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Open access to scientific data is increasingly recognized as critical to fostering scientific progress, trustworthy and reproducible science, global information equity, and evidence-based policymaking. It requires scientists to not only share their data, but to share in such a way that the data have high utility for later users. The FAIR data principles define a set of characteristics for making data “findable, accessible, interoperable, and reusable” (Wilkinson et al., 2016). Training scientists, particularly early-career scientists, on these principles can improve the volume and quality of open science data. 

The “Accessible Oceans” pilot project aims to inclusively design auditory displays that support perception and understanding of ocean data in informal learning environments (ILEs). The project’s multi-disciplinary team includes expertise from all related fields — ocean scientists, dataset experts, a sound designer with specialization in data sonification, and a learning sciences researcher. In addition, the PI is blind and provides a crucial perspective in our research. We describe the sound design of informative sonifications and respective auditory displays based on iterative design with user input at each stage, including from blind and low-vision (BLV) students, their teachers, and subject-matter experts. We discuss the importance of framing data sonifications through an auditory presentation of contextual information. We also report on our latest auditory display evaluation using Auditory Interface UX Scale (BUZZ) surveys at three ILE test sites. These responses further affirm our auditory display design developments. We include access to the auditory displays media and lessons learned over the course of this multi-year NSF-funded Advancing Informal Stem Learning (AISL) grant https://accessibleoceans.whoi.edu/ 

IntroductionA defining aspect of the Intergovernmental Panel on Climate Change (IPCC) assessment reports (AR) is a formal uncertainty language framework that emphasizes higher certainty issues across the reports, especially in the executive summaries and short summaries for policymakers. As a result, potentially significant risks involving understudied components of the climate system are shielded from view. MethodsHere we seek to address this in the latest, sixth assessment report (AR6) for one such component—the deep ocean—by summarizing major uncertainties (based on discussions of low confidence issues or gaps) regarding its role in our changing climate system. The goal is to identify key research priorities to improve IPCC confidence levels in deep ocean systems and facilitate the dissemination of IPCC results regarding potentially high impact deep ocean processes to decision-makers. This will accelerate improvement of global climate projections and aid in informing efforts to mitigate climate change impacts. An analysis of 3,000 pages across the six selected AR6 reports revealed 219 major science gaps related to the deep ocean. These were categorized by climate stressor and nature of impacts. ResultsHalf of these are biological science gaps, primarily surrounding our understanding of changes in ocean ecosystems, fisheries, and primary productivity. The remaining science gaps are related to uncertainties in the physical (32%) and biogeochemical (15%) ocean states and processes. Model deficiencies are the leading cited cause of low certainty in the physical ocean and ice states, whereas causes of biological uncertainties are most often attributed to limited studies and observations or conflicting results. DiscussionKey areas for coordinated effort within the deep ocean observing and modeling community have emerged, which will improve confidence in the deep ocean state and its ongoing changes for the next assessment report. This list of key “known unknowns” includes meridional overturning circulation, ocean deoxygenation and acidification, primary production, food supply and the ocean carbon cycle, climate change impacts on ocean ecosystems and fisheries, and ocean-based climate interventions. From these findings, we offer recommendations for AR7 to avoid omitting low confidence-high risk changes in the climate system. 

Look at a graph of oceanographic data. How would you convey the information only using sound? This is the challenge addressed by the US National Science Foundation-funded “Accessible Oceans” project, which seeks to increase access to ocean data in informal learning environments like museums, science centers, and aquariums. Quantitative information in these settings is almost always conveyed with visual displays. For audience members who are blind or have low vision, or those with data illiteracy or innumeracy, these displays remain inaccessible. In this article, we discuss our interdisciplinary project using an inclusive human-centered design process to develop auditory displays that support learning and understanding of ocean science in informal learning environments. We share information about our project and takeaways for inclusive auditory display design, hoping to inspire others to examine the accessibility of their own work. 

The quasi-geostrophic (QG) equations play a crucial role in our understanding of atmospheric and oceanic fluid dynamics. Nevertheless, the traditional QG equations describe ‘dry’ dynamics that do not account for moisture and clouds. To move beyond the dry setting, precipitating QG (PQG) equations have been derived recently using formal asymptotics. Here, we investigate whether the moist Boussinesq equations with phase changes will converge to the PQG equations. A priori , it is possible that the nonlinearity at the phase interface (cloud edge) may complicate convergence. A numerical investigation of convergence or non-convergence is presented here. The numerical simulations consider cases of ϵ = 0.1 , 0.01 and 0.001, where ϵ is proportional to the Rossby and Froude numbers. In the numerical simulations, the magnitude of vertical velocity w (or other measures of imbalance and inertio-gravity waves) is seen to be approximately proportional to ϵ as ϵ decreases, which suggests convergence to PQG dynamics. These measures are quantified at a fixed time T that is O ( 1 ) , and the numerical data also suggests the possibility of convergence at later times. This article is part of the theme issue ‘Mathematical problems in physical fluid dynamics (part 2)’. 

Abstract Potential vorticity (PV) is one of the most important quantities in atmospheric science. In the absence of dissipative processes, the PV of each fluid parcel is known to be conserved, for a dry atmosphere. However, a parcel's PV is not conserved if clouds or phase changes of water occur. Recently, PV conservation laws were derived for a cloudy atmosphere, where each parcel's PV is not conserved but parcel‐integrated PV is conserved, for integrals over certain volumes that move with the flow. Hence a variety of different statements are now possible for moist PV conservation and non‐conservation, and in comparison to the case of a dry atmosphere, the situation for moist PV is more complex. Here, in light of this complexity, several different definitions of moist PV are compared for a cloudy atmosphere. Numerical simulations are shown for a rising thermal, both before and after the formation of a cloud. These simulations include the first computational illustration of the parcel‐integrated, moist PV conservation laws. The comparisons, both theoretical and numerical, serve to clarify and highlight the different statements of conservation and non‐conservation that arise for different definitions of moist PV. 

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