The observed decline in Arctic sea ice is projected to continue, opening shorter trade routes across the Arctic Ocean, with potentially global economic implications. Here we quantify, using CMIP5 global climate model simulations calibrated to remove spatial biases, how projected sea ice loss might increase opportunities for Arctic-transit shipping. By mid-century for standard Open Water vessels, the frequency of navigable periods doubles, with routes across the central Arctic becoming available. A sea ice – ship speed relationship is used to show that European
routes to Asia typically become 10 days faster via the Arctic than alternatives by mid-century, and 13 days faster by late-century, while North American routes become 4 days faster. Future greenhouse-gas emissions have a larger impact by late-century; the shipping season reaching 4-8
months in RCP8.5, double that of RCP2.6, both with substantial inter-annual variability.
Moderately ice-strengthened vessels likely enable Arctic transits for 10-12 months by late century.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2016GL069315

Sea ice decline and 21st century trans‐Arctic shipping routes

Abstract The growing importance of data in society in general and scientific domains in particular, mirrored in the Open Data initiative and in the advent of eScience, requires public, school and academic libraries to contribute to both data and information literacy, as part of their mission to further knowledge and innovation in their respective fields of action. No specific library standards have been proposed to date, however, and most research studies conducted adopt a partial view of data literacy, stressing only the components needed in any given context. The present paper aims to contribute to the advancement of data literacy with the proposal of a set of core competencies and contents that can serve as a framework of reference for its inclusion in libraries’ information literacy programs. The various definitions of data literacy are discussed, the coverage of the competencies listed in information literacy standards is described, and the competencies considered in the experiments conducted to date in education and libraries are identified. The conclusion drawn is that the model proposed can favour the development of data literacy support resources and services. Topics for further research are also specified.

/pdf/incorporating-data-literacy-into-information-literacy-2holoxvfai.pdf

Incorporating Data Literacy into Information Literacy Programs: Core Competencies and Contents

This study suggests that the Pacific Decadal Oscillation phase influences how much sea-ice loss contributes to Arctic amplification, with warming being larger during the negative phase with greater sea-ice loss.

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Contribution of sea-ice loss to Arctic amplification is regulated by Pacific Ocean decadal variability

. Nineteen subpopulations of polar bears (Ursus maritimus) are found throughout the circumpolar Arctic, and in all regions they depend on sea ice as a platform for traveling, hunting, and breeding. Therefore polar bear phenology – the cycle of biological events – is linked to the timing of sea-ice retreat in spring and advance in fall. We analyzed the dates of sea-ice retreat and advance in all 19 polar bear subpopulation regions from 1979 to 2014, using daily sea-ice concentration data from satellite passive microwave instruments. We define the dates of sea-ice retreat and advance in a region as the dates when the area of sea ice drops below a certain threshold (retreat) on its way to the summer minimum or rises above the threshold (advance) on its way to the winter maximum. The threshold is chosen to be halfway between the historical (1979–2014) mean September and mean March sea-ice areas. In all 19 regions there is a trend toward earlier sea-ice retreat and later sea-ice advance. Trends generally range from −3 to −9 days decade−1 in spring and from +3 to +9 days decade−1 in fall, with larger trends in the Barents Sea and central Arctic Basin. The trends are not sensitive to the threshold. We also calculated the number of days per year that the sea-ice area exceeded the threshold (termed ice-covered days) and the average sea-ice concentration from 1 June through 31 October. The number of ice-covered days is declining in all regions at the rate of −7 to −19 days decade−1, with larger trends in the Barents Sea and central Arctic Basin. The June–October sea-ice concentration is declining in all regions at rates ranging from −1 to −9 percent decade−1. These sea-ice metrics (or indicators of habitat change) were designed to be useful for management agencies and for comparative purposes among subpopulations. We recommend that the National Climate Assessment include the timing of sea-ice retreat and advance in future reports.

/pdf/sea-ice-indicators-of-polar-bear-habitat-5fdt7w11zp.pdf

Sea-Ice Indicators of Polar Bear Habitat

The Arctic is rapidly warming and experiencing tremendous changes in sea ice, ocean and terrestrial regions. Lack of long-term scientific observations makes it difficult to assess whether Arctic changes statistically represent a ‘new Arctic’ climate. Here we use five Coupled Model Intercomparison Project 5 class Earth system model large ensembles to show how the Arctic is transitioning from a dominantly frozen state and to quantify the nature and timing of an emerging new Arctic climate in sea ice, air temperatures and precipitation phase (rain versus snow). Our results suggest that Arctic climate has already emerged in sea ice. Air temperatures will emerge under the representative concentration pathway 8.5 scenario in the early- to mid-twenty-first century, followed by precipitation-phase changes. Despite differences in mean state and forced response, these models show striking similarities in their anthropogenically forced emergence from internal variability in Arctic sea ice, surface temperatures and precipitation-phase changes. The short observational record makes it difficult to gauge how unprecedented recent Arctic warming is. A multi-model large ensemble estimates a new Arctic climate has emerged for sea-ice extent. As the Arctic shifts from a primarily frozen state, temperature and precipitation follow within decades.

Extremes become routine in an emerging new Arctic

Researchers increasingly need to integrate the disposition, management, and curation of their data into their current workflows. However, it is not yet clear to what extent faculty and students are sufficiently prepared to take on these responsibilities. This paper articulates the need for a data information literacy program (DIL) to prepare students to engage in such an "e-research" environment. Assessments of faculty interviews and student performance in a geoinformatics course provide complementary sources of information, which are then filtered through the perspective of ACRL's information literacy competency standards to produce a draft set of outcomes for a data information literacy program.

/pdf/determining-data-information-literacy-needs-a-study-of-3mcm13jgs7.pdf

Determining Data Information Literacy Needs: A Study of Students and Research Faculty

This study uses model projections of the open water season (for 1920–2100) to investigate Arctic sea-ice decline. Nearshore regions began shifting from pre-industrial conditions in 1990, and human influence is projected to emerge in 2040. Sea ice impacts most of the Arctic environment, from ocean circulation and marine ecosystems to animal migration and marine transportation. Sea ice has thinned and decreased in age over the observational record1,2. Ice extent has decreased3. Reduced ice cover has warmed the surface ocean4, accelerated coastal erosion5,6 and impacted biological productivity7. Declines in Arctic sea-ice extent cannot be explained by internal climate variability alone and can be attributed to anthropogenic effects8,9. However, extent is a poor measure of ice decline at specific locations as it integrates over the entire Arctic basin and thus contains no spatial information. The open water season, in contrast, is a metric that represents the duration of open water over a year at an individual location10,11. Here we present maps of the open water season over the period 1920–2100 using daily output from a 30-member initial-condition ensemble of business-as-usual climate simulations12 that characterize the expansion of Arctic open water, determine when the open water season will move away from pre-industrial conditions (‘shift’ time) and identify when human forcing will take the Arctic sea-ice system outside its normal bounds (‘emergence’ time). The majority of the Arctic nearshore regions began shifting in 1990 and will begin leaving the range of internal variability in 2040. Models suggest that ice will cover coastal regions for only half of the year by 2070.

Mapping the future expansion of Arctic open water

As the quantity and complexity of scientific data expand, accessible interfaces for data manipulation and analysis are needed to support broad and efficient data use. The Isoscapes Modeling, Analysis, and Prediction (IsoMAP; http://isomap.org) Web-based geographical information system (GIS) gateway is an example of such a resource. Recently launched with support from the U.S. National Science Foundation (NSF) Division of Biological Infrastructure, IsoMAP enables analysis and integration of diverse light stable isotope and environmental data by a broad-based user community. It provides an intuitive, spatial interface that streamlines data analysis, modeling, and exploration in research ranging from greenhouse gas biogeochemistry to food science.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2012EO190002

Cyberinfrastructure for isotope analysis and modeling

The in-vitro and in-vivo temperature rises during MRI for a sample passive implant in the form of a metal rod of 8 mm diameter and 118 mm length in the right humerus were calculated with FDTD and the heat equation. The temperature rise in a phantom test was calculated for a background medium with electric properties specified in ASTM F2182–09 and for a medium with electrical properties of the cancellous bone that surrounds the implant. Scaled to local background SAR, in-vitro rises are greater for the bone. For a patient in the MRI coil with landmark in the torso and a whole body SAR of 2 W/kg, the calculated temperature rise after six minutes of RF power deposition was 1.3 °C for 64 MHz and 2.4 °C for 128 MHz. The numerical methods presented here could be extended to determine the temperature rises that would occur in the phantom and in the patient for other implants.

/pdf/calculation-of-heating-of-passive-implants-by-the-rf-e6r4zvt2qe.pdf

Calculation of heating of passive implants by the RF electromagnetic field in MRI

One aspect of the development of an e-infrastructure for research discovery that is often overlooked is the human element. Data is only as interoperable as the scientists who are willing to meet data standards and share their work with others. Information literacy in the data world has at least as many challenges as it does in the world of documents. For example, the provenance of data, who collected it, how they collected it, and whether and how it has been verified, are all very important factors for researchers to consider before incorporating external data into their analyses. With this in mind, the Purdue University Libraries and Earth and Atmospheric Sciences department partnered to offer a geoinformatics course to teach our next generation of scientists about the stores of data available for them to use and the power and limitations of networked tools and data structures to enhance the value and relevance of their own data, while fostering good data hygiene. Students will realize through handson activities why good data habits are critical to their professional success in the sciences. In this course, students follow a research project from the data gathering stage, through geospatial visualization and incorporation of external data sets, analysis of the combined data through workflow management software, comparison of results with data models, and, finally, curation of their data, culminating in its deposition in a disciplinary data repository, where it will be shared with and peer reviewed by classmates. The authors will describe how the goals and objectives of this course were determined and implemented and report findings from the pilot offering of this course. e-science instruction geoinformatics ENVIRONMENT AND LANDSCAPE Some time between January 2003 and March 2007 a revolution occurred. In 2003, the National Science Foundation (NSF) released their "Revolutionizing Science and Engineering Through Cyberinfrastructure Report of the National Science Foundation Blue-Ribbon Advisory Panel on Cyberinfrastructure" [Atkins, 2003] and led with a section titled "A Nascent Revolution" [Atkins, 2003, p. 9]. In some ways The Panel was referring to the same computer revolution most of the developed world is enjoying, but more specifically it is that current within the greater flood of more computers, more computation, and more automation in scientific research that brings with it previously impossible, vanguard methods of scientific inquiry. "New technology-mediated, distributed work environments are emerging to relax constraints of distance and time. These new research environments are linking together research teams, digital data and information libraries, high-performance computational services, scientific instruments, and arrays of sensors" [Atkins, 2003, p. 9]. In that trajectory of not only more computational power, not only more advanced systems, and not only more data, but more access to those resources, the Blue-Ribbon panel saw glimpses of a very cyber future in which, among other wholesale changes, "advanced computing is no longer restricted to a few research groups in a few fields...but pervades scientific and engineering research" [2003, p. 9] and in which "the classic two approaches to scientific research, theoretical/analytical and experimental/observational, have been extended to in silico simulation and modeling" [2003, p. 9]. In 2003, the origins of that future represented to the Panel "just the beginnings of a revolution" [2003, p. 10]. Well, the future is now. Or March 2007, rather, when NSF's Cyberinfrastructure Council published their "Cyberinfrastructure Vision for 21st Century Discovery" [2007]. In it, the NSF lays out a plan for directing and funding the initiatives designed to take the many and rapid advances in (mostly) large-scale computing architectures, communication and data transfer protocols and very large data storage capabilities and build from them a coordinated, integrated, interoperable cyberinfrastructure (CI) that, among other virtues, "serves as an agent for broadening participation and strengthening the nation's workforce in all areas of science and engineering" [The Council, 2007, p. 6]. Much of what NSF proposes is grid-level, that is, involving the supercomputing centers around the country and the TeraGrid that connects them at the research community. Yet they've taken care to acknowledge in their plan the fact that although e-infrastructure is an increasingly vital component of scientific research, these machines still require engineers, of sorts; scientists who can care for the data drawn from and fed into the electronic machines that produce or consume them. Just as much as high-end computing architectures must be relied upon to process and manipulate and share data, there is an equally important amount of human finesse that goes into the preparation, consumption, interpretation of and care for those data. The geoinformatics course described in this paper is an attempt by Library and cooperating Earth & Atmospheric Sciences faculty at Purdue University to address that niche within the emerging universe of cyberinfrastructure that will "both demand and support a new level of technical competence in the science and engineering workforce and in our citizenry at large" [The Council, 2007, p. 37]. So here we are again: barely re-energized from a fast and confusing decade in which librarians were spun dizzy and found clinging to a handful of retrenched values – information literacy among them – we are bracing for another, larger storm, the scale of which promises even greater challenges, both in magnitude and scale. Lest the horizon appear too bleak and foreboding for librarians trained at the kilobyte end of the spectrum or even weaned on the soft comfort of a paper catalog, there are two subcurrents within this greater rush toward a supercomputed future that provide more than a modicum of hope. Two little preservers bobbing between the swells. The first of these is NSF's own unequivocal statement that "in the future, U.S. international leadership in science and engineering will increasingly depend upon our ability to leverage this reservoir of scientific data captured in digital form" [The Council, 2007, p. 22]. And as such, "ongoing attention must be paid to the education of the professionals who will support, deploy, develop, and design current and emerging cyberinfrastructure" [The Council, 2007, p. 38]. Sharp-eyed librarians will recognize the tenets of their own professional tradition, if not themselves, in that utopian scenario. Without promising the job to any one profession, The Council leaves ajar the door to a long, fruitful future for librarians and their computer science friends. Work is being done on this front already, of course, but there is still another aspect of CI that librarians are finding to be ripe for the kind of attention a librarian is wont to pay an issue. The development of *informatics disciplines (where ‘*’ indicates any discipline one would care to mention), predating and contemporaneous to the march toward CI, has also enabled more and more opportunities for librarians, computer scientists, and like-minded domain scientists to recast the issues that either gird or inform CI (issues like data interoperability, semantic discovery and integration, longterm stewardship in decentralized systems) and attempt to wedge them into tight domain curricula. While bioinformatics is perhaps the best-known of all the *informatics branches, a younger, blossoming informatics, geoinformatics, is concerned with the geospatial elements of today's science. This means it is a remarkably fecund field for those interested in advancing both the systems and skills that will enable growing infrastructures to be even more capable of handling inherently and tangentially-geospatial datasets and applications. It is here, in this hotspot between CI and the semantic web and data futures and rapidly-developing, increasingly geospatially-savvy technologies, where The Libraries' and EAS' geoinformatics course intends to push on the "workforce" component of the NSF plan [The Council, 2007, ch. 5] and begin teaching our next generation of scientists about the stores of data available in online systems, the power and limitations of those networked tools and data structures, and the importance of good data hygiene. The remainder of this paper will outline and annotate the design of the course, followed by a brief summary of where the course fits into the greater efforts of the NSF to build CI and then major and minor initiatives and developments with geoinformatics teaching and scholarship. THE COURSE AT THE MEGABYTE LEVEL While the hope is that the students will soon be advancing projects that draw at will from countless distributed super data stores and running simulations with cpu cycles leeched from centers on multiple continents, the course itself takes place in a more limited sphere. The authors would be remiss not to address the building blocks of CI in favor of the more advanced systems being developed by researchers in the field. As such, the course begins with units on basic computing environments, including Unix-based operating system environments and database structures and operations. Students are exposed to the relational model, SQL query and function syntax, and various manipulations of data. Specifically geospatial flavors of data are then introduced, first as file-based raster and vector formats and then within the context of the geospatial database. Care is taken at each introduction to discuss primary uses of and sources for each of these data formats as well as the issues they raise for interoperability and storability. Following the introduction to data formats, several weeks are spent introducing Geographic Information Systems (GIS) to students, first in terms of its foundational concepts (data layering and interaction, the divestment of display from da

/pdf/creating-a-culture-of-data-integration-and-interoperability-mu9t5knqg4.pdf

Chris Miller

Papers

Determining Data Information Literacy Needs: A Study of Students and Research Faculty

Mapping the future expansion of Arctic open water

Cyberinfrastructure for isotope analysis and modeling

Calculation of heating of passive implants by the RF electromagnetic field in MRI

Creating a culture of data integration and interoperability: librarians and Earth Science Faculty collaborate on a geoinformatics course