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This document provides a summary of sensors, platforms, and observing systems implemented during INTAROS field campaigns and presents technical recommendations based on experience gained from operating these components for collecting in situ observations during the project. This document is intended to: – Shortly summarize details of all individual sensors, platforms, and systems developed and deployed during INTAROS for collecting in situ measurements in the cryospheric, ocean, atmospheric and terrestrial domains, – Provide main recommendations for the technology used in INTAROS with the respect to become a component of a future sustained Arctic observing system, – Describe main limitations of technology used and recommendations to overcome these limitations to enable including this technology in a future observing system, – Overview other technical solutions which could better replace or complement technology used during INTAROS to provide similar set of observations for a future observing system, – Identify and describe cross-cutting technical recommendations based on recommendations for individual systems, – Summarize main challenges and achievements in implementing in situ observations in WP3, – Summarize main technical recommendations from WP3 for use in the INTAROS Roadmap for a future integrated Arctic observing system INTAROS has collaborated with many other field programs and projects which have contributed to the results in WP3. These programs and projects are listed in Annex A. A summary of platforms and sensors developed and implemented during INTAROS, including main challenges and final outcomes, is provided in Annex B.

This report gives an overview of the activities, results and impacts of INTAROS Work Package 6 (WP6). The aim of WP6 is to demonstrate how an integrated observation system can be of specific benefit for society at local, regional or pan-Arctic scale. Through WP6 we show the capability of an enhanced Arctic Observation System towards advancing the economic role of the Arctic by providing support for better-documented processes and better-informed decisions within key sectors such as shipping, petroleum, fishing, and tourism. Further, WP6 demonstrates how the Arctic Observation system may be applied to further develop the accuracy of climate models, improve the understanding of biogeochemical cycles and ecosystem functioning, enhance fisheries and environmental management, increase the level of preparedness towards natural hazards, and develop better management and decision making concepts for selected local communities. Through WP6 INTAROS demonstrates enhanced data search and retrieval, assimilation into models, validation of estimated and projected climate parameters, scientific analysis, decision-support and policy-making. Following a general introduction to INTAROS WP6, eight chapters summarize, for each topic covered, the main activities and results, data and models used, stakeholder/user benefits, and further development and exploitation of results. The topics span broadly and target very different end-user groups but they all share the same overall challenge: how to synthesize data across time and space from different sources, formats and scientific disciplines into aggregated synoptic data products that are relevant for end-users. The following topics are addressed: Improving skill of model predictions in the Arctic, Applying observations and models for environmental and fisheries management, Ice-ocean statistics, Remote sensing applications, Natural hazards in the Arctic, Greenhouse gas exchange in the Arctic, Case studies of community-based observing systems and Benefits of ocean observing for blue growth in the Arctic. The report then describes concrete showcases, software applications. Selected main results across WP6 are then presented, before the report ends with conclusions and perspectives.

This document is a result of INTAROS WP6 Task 6.5 on Arctic greenhouse gas exchange. The reported work rests upon results provided in WP3, more specifically tasks 3.1, 3.2 and 3.3. It synthesizes data stored in databases SOCAT and GLODAP and additional data from a Ferry box system crossing the Barents Sea opening and from Greenland fjords. To show the potential establishing long term monitoring of the carbon system variables as suggested in INTAROS, trends in ocean uptake and transport of carbon, ocean acidification and deoxygenation can be produced. Examples on synthesis of carbon system data are shown, with the aim of analyzing trends in ocean acidification in the Nordic Seas. The results reported by each of the marine science partners in Task 6.5 include: UiB. The main task has been to prepare for a comparison of pCO2 field extracted from 2018 data in the SOCAT database, and test a self-organising map technique, a type of artificial neural network that uses machine learning. This was implemented to estimate surface water pCO2values for the Barents Sea opening (10°E-30°E; 70°N-77.5°N). NIVA. A FerryBox system was equipped on M/S Norbjørn which made approximately 25-30 round-trip crossings per year through the Barents Sea Opening between Tromsø, Norway and Longyearbyen, Svalbard. The FerryBox system included several physical, chemical, and biological sensors. UA. In Greenland, measuring ocean CO2and carbonate chemistry is included in the Greenland Ecosystem Monitoring (GEM) Programme. Although these long-term programs provide essential time-series of change, the three sites do not cover the spatial variation across the vast Greenland coastal zone

This report presents a synthesis of the substantial assessment of Arctic observations within INTAROS.Since the assessed systems mainly belong to the European partners in the project, the assessment is unavoidably biased towards the European sector of the Arctic. The detailed results of the assessment can be found in previous deliverables (D2.1, D2.2, D2.4, D2.5, D2.7, D2.8 and D2.12). Also some higher-level recommendations for future improvements of Arctic observing are taken into account. The assessment addresses a substantial subset of Arctic observing systems, data collections and satellite products across scientific disciplines, also including some data repositories and a brief scientific gap analysis. In the assessment we analyzed sustainability, including funding, technical maturity and data handling for the entire chain from observation to users, including metadata procedures and availability of data. The gap analysis includes both technical characteristics, such as spatial and temporal coverage and resolution or accuracy, and a smaller set of scientific gap analyses where models and observations were used synergistically. Each characteristic of the observing systems were ranked from maturity 1 (lowest score) to maturity 6 (highest score) based on the results of the survey. In the synthesis wefirst ranked the systems according to general sustainability and then other characteristics were used. The range in maturity of sustainability varied from 1 to 6, and so did the other characteristics. A noteworthy result was that systems with high sustainability scores tended to score high also on other characteristics, such as data handling and technical maturity. Moreover, many systems with high maturity in sustainability, as well as in data handling and data availability, are supported by national or international monitoring or infrastructure programs. It is also noteworthy that several of these are mostly present at mid-latitudes, but poorly represented in the Arctic. For observations over Arctic land, the quality of some existing systems would benefit from being enhanced by new instruments or improved methods. As example, adequate observing of snow properties is problematic due to the high spatial variability of snow cover. While this also applies to hydrological observations, the situation improves as a result of large overarching international programmes. Observations of aerosols and some trace gases are also lacking in some specific regions. For the Arctic Ocean there is a lack of in-situ observing systems across all disciplines, which is connected to limited infrastructure provided by ships,icebreakers, and various types of autonomous observing platforms operating on sea ice with capacity to transfer data in near real-time.Subsurface observing systems such as bottom-anchored moorings and sea floor installations are robust and can operate autonomously over several year, but the data can only be delivered in delayed mode.In the atmosphere, icebreaker-based summer science expeditions provide the only reliable information on atmospheric vertical structure. While scientific expeditions likely provide the highest quality observations available for the Arctic Ocean region, the scores for almost all other aspects, sustainability as well as for data handling, in general and especially for atmospheric observations are among the lowest for vessel-based observations. Satellite observations provide the only possibility to obtain data with sufficient spatial and temporal coverage as well as resolution. Satellite data products have generally high score on data handling aspects, but for some data products the score on quality and uncertainty estimation is low. While retrieved temperature, and to a lesser extent, humidity at levels in the atmosphere is generally adequate for monitoring, satellite profiling of the atmosphere suffers from significant and seasonally varying biases and errors. Passive satellite sensing of clouds is also problematic; while some bulk products, such as cloud fraction, are useful during the sunlit season, more precise information, such as liquid water path, has high uncertainty as indicated by comparing different retrievals from the same set of sensors. In the dark season, when visible radiation channels vanish, most satellite cloud products are very unreliable. Regarding sea ice observations, there is significant uncertainty in the estimation of thickness and snow layer. There is also uncertainty in ice concentration in the summer season with melt-ponds on top of the ice. Traditionally, observation network assessments build on the network concept with a “comprehensive” level including all observations, a “baseline” level of an agreed subset of sustained observations, and a “reference” level, with observations adhering to specific calibrations and traceability criteria. An atmospheric example is the “comprehensive” global GCOS radiosounding network, and the “baseline” GUAN (GCOS Upper Air Network) and “reference” GRUAN (GCOS Reference Upper Air Network) networks. With the lack of in-situ observations and the logistical difficulties to deploy new stations, this concept does not work well in the marine part of the Arctic. In summary, we recommend to •Advance Arctic observing systems under national, international or regional programs that provide more sustainable funding than short-term research projects •Coordinate better between operational monitoring systems and research-funded observations, since both systems often use the same data and will have mutual benefit of collaboration •Improve the utilization of existing infrastructures on land and sea for more cost-effective collection of in situ data across multiple disciplines •Deploy more autonomous observing platforms in the sea ice areas for year-round operation and implement data collection from all types of ships operating in the Arctic ocean •Enhance the observing system on existing stations, including supersites, by use of new sensors and methods to validate satellite observations and support modelling and forecasting systems •Improve the exploitation of satellite data and coordinate better in situ and satellite observations for use in data assimilation, modelling and reanalyses •Clarify roles and responsibilities between data producers and managers and establish adequate funding mechanisms to support a functional data management system for multidisciplinary Arctic data., The reviewer's comments are not included in the present version, but are taken into account in the follow-up publications and in the Roadmap document (D1.10) developed during the final phase of the project.

A major goal of WP2: “Exploitation of existing observing systems” is to analyze strengths, weaknesses, gaps in spatial/temporal coverage, and missing monitoring parameters of the existing observation networks and databases in relation to the requirements from different user groups. This report is prepared to assess the existing ocean and sea ice observing systems in the Arctic, primary those where the INTAROS partners have responsibilities, but also where the partners contribute to larger, international observing systems. A core activity in the first 18 months of WP2 has been to conduct a survey where partners have responded to three sets of questionnaires: Questionnaire A: Existing Arctic In-situ Observing Systems, Questionnaire B: In-situ data collections, and Questionnaire C: Satellite Products. The survey has covered the scientific disciplines addressed in INTAROS, including atmosphere, ocean and terrestrial disciplines. The focus of the survey has been on in-situ observing systems, which is the priority of INTAROS, while satellite observing systems are treated more generally. This report therefore provides more details on selected in-situ systems and data collections than previous surveys and inventories. The reason or the detailed survey is that INTAROS will develop and demonstrate machine-to-machine operations between data repositories, following the FAIR data management principle (“Findable, Accessible, Interoperable and Re-usable”). An expected outcome of the survey is identification of selected observing systems and data collections that will be used further in the project, especially in WP5 (“Data integration and management”) and WP6 (“Application of iAOS towards stakeholders”). A major part of the report is a status description of in situ observing systems that are operated by the partners (Section 2). In INTAROS we identify a set of data collected from the same types of instruments and platforms over time to be an observing system (for example CTD surveys by ships, network of moorings, glider surveys). An observing system is often defined programmatically, where many institutions agree to establish and operate a network of instruments collecting a set of standard measurements and agree on sharing and exploitation of the data (for example International Arctic Buoy Programme). We have also analysed selected in-situ data collections, which can be part of one or more observing systems, or can be a stand-along data set. This analysis has been more detailed, addressing spatial/temporal coverage, uncertainty characterisation and metadata description. Requirements for observing systems is discussed in Section 3, where requirements to platforms, instruments and data management are central. For in-situ data, it is most important to focus on data at level 0 (raw data), level 1 and level 2 (physical, biological variables). These data are needed by different users along the downstream processing chain. Level 3 and level 4 data are gridded data, usually coming from satellite data and reanalysis fields, with input from in-situ data where these are available. Ocean modelling, reanalysis of forecasting are important users of data from level 2 and higher. Requirements to observational data are described in documents from programmes such as WMO, GCOS, Copernicus. Other users are marine ecosystem management, marine hazards and environmental monitoring. The assessment of the observing systems is described in Section 4. The assessment criteria include the spatial and temporal coverage of the data collection, scientific-technical support, sustainability of funding, data management, data usage, user feedback and others. The criteria are assessed on a scale from 1 (low maturity) to 6 (high maturity). The technical readiness level for all the instruments is generally high, showing that the observing systems are generally robust. For biogeochemical, observations there are fewer automated systems compared to physical observation systems. This is reflected in much less collection of biogeochemical data compared to physical data. For the ice-covered Arctic, there is a huge gap in collection in-situ measurements Uncertainty characterisation and metadata have mid to low maturity, while data management varies a lot. It is noteworthy that data management becomes a discipline in itself because the amount of data grows very rapidly. Therefore, data producers and data managers require experts and training to be able to do a good job. Recommendations to develop and maintain in-situ observing systems are described in Section 5. There are significant efforts to build observing systems by many countries, organisations and projects in the Pan-Arctic region. The amount of data collected in the Arctic is growing and there are numerous initiatives to establish observing systems for collection of data in different disciplines. Many recommendations deal with technology development, collaboration and organisation. However, the funding of the observing systems is to a large extent dependent on time-limited research and observation projects. These systems are therefore not sustainable and there is a high risk that many will not be maintained in the future. Some satellite Earth Observation programmes, such as Copernicus, have long-term perspectives and funding plans for 5 – 10 years, but most of the observations from in-situ systems on ground and in water have no long-term funding. It is therefore essential to develop and maintain long-term in-situ observing systems to monitor trends, and to detect natural variations and human impacts on climate, environment, livelihoods and societies. This requires mechanisms for long-term funding to be established. This report only provides preliminary results of the assessment, because organisations outside of the consortium are not yet included in the survey. It is therefore planned to update the assessment later in the project.

The detailed analysis of phenomena and observation requirements for the Arctic region given in this report reveals the following conclusions: • The Arctic is a region very sensitive to environmental changes. There is a very close interrelation and delicate balance between the five thematic areas investigated(atmosphere, terrestrial, cryosphere, sea ice and ocean),especially in relation to solar energy and radiation budget and hydrological cycle. This has a great impact on physical, chemical and biological processes in the area. • Due to the hostile environment, there is a great lack of basic observations in the Arctic,that can support scientific understanding of key processes. Most of the existing data are collected via time limited research projects. This lack of process knowledge is reflected in big errors in forecasting models –operational as well as climate. • It is therefore crucial to establish a sustained Integrated Arctic Observing System,that in the short time frame can increase fundamental scientific understanding of the complex and sensitive Arctic environment and in a longer time frame can secure a robust basis for decision making to the benefit of the people living in the Arctic, the environment, the broader international society, and commercial activities. • It is foreseen that a future Arctic observation system will rely heavily on satellite observations supplemented by more traditional in-situ platforms. Especially the ocean will use several other platforms such as ships, profiling floats, gliders, moorings, AUVs etc. to monitor the interior of the Arctic Ocean. • In all countries around the Arctic, there are community based observing systems that represent a strong potential for further development. Existing activities shall form part of the natural basis for a future more intensive and integrated sustainable Arctic Observing System. • A stakeholder workshop was held in Brussel on 5 May, organised by EuroGOOS, where status and challenges regarding development of Arctic Observing Systems were discussed. In addition to technical and logistical challenges, there are also organisational barriers to building and operating a multidisciplinary observing system. These issues will be addressed in follow-up workshops.