Deliverable 2.1 Report on present observing capacities and gaps: ocean and sea ice observing system

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.