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Deep-ocean observing is essential for informing policy making in the arenas of climate, biodiversity, fisheries, energy and minerals extraction, pollution, hazards, and genetic resources. The Deep Ocean Observing Strategy (DOOS), a UN Ocean Decade endorsed programme, is meeting with representatives from relevant international bodies and agreements to strengthen their interface with the deep-ocean science community, ensure that deep observing is responsive to societal needs, identify points of entry for science in policy making, and to develop relevant products for broad use. DOOS collaboration with the Environmental Systems Research Institute (Esri) facilitates this co-design. A DOOS policy liaison team is being formed to link the contacts, voices, and messaging of multiple deep-ocean networks and organizations in reaching international policy makers. The UN Ocean Decade will help to gain the ear of target communities, scale communication channels appropriately, minimize duplicative efforts, maximize limited resources, and organize inclusive and equitable public and private partners in deep-ocean science and policy.

 

Abstract The Deep Ocean Observing Strategy (DOOS) is an international, community-driven initiative that facilitates collaboration across disciplines and fields, elevates a diverse cohort of early career researchers into future leaders, and connects scientific advancements to societal needs. DOOS represents a global network of deep-ocean observing, mapping, and modeling experts, focusing community efforts in the support of strong science, policy, and planning for sustainable oceans. Its initiatives work to propose deep-sea Essential Ocean Variables; assess technology development; develop shared best practices, standards, and cross-calibration procedures; and transfer knowledge to policy makers and deep-ocean stakeholders. Several of these efforts align with the vision of the UN Ocean Decade to generate the science we need to create the deep ocean we want. DOOS works toward (1) a healthy and resilient deep ocean by informing science-based conservation actions, including optimizing data delivery, creating habitat and ecological maps of critical areas, and developing regional demonstration projects; (2) a predicted deep ocean by strengthening collaborations within the modeling community, determining needs for interdisciplinary modeling and observing system assessment in the deep ocean; (3) an accessible deep ocean by enhancing open access to innovative low-cost sensors and open-source plans, making deep-ocean data Findable, Accessible, Interoperable, and Reusable, and focusing on capacity development in developing countries; and finally (4) an inspiring and engaging deep ocean by translating science to stakeholders/end users and informing policy and management decisions, including in international waters. 

A description and assessment of the first release of the Arctic Subpolar gyre sTate Estimate (ASTE_R1), a data‐constrained ocean‐sea ice model‐data synthesis, is presented. ASTE_R1 has a nominal resolution of 1/3° and spans the period 2002–2017. The fit of the model to an extensive (O(10⁹)) set of satellite and in situ observations was achieved through adjoint‐based nonlinear least squares optimization. The improvement of the solution compared to an unconstrained simulation is reflected in misfit reductions of 77% for Argo, 50% for satellite sea surface height, 58% for the Fram Strait mooring, 65% for Ice Tethered Profilers, and 83% for sea ice extent. Exact dynamical and kinematic consistency is a key advantage of ASTE_R1, distinguishing the state estimate from existing ocean reanalyses. Through strict adherence to conservation laws, all sources and sinks within ASTE_R1 can be accounted for, permitting meaningful analysis of closed budgets at the grid‐scale, such as contributions of horizontal and vertical convergence to the tendencies of heat and salt. ASTE_R1 thus serves as the biggest effort undertaken to date of producing a specialized Arctic ocean‐ice estimate over the 21st century. Transports of volume, heat, and freshwater are consistent with published observation‐based estimates across important Arctic Mediterranean gateways. Interannual variability and low frequency trends of freshwater and heat content are well represented in the Barents Sea, western Arctic halocline, and east subpolar North Atlantic. Systematic biases remain in ASTE_R1, including a warm bias in the Atlantic Water layer in the Arctic and deficient freshwater inputs from rivers and Greenland discharge.