ITS2.18/CL3.2.16

Communicating geosciences across linguistic and cultural borders is becoming increasingly important in our globalised world, and it is as important to have a globally coherent communication as it is to have global research infrastructure. In the context of geological hazards and the geological environment, we need a clear system that enables specialists and others to communicate effectively with each other. By using symbols and pictograms to represent geohazards, we can communicate these hazards clearly and efficiently. Certain hazard symbols are already in use across the globe, such as those for chemical or environmental hazards. In this project, we focus on the geological environment and geohazards, and much of the work is done within a UNESCO Geoscience Programme project 'Geoheritage for Resilience', using geoheritage sites as sites for communication and testing. The geological pictograms, or ‘geomojis’, bridge the gap between simple symbols and words, crossing language borders by representing concepts that we have identified as particularly important for understanding geohazards and risk. Our geomojis are based on the Global Framework for Geology (see Global and Planetary Change, 2018 - https://digitalcommons.mtu.edu/michigantech-p/427), also introduced during the IUGG centenary at UNESCO. This shows the context where they fit in the Earth system. We invite feedback on the geomojis that we have created, to consolidate geoscience knowledge and create a basic standardised set of symbols for all geological hazards. This standardisation of geohazard symbols could improve communication not only between specialists and non-specialists, but between geologists themselves. The global framework and geomojis will help us to think outside the box of our specialist environment. The geohazard pictograms can be used for geoscience communication in all forms, from hazard and risk publications to signage at geological sites. They can be adapted and modified for the local context and needs, while providing a central, and global, base for comparison. We plan to use the geomojis to accompany a multilingual glossary on geological hazard and risk terminology, a project that we hope will help international geoscience communication.

How to cite: Shires, C., Spitzl-Dupic, F., Grégoire, M., Martin, D., and van Wyk de Vries, B.: Geomojis – a Global Symbology for Communicating Geosciences, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9945, https://doi.org/10.5194/egusphere-egu21-9945, 2021.

Life on earth is closely linked to the availability of water and its variability. However, global change means that the demands placed on water resources are constantly increasing. According to the conclusions of the IPCC's 5th Assessment Report, it is likely that human activities have influenced the global water cycle since 1960. Satellite-based remote sensing of water-related parameters and operational data-assimilation services are becoming increasingly important to assess changes of the global water cycle as part of the essential climate variables (gcos.wmo.int). However, particularly over land or in the deep ocean where space-borne monitoring is not possible, in-situ data provide long-term records of changes in the various components of the hydrological cycle.

Global data centres, often operating under the auspices of UN agencies, collect and harmonise water data worldwide and make the global data sets available to the public again. Most of these relevant Global Data Centres are members of the Global Terrestrial Network of Hydrology (GTN-H) that operates under auspices of WMO and the Terrestrial observation Panel of Climate (TOPC) of the Global Climate Observing System GCOS. GTN-H links existing networks and systems for integrated observations of the global water cycle. The network was established in 2001 as a „network of networks“ to support a range of climate and water resource objectives, building on existing networks and data centres, and producing value-added products through enhanced communications and shared development. Since 2017 the GTN-H coordination is held by the International Centre for Water Resources and Global change (ICWRGC, operating under auspices of the UNESCO) aiming for a data and knowledge transfer between data providers, scientists and decision makers as well as between the different institutional bodies on UN-level inter alia the WMO, UNESCO, FAO, UNEP or GCOS.

We will demonstrate the state-of-the art of the global in-situ terrestrial water resources monitoring and draw a picture of a global water observation architecture.
As a major outcome we will share the most recent evaluation of global water storage and water cycle fluxes. Here, we assess the relevant land, atmosphere, and ocean water storage and the fluxes between them, including anthropogenic water use. Based on the assessment, we discuss gaps in existing observation systems and formulate guidelines for future water cycle observation strategies.

How to cite: Dietrich, S., Aich, V., Dorigo, W., Recknagel, T., Koethe, H., and Egglestone, S.: Global Terrestrial Network of Water Resources Observation Infrastructures, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10337, https://doi.org/10.5194/egusphere-egu21-10337, 2021.

AuScope is Australia’s National Geoscience Research Infrastructure Program. As outlined in is 2020-2030 10-year Strategy¹, AuScope seeks to provide a world-class research physical and digital infrastructure to help tackle Australia's key geoscience challenges, in particular, food and water sustainability, minerals and energy security, and mitigating impact from geohazards. These challenges tie in directly with the following United Nations (UN) Sustainable Development Goals (SDGs): SDG#6 (Clean Water and Sanitation); SDG#7 (Affordable and Clean Energy); SDG#8 (Decent Work and Economic Growth); SDG#9 (Industry, Innovation and Infrastructure); SDG#13 (Climate Action) and SDG#15 (Life on Land). 

The SDGs were set in 2015 by the UN General Assembly to be achieved by the year 2030. If the global research sector is to support achieving them, is a rethink required? Current practices tend to focus on building infrastructures in domain and/or national/regional and/or sector (research, government, private) and/or institutional/network silos. These are not necessarily enabling global interoperability, reuse and open sharing of data. For example, AuScope is building high-quality geoscience research data and software infrastructures that are at the heart of positioning Australia to meet these SDG challenges. Equivalent geoscience research infrastructures are also being built internationally (EPOS (Europe); EarthScope, EarthCube (USA)) and AuScope is looking for ways to interoperate more effectively with these.

Within the international geoscience community some interoperable networks are in place to enable global collaborations that share data and software (e.g., Earth System Grid Federation (ESGF), which develops software infrastructure for the management, dissemination, and analysis of model output and observational climate data; the Federation of Digital Seismograph Networks (FDSN) enables members to coordinate station siting and provide free and open data). However, these are the exceptions rather than the rule. 

None of the SDGs depend exclusively on geoscience data: all require integration with data from other domains, particularly from the social sciences and humanities. Some initiatives trying to assist data combination between the social sciences and the physical or environmental sciences are emerging (e.g., the Data Documentation Initiative - Cross Domain Integration (DDI-CDI)²; the CODATA/ISC Decadal programme on “Making data work for cross-domain grand challenges”³) , but traditional organizational and funding arrangements do not usually facilitate this. While there are exemplars of how to achieve integration of global domain and cross-domain research infrastructures and data sharing frameworks, we urgently need to leverage these to develop a roadmap that enables global integration of data and research infrastructures, both within the geosciences and beyond, to ensure sustainable production of data, products and services that support the realisation of the UN SDGs by 2030. In doing so, potentially the main tension will be to ensure that in enabling the broader, global transdisciplinary goals of the SDGs that deeper domain science is not compromised, scarce expertise is not misdirected, and that infrastructure developments within the domains are not unduly hampered.

¹https://www.auscope.org.au/news-features/strategy-and-investment-plan-launch 

²https://ddi-alliance.atlassian.net/wiki/spaces/DDI4/pages/860815393/DDI+Cross+Domain+Integration+DDI-CDI+Review 

³https://codata.org/initiatives/strategic-programme/decadal-programme/

How to cite: Wyborn, L., Rawling, T., Cox, S., Evans, B., Hodson, S., Klump, J., and McEachern, S.: Developing Global Coordination of Solid Earth Research Infrastructures in Support of the United Nations Sustainable Development Goals., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10877, https://doi.org/10.5194/egusphere-egu21-10877, 2021.

Climate change is already impacting the performance and integrity of transportation infrastructure around the world and is anticipated to have serious ramifications for infrastructure safety, environmental sustainability, economic vitality, mobility and system reliability. These impacts will disproportionately affect vulnerable populations and urban locations as well as compromising the resilience of the larger interconnected physical, cyber, and social infrastructure networks. For this reason, increasing the resilience of transportation infrastructure to current and future weather and climate extremes is a global priority.

The complexity of this challenge requires a convergence approach to foster collaboration and innovation among technically and socially diverse researchers and practitioners. The multi-institutional ICNet Global Network of Networks unites domestic and international research and practice networks to facilitate integrated engineering, climate science, and policy research to advance the development of resilient transportation infrastructure and systems. ICNet Globalcollaborators represent networks based in Korea, Europe, United Kingdom, and the United States and link researchers at the forefront of scientific, engineering, and policy research frontiers, drawing expertise from many disciplines and nations to share and enhance best practices for transportation resilience.

ICNet Global’s long-term mission is to prepare the world’s existing and future transportation infrastructure for a changing climate. To that end, we are working to: (1) build a network of existing research networks who are tackling the challenges climate change poses to transportation infrastructure; (2) establish a common base-level knowledge, capacity, and vision to support the convergence of novel and diverse ideas, approaches, and technologies for creating climate resilient transportation infrastructure; and (3) grow the next generation of critical and diverse thinkers with the expertise to address and solve climate-related infrastructure challenges. Although just one year into our work, and dispite challenges represented by COVID-19, we have surveyed over 100 potential members worldwide to learn about fields of interest and held five productive virtual workshops to discuss current research, how to encorporate climate change information into engineering education, and how practitioners are currently including climate information into planning and design. In this presentation we highlight our goals and recent accomplishments while laying out future plans and inviting interested researchers and practitioners to join us.

How to cite: Stoner, A., Jacobs, J., Sias, J., Airey, G., and Hayhoe, K.: ICNet Global: Infrastructure and Climate Networks of Networks, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15099, https://doi.org/10.5194/egusphere-egu21-15099, 2021.

The Agenda 2030 of sustainable development introduced in 2015 by the United Nations is a call for action to address the major challenges the world faces [1]. To tackle these challenges, the Agenda defines the 17 Sustainable Development Goals (SDGs), which have been conceived with respect to five pillars (planet, people, prosperity, peace and partnership), thus creating synergies and trade-offs among the Goals. The Agenda also addresses the need for more targeted policy implementations, totaling 169 targets across the Goals. Moreover, indicators have been defined to measure progresses in each target, and so, Goal.

To create aggregated scores of such countries’ performance indicators is a recurrent and crucial issue within the SDGs framework, where several methodologies have been proposed to create a ranking of countries which can provide insights about the fulfillment of all of the Agenda’s objectives and principles (see, e.g., Sachs et. al. [2] and Biggeri et al. [3]). In light of the complex nature of the Agenda (as pointed out by LeBlanc [4]), we argue that the use of multidisciplinary tools is essential to help shed light on how to address efforts in global sustainable development. In particular, network theory can be used to create several aggregated scores that can actually account for the complex nature of the Agenda, the synergies and trade-offs among the Goals and, no less, of the role of countries toward the achievement of SDGs.

In this work, we recast the data concerning the performances of countries in each Goal’s indicators as the incidence matrix of a bipartite system constituted of two sets: countries and Goals, connected by the performances of countries within each Goal. We exemplify our framework using the data taken from the 2020 SDG Index and Dashboard by Sachs et al. [2]. We show that, framed within network science, the SDG Index coincides with measuring the degree centrality of countries within this bipartite system and that such measure neglects the heterogeneity of countries in tackling the Goals and their responsibilities at the global scale. More informative centrality measures, and so, aggregated scores, can be obtained by the adoption of the economic complexity theory, in particular, the GENEPY framework [5]. The GENEPY rationale defines a data-driven weighting scheme in which relative countries’ performances of all SDGs are considered to define a more comprehensive ranking of countries.

References:

[1] Transforming our world: the 2030 Agenda for Sustainable Development. Division for Sustainable Development Goals: New York, NY, USA, 2015.

[2] Sachs, J., et al. . 2020. The Sustainable Development Goals and COVID-19. Sustainable Development Report 2020. Cambridge: Cambridge University Press.

[3] Biggeri, M., et al. (2019). Tracking the SDGs in an ‘integrated’ manner: A proposal for a new index to capture synergies and trade-offs between and within goals. World Development, 122, 628-647.

[4] Le Blanc, D. (2015). Towards integration at last? The sustainable development goals as a network of targets. Sustainable Development, 23(3), 176-187.

[5] Sciarra, C., et al. (2020). Reconciling contrasting views on economic complexity. Nature Communications, 11(1), 1-10.

How to cite: Sciarra, C., Chiarotti, G., Ridolfi, L., and Laio, F.: Measuring countries' progress in sustainable development through network theory, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9607, https://doi.org/10.5194/egusphere-egu21-9607, 2021.

The last few decades have seen a range of advances in climate science and consequential policy initiatives at both national and international levels. These advances have been built on the back of progress in modelling and in part been enabled by the global data sharing initiative - the Earth System Grid Federation (ESGF) - which has underpinned recent phases of the World Climate Research Programme's Coupled Model Intercomparison Projects.  

The ESGF itself consists of data nodes deployed by individual modelling centres and a backbone of software development and services delivered by a few core institutions. Within Europe, along with some shared development of model components, these core ESGF software development and services are coordinated by the European Network on Earth System Modelling (ENES) and supported by the H2020 IS-ENES Phase 3 research infrastructure project.  

We provide an historical overview on advances in policy-relevant science, such as the Intergovernmental Panel for Climate Change (IPCC), that have been enabled by long-term underpinning development and funding of the ENES and ESGF infrastructure. We illustrate the recent shift of research funding from physical science objectives alone towards funding services to society (and the necessary underpinning research). We stress the potential dangers of underfunding research infrastructures that need to be simultaneously flexible and reliable enough to serve both ongoing basic research and the growing societal objectives, as emphasised by the development of climate services such as Copernicus Climate Change Service. We conclude by presenting some steps towards sustaining such research infrastructure in the context of the ENES and the possible futures of climate science.

How to cite: Adloff, F., Lawrence, B., Joussaume, S., Lautenschlager, M., Bessembinder, J., Biercamp, J., Cofiño, A., D’Anca, A., Fladrich, U., Hines, A., Juckes, M., Kazeroni, R., Kershaw, P., Kindermann, S., Nassisi, P., Pagé, C., Serradell, K., and Valcke, S.: From climate models to informing policy decisions: the end-to-end importance of an effective research infrastructure, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15251, https://doi.org/10.5194/egusphere-egu21-15251, 2021.

There are nearly 80 million people forcibly displaced worldwide, of which 26 million are refugees and 45 million are internally displaced people (IDPs) (UNHCR, 2020). It is difficult to foresee and accurately forecast forced migration trends due to the severity and instability of conflicts or crises. However, it is possible to capture relevant aspects of this complex phenomenon and propose an approach forecasting future migration trends. Hence, we present an agent-based modelling approach, namely FLEE, that predicts the distribution of incoming refugees from a conflict origin to neighbouring countries (Suleimenova et al., 2017). Our aim is to assist governments, organisations and NGOs to efficiently allocate humanitarian resources, manage crises and save lives.

To construct a forced migration model, we obtain relevant data from three sources: the United Nations High Commissioner for Refugees (UNHCR, https://data2.unhcr.org) providing the number of forcibly displaced people in the conflict, the camp locations in neighbouring countries and their population capacities; the Armed Conflict Location and Event Data Project (ACLED, https://acled-data.com) for conflict locations and dates of battles; and the OpenStreetMaps platform (https://openstreetmap.org) to geospatially interconnect camp and conflict locations with other major settlements that reside en-route between these locations. Consequently, we simulate the constructed model using the FLEE code (https://github.com/djgroen/flee-release) and obtain the distribution of incoming forced displacement across destination camps. We were able to reproduce key trends in refugee counts found in the UNHCR data across Burundi, Central African Republic and Mali (Suleimenova et al., 2017), as well as investigated the impact of policy decisions, such as camp and border closures, in the South Sudan conflict (Suleimenova and Groen, 2020).

In our recent collaboration with Save the Children, we focus on an ongoing conflict in Ethiopia’s Tigray region and forecast IDP numbers within the region and refugee arrival counts in Sudan. We found that the number of arrivals in Sudan seem to depend strongly on whether the conflict will erupt in the east or in the west of Tigray. This seems to be a larger factor than the actual intensity of the conflict.

Moreover, our modelling approach allows us to investigate possible effects of weather conditions on forcibly displaced people by coupling FLEE with precipitation data, seasonal flood and river discharge levels. The purpose of coupling with the European Centre for Medium-Range Weather Forecasts (ECMWF) data is to identify the effect of weather conditions on the behaviour and movement speed of forced migrants.

The overall strategy is the static coupling of weather data where we have analysed 40 years of precipitation data for South Sudan to identify the precipitation range (minimum and maximum levels) as triggers which by the agents’ movement speed changes accordingly. Besides, we have used daily river discharge data from Global flood forecasting system (GloFAS) to explore the threshold for closing the link considering values of river discharge for return periods of 2, 5 and 20 years. Currently, we only use a simple rule with one threshold to define the river distance for a given link, which we aim to investigate further.

References
1. UNHCR (2020). Figures at a Glance, Available at: https://www.unhcr.org/figures-at-a-glance.html.
2. Suleimenova D., Bell D. and Groen D. (2017) “A generalized simulation development approach for predicting refugee destinations”. Scientific Reports 7:13377. (https://doi.org/10.1038/s41598-017-13828-9).
3. Suleimenova D. and Groen D. (2020) “How policy decisions affect refugee journeys in SouthSudan: A study using automated ensemble simulations”. Journal of Artificial Societies and Social Simulation 23(1)2, pp. 1-17. (https://doi.org/10.18564/jasss.4193).

How to cite: Suleimenova, D., Jahani, A., Arabnejad, H., and Groen, D.: Forecasting Forced Migration by Coupling an Agent-based Simulation Approach with Weather Data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16086, https://doi.org/10.5194/egusphere-egu21-16086, 2021.

The Oceans have taken up 20-25% of the carbon dioxide released to the atmosphere by human activities, in the process slowing the rate of climate change and giving us more time to adapt to and mitigate the effects of global warming. However this ‘sink’ has not been stable over the recent past and there is therefore a need to measure it in near real time with higher confidence than currently possible so that appropriate policy measures can be developed and implemented in response to any change. We have a wide array of tools including satellites, ship based and autonomous (gliders, moored, floats and surface vehicles) measuring systems which together with the associated data infrastructure can demonstrably come together to deliver this vision. These have largely been developed under short-term funding streams and, as a consequence do not currently deliver the robust, near real time, sustainable estimate of ocean C uptake that we believe is necessary to support international climate negotiations and the development of adaptation/mitigation strategies. We are currently developing a blueprint for the ‘Integrated Ocean Carbon Observing System’ which we believe will be as necessary for reliably forecasting climate over the next 5-10 years as meteorological observations currently are for forecasting weather over the next 5-10 days. In this contribution we will describe the key elements of this blueprint and outline a timeline for assembling them together to deliver an annual near realtime databased estimate of ocean carbon uptake to the annual COP in support of international climate negotiations.

How to cite: Sanders, R. and Watson, A.: The Integrated Ocean Carbon Observing System, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13106, https://doi.org/10.5194/egusphere-egu21-13106, 2021.