CBM in Canada. This is meant to be a collaboration across the North Water Polynya, including monitoring sites in the polynya. 36 4. Atmosphere For the atmosphere domain, Arctic PASSION supported the development of the Air Quality Forecast for Arctic Communities (AURORAE) Arctic service to release reliable short-term air pollution forecast as support to local communities, local authorities, policymakers and citizens and to align to the new European Air Quality Directive 2024/2881 [4.1]. The AURORAE service provides an easy-to use web interface that allows access to near-real time particular matter concentrations data and forecast for about a hundred air pollution monitoring stations in the European Arctic. Hence, added value is provided to air pollution observations, improving data accessibility and interoperability. Arctic PASSION also contributed to making World Meteorological Organisation (WMO) Global Telecommunication System (GTS) real time exchange data available for non-GTS connected users [4.2]. The primary focus of the approach was to extract information from synoptic weather stations, radiosonde stations and ocean buoys. Activities initiated within the EU H2020 Arctic Research Icebreaker Consortium (ARICE) project were continued to take the opportunity offered by commercial passenger cruises for implementing costeffective monitoring of surface radiation fluxes and cloud measurements over the Arctic Ocean [4.3]. 4.1. Air Quality (Arctic Service AURORAE) EC Joint Research Centre (JRC-ISPRA) 4.1.1. Background For a long time, the atmosphere in the Arctic has been considered free from pollution until explorers in the 1950s observed the phenomenon of Arctic Haze, the accumulation of pollutants in the lowest part of the troposphere during winter and early spring. This phenomenon is driven by low temperatures during the cold Arctic winter trapping the atmospheric pollutants close to the Earth’s surface. Particulate matter (PM) is an atmospheric pollutant which can be found in the Arctic and consists of a mixture of solids and liquid droplets containing several chemical species such as nitrate, sulphate, organic compounds, and many others. Nowadays, residential combustion for heating, shipping, oil extraction and metal smelting represent the main local PM sources in the extreme North. Due to the small size of the particulate, with 10 µm of equivalent diameter or less, called PM10, the particles can enter the lungs through breathing, and exposure to high concentrations might cause respiratory problems, cardiovascular diseases and cancer. Considering the adverse health effects caused by PM10, an accurate forecast of its concentrations is essential for pollution mitigation and emergency preparedness in Arctic villages and cities. The forecast of PM10 concentrations over Europe, including the Arctic, is performed by the Copernicus Atmosphere Monitoring Service (CAMS), based on an ensemble of eleven state-of-the-art numerical air quality models. Nonetheless, the CAMS predictions have uncertainties, mainly related to errors in the input data such as initial state estimation, model parametrization, emissions, and model algorithms. Also, CAMS forecasted concentrations appear to agree less with in situ measurements of PM10 in Northern Europe in comparison to other regions. In addition, CAMS air pollution forecasts are difficult to access by non-scientific and non-professional users. 4.1.2. Evolution and lessons learned through Arctic PASSION As one of the Arctic PASSION Arctic Services developed in WP4 (D4.13; EC-JRC, 2024), the AURORAE air quality service was developed to provide reliable short-term air pollution forecasts tailored to the 37 needs of local communities, authorities, policymakers, and citizens in the European Arctic. The service also aligns with the new European Air Quality Directive 2024/2881 (EU, 2024), supporting policy planning and efforts to reduce population exposure to harmful pollutants. Producing accurate and accessible PM10 forecasts for Northern European countries is therefore critical, particularly to empower Arctic communities and inform decisions on pollution reduction and prevention measures. The AURORAE service provides an easy-to use web interface that allows access to near-real time PM10 concentrations data and forecast for about a hundred air pollution monitoring stations. It is designed for a non-scientific audience, and users can easily visualize and download PM10 at the selected stations through an interactive map. The service, in addition, aims at providing added value to air pollution observations, improving data accessibility and interoperability. This approach strengthens the effectiveness of the air pollution monitoring stations network and provides additional societal benefits to people living in the Arctic. AURORAE is composed by three main modules: • Data gathering module: it collects daily PM10 concentrations from the European Environmental Agency (EEA) and Finnish Meteorological Institute (FMI) monitoring stations at one-hour resolution, CAMS weather meteorological fields forecast, and PM10 CAMS forecast for North Europe as input to the Forecasting module. • Forecasting module: consists of a Deep Learning model (Crossformer) that provides PM10 concentration forecast for the upcoming 48 hours for each monitoring station. • Online platform module (dashboard): the near real time PM10 concentrations and the forecast are visualized on an interactive map in which all monitoring stations. The dashboard is the information access point for the users to visualize and download the PM10 observation time series and forecasts for each station. In addition, the service releases a daily air pollution report with current PM10 concentrations, forecasts for all monitoring stations, and pollution trends, available for free download. During the development process we encountered the following challenges within the observational scope: • Lack of sufficient spatial coverage of monitoring stations in the European Arctic - even though the service is tailored for all European Arctic communities the PM10 forecast cannot be provided to all of them due to lack of data. • Discontinuity of air pollution data over time. Some of the air pollution monitoring stations that provide PM10 input data for the forecast model may experience technical issues and fail to deliver data for several days or even months, disabling the service from issuing forecasts for those locations. The CAMS Data Store service was also down following a data server migration, preventing the release of the forecast on certain dates. • Technical disturbances were caused by migration of the data servers involving changes in the programming interfaces and data format, delaying the implementation of the service. 4.1.3. Ways forward For the upcoming years it is important to guarantee and expand the air pollution observation network on which the AUROARE service relies, especially in the Arctic. The EEA and FMI are operating only a few stations at latitudes north of 65°N; expanding the in situ observation network is essential to improve the knowledge on air pollution in remote areas and increase the geographical extension of the AURORAE service. The extension of geographical coverage of the in situ monitoring stations would allow the production of forecasts on a regular geographical grid. 38 Currently, most of the EEA and FMI stations measure PM10 concentrations, but only a small amount of them can measure the concentrations of other key pollutants such as PM2.5, ozone, nitrogen oxides, and sulfur oxides, etc. It is essential to increase the analytical capabilities of the in situ monitoring stations to provide more data on such other atmospheric pollutants and to develop a comprehensive forecast model including those compounds. Continuous engagement and collaboration with local communities, local authorities and citizens is crucial also to increase the usefulness of the service and to provide socio-economic benefits to the users. In addition, there is a strong relationship between air pollution and wildfires, especially in Canada and Alaska. A future expansion of the AURORAE service to North America would constitute a valuable opportunity to develop a new service, in collaboration with the INFRA service, that provides information on both wildfire activities and the level of air pollution generated by such extreme events, improving communities’ responsiveness and mitigation capabilities. 4.2. WMO GTS datasets made available Norwegian Meteorological Institute (MET) 4.2.1. Background The World Meteorological Organisation (WMO) Global Telecommunication System (GTS) is the system serving real time exchange of data for WMO and is operated in a private network. It is a key component of the WMO Information System (WIS). GTS is being replaced by a more modern approach, WIS2.0, based on an approach relying on a lightweight, publish-subscribe, machine to machine network protocol for message queue/message queuing service (MQTT). When the transition from GTS to MQTT is finished, the WMO real time exchange of data will no longer happen in a private network but will use the public Internet as the transport mechanism. It is, however, still a private network in the sense that it is made to serve the needs of WMO member states operational services. (Details on the system set up are provided through the acronym list in Appendix 2) Traditionally, the GTS information has been conveyed in WMO binary formats BUFR and GRIB which are generally difficult formats to interpret, requiring specialised software and correct lookup tables. WIS2 is detaching a bit from the BUFR and GRIB approach, making the information easier to read and interpret (although the bulk of data will still be in these formats). As part of the evolution of WMO data exchange, the Climate and Forecast metadata convention CF-NetCDF has also become a WMO adopted format and can be used in WIS2.0. While GTS focused primarily on real time or near real time data, WIS2.0 has a wider scope and will also be able to serve delayed mode data (although this capacity is still under development). MQTT in WIS 2.0 is a direct replacement for GTS in the real time data exchange capacity. Furthermore, with the existing GTS operation through private networks (as opposed to Internet), there is a need for user community demand for the products, for e.g. feeding into numerical models, as bandwidth is limited. 4.2.2. Evolution and lessons learned through Arctic PASSION Arctic PASSION has contributed to making real time exchange data within the WMO GTS available for non-GTS connected users. Data were extracted from WMO BUFR binary data format and converted to CF-NetCDF format for publication. In the process, individual measurements were aggregated into datasets. The intention was also to ingest datasets into WMO GTS, but no datasets were proven to be relevant for real-time exchange at this point. Delayed mode datasets will be continuously considered for this purpose. The datasets extracted from WMO GTS were not, as such, generated by Arctic PASSION, but the project improved and simplified access to these data for a larger number of 39 users by exposing them outside the limited group that have access to them today. Furthermore, by ingesting them into the SAON data portal the datasets were made more easily discoverable. The datasets generated by Arctic PASSION based on information through WMO GTS are published as CF-NetCDF files with global attributes adhering to the Attribute Convention for Dataset Discovery (ACDD). In the process, the instantaneous measurements reported as messages in WMO channels were collocated into time series as well. The primary focus of the approach, in prioritized order, was to extract information from synoptic weather stations, radiosonde stations and ocean buoys. More than 45 weather stations were made available, and about 20 radiosonde stations. The number of reporting ships and buoys is highly variable. For the ingestion of new datasets, a challenge was that no new (near) real time data streams announced by Arctic PASSION partners that would be suitable. Nor were any third-party datasets identified as suitable for ingestion and subsequent use by e.g. the WMO modelling community. Although the availability of real time or near real time observations from the Arctic is improving, the business model of research is still imposing bottlenecks for swift data publication and data reuse. Thus, no real-time data was made available for WMO GTS or MQTT (interface not available). 4.2.3. Ways forward Work is in progress to make discovery metadata from the SAON Data Portal available for WIS 2.0, to announce the existence of new data as such become available. This is not ingestion into the real time exchange of data (as discussed above) but merely adapting the discovery metadata announcing the existence of a dataset to the discovery mechanism of WIS 2.0. The reason for this is that WIS 2.0 relies on a totally different discovery protocol than what is normally used within scientific data management. This interface contains both data generated by Arctic PASSION partners and third-party datasets. While National Meteorological and Hydrological Services within WMO are providing much data at low and mid latitudes it is observed that most of the data in the Polar regions come from the research community. Encouraging this community to continuously improve real time data access by sharing with operational agencies would be beneficial but also calls for alternative business models for the research community. While shared datasets are increasingly acknowledged as Key Performance Indicators (KPIs), they often still remain less emphasized compared to more traditional metrics. 4.3. Radiation observations over the ocean Italian National Research Council, Institute of Polar Sciences (CNR-ISP) 4.3.1. Background Reduction in sea ice extent and thickness largely impacts surface energy exchange processes. Response of the clouds to the changing surface conditions modify the planetary albedo when sea ice melts. Knowledge of all processes and interactions is still poor, with systematic measurements almost exclusively made only from space while ground-based observations are very few and sporadic. This limitation has an impact also on the quality of satellite measurements due to the lack of data for validation activities using observations over the ocean and at high latitudes. 40 4.3.2. Evolution and lessons learned through Arctic PASSION Arctic PASSION continued an activity initiated under the ARICE framework, taking the opportunity provided by the PONANT cruise operators to implement a cost-effective monitoring programme for surface radiation fluxes and cloud measurements over the Arctic Ocean. The programme was designed with both scientific and technical objectives. From a scientific perspective, continuous radiation and sky observations allow characterization of downwelling radiation at the surface. These cover both shortwave (SW) and longwave (LW) components, as well as cloud coverage and radiative impact over a very wide range of latitudes through the whole summer season. Measurements of UV-A and UV-B surface fluxes also provide valuable data for investigations of marine ecosystems. Technically, several new solutions were tested to improve ship-based atmospheric measurements, particularly automatic clean systems for radiometer domes. The goal is to ensure instrumentation continuous operation with minimal maintenance, allowing all cruises to contribute relevant data and potentially transmit them to land in near real time. In 2022 a suite of sensors for measuring downwelling fluxes and ancillary parameters was installed on the icebreaker cruise ship Le Commandant Charcot. Following a detailed inspection and assessment of requirements for radiation measurements, maintenance, power supply, and communication, the instrumentation was mounted aft on the port side of the tenth deck (see Photos 1 and 2). The sensor suite includes a pyranometer, a pyrgeometer, a UV-A sensor, a UV-B sensor and an all-sky camera. Due to technical issues, only 2-3 months of data were collected in 2022. After repairs and system checks in April 2023, the setup was stabilized, enabling continuous data acquisition from May 2023 to May 2025. During this period, the ship conducted multiple cruises both in Arctic and Antarctic regions. An instrument maintenance and upgrade effort is planned for July 2025. The acquired datasets support the development of novel analysis methodologies. Additionally, the design of an automatic cleaning system (RADCLEAN) has been initiated, with the first prototype currently under construction. 4.3.3. Ways forward As the work continues, future plans include: • Routine observations of radiation and cloudiness conditions aboard Le Commandant Charcot. • Establishing a second observing point on the ship to increase the significance of measurements as recommended by several studies and best practices. CNR-ISP and PONANT will collaborate to identify the most suitable solution for this upgrade. • Finalizing the RADCLEAN system and conducting extended performance tests. • Ensuring data interoperability with project database through Italian polar data repositories, particularly IADC. • Developing methodologies based on the large volume of new data, with a focus on cloudiness. 41 Photos: Instrument location and details of instrument mounting on the aft side of Le Commandant Charcot. 48 For Land ice, one goal is to develop a comprehensive meltwater discharge in situ observation network and a high-resolution modelling framework for Arctic glaciers and ice caps. This aligns with current EU-funded projects, like LIQUIDICE. Also, a collaborative framework for harmonisation of data for Arctic glaciers and ice sheets should be developed for improved integration of national and international initiatives. In the marine domain, improved coordination of plans for scientific monitoring and dedicated campaigns can be achieved through open annual meetings between actors operating Arctic Ocean scientific expeditions, moorings and sea ice platforms. Ideally, such meetings should have multi-year planning horizons to allow for upcoming project proposals to adjust to known programmes and plans. The cost of deploying marine and sea ice observing infrastructure is often larger than the purchasing cost - improved coordination can help minimize the overall cost. Along similar lines, EU-PolarNet 2 (Lymer et al. 2024) recommended further development of international agreements for sharing national infrastructures, to facilitate international access and exchanges between polar observatories. Practical actions suggested for implementing these recommendations include extending the use of catalogues such as the Registry of Polar Observing Networks (RoPON) and the Polardex interactive polar infrastructure registration database. In this context, the GOOS and SAON supported establishment of an Arctic Ocean Regional Alliance (ArORA), currently undertaken by the ArORA Task Team, is vital for bringing together and supporting coordinated Arctic Ocean observing efforts. Future observational systems will need to realize a larger proportion of integrated measurements of physical, biological and geochemical parameters compared to earlier setups, for relating changes in the different systems to causes and impacts in the others. It is important to continue and expand the air pollution observation network, especially in the Arctic region (north of 65°N), to improve the knowledge on air pollution in remote areas and increase the geographical extent of the AURORAE service. The analytical capabilities of the in situ monitoring stations must be developed, to provide more data on additional atmospheric key pollutants, allowing development of more comprehensive forecast models. The CS Polar Roadmap (Duchossois et al., 2024) highlights the importance of engaging local populations through citizen science to strengthen polar monitoring and support inclusive decisionmaking. Outreach and demonstration projects play a key role in raising awareness and encouraging participation. Several of the pilot Arctic Services developed within Arctic PASSION (WP4) exemplify this approach. As part of the implementation phase of the Wildfire SAV [2.3] a mobile phone application will be developed to collect terrain moisture observations from individuals walking in nature, contributing to wildfire-related moisture monitoring. A goal for the INFRA Wildfire Service [2.4], is to increasingly involve local communities, rights-holders and end users in the development of the service. Another example is the Lake Ice Service for Arctic Climate and Safety [2.8], which integrates community-based real-time reporting of ice conditions directly from the field, making the service more responsive and contextually relevant. Overall, the Arctic Services developed in the project are grounded in increased engagement and enhanced exchange of knowledge and information with local communities. Each of them represents meaningful contributions to Arctic monitoring that merit continued development. 5.3.2. Coordination across organizational structures Efforts to synthesise research and integrate observations from diverse knowledge systems should be supported to sustain data use across different observatories and observational approaches. Different stakeholders should be brought closer together to increase the use of variables or samples 49 of special importance for certain user groups. The work on FAIR and CARE data handling should be continued to improve the usability and accessibility of collected data and ensure that data collected in the Arctic is used and shared in accordance with the rights holders. Hence, data management that enables identification, harvesting and use of data across storage platforms should always be encouraged. For the marine domain, closer collaboration is encouraged between the in situ, remote sensing and modelling communities to optimize the availability of data for validation, evaluation and model input. At the same time, digital tools such as numerical models and geostatistics can help fill spatial and temporal gaps in the often irregular nature of in situ observations. This dual benefit aligns with the call for better integration of complementary capabilities by INTAROS (Sandven et al., 2021). Regular international network meetings are necessary within the sea ice buoy community to aid sharing information on systems design and setup, data processing/interpretation, as well as deployment strategies and opportunities. Such networking could help to establish a shared information and planning tool for upcoming expeditions that allow deployment of autonomous systems. Synergies with existing portals and technical solutions should be explored for optimization, and to improve cross-cutting collaborations between users of similar infrastructure. Long-term, international agreements on observational contributions to pan-Arctic observatories, such as the DBOs, should be developed. Observations should be optimized to detect changes, including societal use and nature conservation needs and harmonised across sites to facilitate comparison but also capture site specific features. Active links between research activities and existing observational structures should be promoted, as they will provide temporal and spatial context to new observations. As part of the Baffin Bay Distributed Biological Observatory, the established Community Based Monitoring in Qaanaaq should continue to evolve and maintain the core monitoring activities in collaboration with the local community, for community relevant contexts and needs. The connection across the North Water Polynya, between the Qaanaaq and Grise Fjord CBM initiatives, is expected to grow through collaborative monitoring efforts. The CBM pilot developed under Arctic PASSION aims to evolve into Pikialasorsuami Nasiffik, a locally driven science hub where researchers can engage with the community to present plans, request assistance and share results while the community can express science needs and propose involvement in future activities. 5.4. Long-term sustainability The lack of sustained, internationally coordinated funding, combined with the high operational costs of Arctic in situ observations, makes it challenging to maintain comprehensive long-term monitoring programmes. This is especially true in the central Arctic Ocean and at remote land sites. Voluntary coordination efforts among key actors, though often intermittent and project-dependent, can improve efficiency and cost-effectiveness but they do not solve the fundamental lack of sustained funding schemes. This demand of sustainability cannot be addressed only by the observing community but must also be actively supported by users and funders of such observational data, and funding means need to be better aligned to fit the purpose. The Arctic PASSION Funding Recommendations towards a Sustained Arctic Observing System (D7.1) outline the need for better coordinated, integrated, useful and equitable Arctic Observing System. The recommendations are based on input from across all Work Packages of the project. The responses were grouped into three categories: Coordination and governance, Observations, and Data. Longterm funding emerged as a central requirement — not only for maintaining long-term monitoring, 50 but also as a prerequisite for developing observation systems that respond to societal needs and for critical data gaps in cryosphere science. INTAROS (Sandven et al., 2021) emphasized the need for stronger collaboration among initiatives, institutions, organizations, and nations to secure long-term funding for the establishment and operation of observing systems essential to fulfilling the Joint Statement of Ministers (ASM, 2021). Enhanced collaboration should also aim to support the development of a holistic data ecosystem that includes community-based monitoring and citizen science. Equally important is to ensure transfer of knowledge and expertise through capacity-building activities in relevant observation methods, technologies, and procedures, across generations and genders. To expand the usefulness of several services developed in Arctic PASSION and enhance their socioeconomic benefits, continuous engagement and collaboration with local communities, authorities, and citizens is crucial. Sustaining this engagement requires dedicated, long-term funding. National Meteorological and Hydrological Services within WMO provide much data at low and mid latitudes, but most of the data in the Polar regions come from the research community. This community should be encouraged to improve the real time access to data. Such sharing of data with operational agencies would be highly beneficial but also calls for alternative, sustainable business models for the research community. Collaborative networks like the marine DBOs serve to optimize observational efforts towards common key elements and counteract fragmentation. The facilitation of diverse meeting places in general, as well as support to early career professionals through travel funds, mobility grants and research projects, is needed to leverage scientific outcomes, and expand the international exchange and training opportunities across observatories and programmes. In the longer term, sustainable support is essential to create and operate a pan-Arctic framework that unites Arctic ocean observing efforts. A current initiative by the ArORA Task Team aims to establish an Arctic Ocean Regional Alliance that would harness the collective potential of national and international initiatives, linking observations from coastal zones to continental shelves and the central Arctic Ocean. Along the same lines, EU-PolarNet 2 (Lymer et al. 2024) put emphasis on the need for continued investments necessary for updating, sustaining, and maintaining the existing polar stations, research vessels and infrastructures. The use and being of such existing polar infrastructure could be further optimized through enhanced collaboration between infrastructure managers, vendors and researchers to enhance standardisation. As a final, fundamental recommendation, we propose giving higher priority to long-term funding of national and institutionally driven time series collection, alongside collaborative responsibilities and timely data sharing. A larger share of the funding currently spent on Arctic data collection should be allocated to long-term, internationally coordinated efforts. This is essential to ensure consistent, highquality observations of essential variables and to effectively monitor and respond to rapid climate and environmental change. 51 Appendix 1. References Arctic PASSION online sources New datasets and online data portals and tools: https://arcticpassion.eu/data/ Developed Arctic Services: https://arcticpassion.eu/wp/wp4/; https://arcticpassion.eu/arcticwindow/services Thematic Factsheets: https://arcticpassion.eu/groups/FACTSHEETS/ Arctic PASSION reports D1.1 Mustonen T, Mustonen K, and Roto J (2022). Report on missing elements for an improved Arctic observing system. Arctic PASSION Deliverable 1.3. Zenodo, https://doi.org/10.5281/zenodo.14956338. D1.2 Matero I, Sevestre H, Lihavainen H, Larsen JR, Veijola K, Murray M, Strahlendorff M, and Wells T (2025). The definition for the pilot set of Essential Arctic Variables. Arctic PASSION Deliverable 1.2. Zenodo, https://doi.org/10.5281/zenodo.17534236. D1.3 Nikolopoulos A, and Sundfjord A (2024) Report on development of website with protocols, planning and reporting tools for the Atlantic-Arctic Distributed Biological Observatory network, Arctic PASSION Deliverable 1.3, Zenodo, https://doi.org/10.5281/zenodo.14956380. D1.4 Godøy Ø (2024). Report on WMO GTS datasets made available for non-GTS connected users and on new datasets ingested into WMO GTS based on user requirements. Arctic PASSION Deliverable 1.4, Zenodo, https://doi.org/10.5281/zenodo.14956388. D1.5 Li T, Bamber J, Igneczi A (2024). Demonstration of ALI monitoring capabilities based on existing satellite and in situ services, Zenodo, https://doi.org/10.5281/zenodo.[ref not yet available] D1.6 Danish Meteorological Institute, Dybkjær G, Suhr M, Kolbe W, Singha S, Jensen A, Gierisch A, Kreiner M, Wulff T, Mortensen N, Olsen S, Ribergaard M, and Eastwood S (2025). FRM Surface Temperature Datasets. Arctic PASSION Deliverable 1.6, Zenodo. https://doi.org/10.5281/zenodo.16982595. D1.7 Sundfjord A, Kanzow T, Foss Ø, Nicolaus M, Sennechael N, Tomasz PK, Granskog M, Preußer A, von Appen W-J, and Nikolopoulos A (2025). New near-real time data and time series from drifting observatories and new long-term moorings in the interior Arctic. Arctic PASSION Deliverable 1.7, Zenodo, https://doi.org/10.5281/zenodo.16880626. D4.3 Vitale V (2024). Documentation on the INFRA service and its functionalities (Versjon 1), Arctic PASSION Deliverable 4.3, Zenodo, https://doi.org/10.5281/zenodo.17161102. D4.7 Irrgang A (2024). GTN-P permafrost observing best practices for WMO Guide (T4.2). Arctic PASSION Deliverable 4.7, Zenodo, https://doi.org/10.5281/zenodo.14963159. D4.12 Vitale V (2025). Report on development of INFRA as an operational service, new functionalities and performances (Version 1). Zenodo. https://doi.org/10.5281/zenodo.17508229. D4.13 Crotti I, Cuzzucoli A, DeMarchi D, Ramalli E, Selmi L, Trandafir I, PASINI A, and Dobricic S (2025). AURORAE service: Model description and forecast delivery for the local atmospheric pollution forecasts, Arctic PASSION Deliverable 4.13, Zenodo, https://doi.org/10.5281/zenodo.15864354. D6.3 Larsen JR, Bradley AC, Waigl C, Wayner H, Lihavainen H, Matero I, Veijola K, Divine L, Rudolf M, Murray M, Strahlendorff M, Palarto NJ, Starkweather S, and Wells T (2025). Report on SAON Progress in ROADS, Arctic PASSION Deliverable 6.3, Zenodo, https://doi.org/10.5281/zenodo.15856556. D7.1 Grosfeld L, and Rachold V (2025). Policy support for the Arctic Science Funders Forum, Arctic PASSION Deliverable 7.1, Zenodo, https://doi.org/10.5281/zenodo.15364667. D8.2 Karcher M, Wilkinson J, and Sundfjord A (2025). Final Synthesis and Roadmap for further evolution of the pan-AOSS. 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Report on the gaps in terms of in situ observations in order to improve Polar Regions monitoring and forecasting capabilities, KEPLER project (Key Environmental monitoring for Polar Latitudes and European Readiness), Deliverable D3.1. [Available at https://kepler-polar.eu/] WMO (2022). The 2022 GCOS Implementation Plan. GCOS-244, GOOS-272 of the WMO Global Climate Observing System (GCOS) programme. [Available at https://library.wmo.int/idurl/4/58104] 55 Appendix 2. Abbreviations, Acronyms and Links Arctic PASSION EU H2020 project Pan-Arctic Observing System of Systems: Implementing Observations for Societal Needs https://arcticpassion.eu/ grant agreement No. 101003472 Descriptions of the project’s ten Work Packages (WPs) https://arcticpassion.eu/wp The project’s Data Website for download of many of the services and data products https://arcticpassion.eu/data/ ACDD Attribute Convention for Dataset Discovery https://wiki.esipfed.org A-DBO Atlantic-Arctic Distributed Biological Observatory https://arcticpassion.eu/adbo ALEX Arctic Landscape Explorer service See [2.6], https://alex.awi.de AMAP Arctic Monitoring and Assessment Programme https://www.amap.no/ AOS Arctic Observing Summit https://arcticobservingsummit.org ArCS I & II Arctic Challenge for Sustainability projects https://www.nipr.ac.jp/arcs2/e/index.html Arctic GEOSS ARCTIC GEOSS Global Earth Observations for the Arctic https://arcticgeoss.org/ Arctic ROOS EuroGOOS Arctic Regional Ocean Observing System arctic.eurogoos.eu Arctic Seas portal Snowchange Arctic Seas Portal http://www.arcticseas.org, https://arcticpassion.eu/arcticwindow/services ARICE Arctic Research Icebreaker Consortium https://arice-h2020.eu/ grant agreement 730965 ArORA TT Arctic Ocean Regional Alliance Task Team https://goosocean.org/arora-task-team ASM Arctic Science Ministerial https://asm3.org AURORAE Air Quality Forecast for Arctic Communities See [4.1]; https://aurorae.azurewebsites.net BGOS Arctic Observing Network (AON) Beaufort Gyre Observing System (BGOS) https://www2.whoi.edu/site/beaufortgyre/ https://arcticdata.io/catalog/portals/beaufortgyre BUFR WMO Binary Universal Form for the Representation of meteorological data https://community.wmo.int C3S Copernicus Climate Change Service https://climate.copernicus.eu C3S Ice TAC Copernicus Climate Change Service Thematic Assembly Centre for Sea Ice https://marine.copernicus.eu/about/producers/se aice-tac CAMS Copernicus Atmosphere Monitoring Service https://atmosphere.copernicus.eu CARE Collective Benefit, Authority to Control, Responsibility, and Ethics; Data principles for Indigenous Data Governance https://www.gida-global.org/ CBM Community Based Monitoring https://arcticcouncil.dspace7.dspaceexpress.com/handle/11374/141 CEMS Copernicus Emergency Management Service https://emergency.copernicus.eu CF Climate and Forecast metadata convention https://cfconventions.org CLMS Copernicus Land Monitoring Service https://land.copernicus.eu CMEMS Copernicus Marine Environment Monitoring Service https://marine.copernicus.eu/ CMDS CMS Copernicus Marine Data Store https://data.marine.copernicus.eu/product/ARCTI C_ANALYSISFORECAST_PHY_002_001/description CMS Copernicus Marine Service https://marine.copernicus.eu/ CWFIS Canadian Wildland Fire Information System https://cwfis.cfs.nrcan.gc.ca/ 56 DBO Distributed Biological Observatory https://dbo.cbl.umces.edu (Pacific Arctic Sector) DMI HYCOM CICE model North Atlantic - Arctic Ocean coupled HYCOM ocean CICE sea ice model at DMI https://ocean.dmi.dk/models/hycom.uk.php ECMWF S2S European Centre for Medium-Range Weather Forecasts project for Sub-seasonal to seasonal (S2S) prediction https://www.ecmwf.int/en/research/projects/s2s EAV, ECV Essential Arctic Variables, Essential Climate Variables https://gcos.wmo.int/site/global-climateobserving-system-gcos/essential-climate-variables EEA European Environmental Agency https://www.eea.europa.eu EMODnet European Marine Observation and Data Network https://emodnet.ec.europa.eu Expert Panel ROADS Expert Panels (EPs) https://roadsadvisorypanel.org/expert-panel ERC European Research Council https://erc.europa.eu ESA European Space Agency https://www.esa.int EU European Union https://european-union.europa.eu EU PolarNet Co-ordinating and Co-designing the European Polar Research Area https://eu-polarnet.eu EuroGOOS European Global Ocean Observing System https://eurogoos.eu CBM Event Database Event Database of CBM Using Oral Histories, Indigenous knowledge and local knowledge https://www.arcticseas.org/ FAIR Findable Accessible Interoperable Reusable Data principles; https://doi.org/10.1038/sdata.2016.18 FPIC The practice of Free, Prior and Informed Consent https://www.ohchr.org/en/indigenous-peoples FRM Fiducial Reference Measurements See [3.2] G3W Global Greenhouse Gas Watch https://g3w.wmo.int/ GCOS Global Climate Observing Systems https://gcos.wmo.int/ GOOS Global Ocean Observing System https://goosocean.org GRIB WMO GRIdded Binary (model output and forecasts) https://community.wmo.int GrIS-GEUS Greenland Ice Sheet mass balance service https://doi.org/10.22008/FK2/OHI23Z GTN-P Global Terrestrial Network for Permafrost https://gtnp.arcticportal.org/ GTS WMO Global Telecommunication System https://community.wmo.int/en/activity-areas GWIS Global Wildfire Information Service https://gwis.jrc.ec.europa.eu HiAOOS EU Horizon Europe project High Arctic Ocean Observing System project https://hiaoos.eu grant agreement No.101094621 HR-WSI Copernicus Higher-Resolution Water Snow Ice data https://www.copernicus.eu/en/access-data IASC International Arctic Science Committee https://iasc.info IASC MWG IASC Marine Working Group https://iasc.info/working-groups/marine ICC Inuit Circumpolar Council-Alaska https://iccalaska.org IICWG International Ice Charting Working Group https://nsidc.org/iicwg Ice Logistics Portal, ILP The Global Ice Charts and Sea Ice Information Portal https://www.icelogistics.info IMB Ice Mass Balance buoys See [3.2] IMO International Maritime Organization https://www.imo.org INFRA Integrated Fire Risk Management web service See [2.4]; https://www.programmaricercaartico.it/en/integrated-fire-risk-management-infraservice 57 INTAROS EU H2020 project INTegrated ARctic Observation System https://intaros.nersc.no grant agreement No. 727890 INPA, INTERACT International Network for Terrestrial Research and Monitoring in the Arctic Non-Profit Association https://www.interactassociation.org IST Ice Surface Temperature See [3.2] K-AWARE Korea-Arctic ocean WArming & Response of Ecosystem project https://kopri.re.kr KEPLER EU H2020 project Key Environmental monitoring for Polar Latitudes and European Readiness https://kepler-polar.eu grant agreement No. 821984 Lake Ice Service Lake Ice component in the Tarkka service and Syke's Earth Observation See [2.8]; https://tarkka.syke.fi/eo-tarkka/map/ LIQUIDICE LinkIng and QUantifying the Impacts of climate change on inlanD ICE project https://eu-liquidice.eu/ MQTT Message Queuing Telemetry Transport standard messaging protocol https://mqtt.org NABOS Nansen and Amundsen Basins Observational System https://uaf-iarc.org/nabos NSF US National Science Foundation https://www.nsf.gov PANGAEA Data Publisher for Earth & Environmental Science https://www.pangaea.de Polardex interactive polar infrastructure database https://polardex.org POLARIS IMO Polar Operational Limit Assessment Risk Indexing System https://www.imo.org RIO POLARIS Risk Index Outcome See [3.3] ROADS Roadmap for Arctic Observing and Data Systems https://roadsadvisorypanel.org RoPON The Registry of Polar Observing Networks https://polarobservingregistry.org SAON, SAON data portal Sustaining Arctic Observing Networks https://arcticobserving.org, https://data.arcticobserving.org SAS Synoptic Arctic Survey https://synopticarcticsurvey.w.uib.no SAV Shared Arctic Variable https://roadsadvisorypanel.org; Bradley et al. 2023 SIOS Svalbard Integrated Arctic Earth Observing System https://sios-svalbard.org TRUSTED Towards fiducial Reference measUrements of Sea-Surface Temperature by European Drifters https://www.eumetsat.int/TRUSTED WIS, WIS 2.0 WMO Information System https://community.wmo.int/en/activity-areas/wis WMO World Meteorological Organisation https://wmo.int