SCIENTIFIC DOCUMENT

THE CONTRIBUTION OF THE RESEARCH INFRASTRUCTURE DATATERRA

TO SCIENTIFIC AND TECHNOLOGICAL CHALLENGES

OF MULTIDISCIPLINARY AND MULTISCALE APPROACHES TO THE EARTH SYSTEM

IR DATA TERRA

June, 30, 2020

TABLE OF CONTENT

Preambule 31 Introduction 32 Scientific challenges 4

2.1 Land-ocean continuum and interfaces 42.1.1 Observing and modelling the impacts of global change 42.1.2 Towards a reference climatology of the French coastal environment 52.1.3 Sea level change 52.1.4 Management of fisheries, energy and mineral resources: 6

2.2 Understand the critical zone 62.2.1 Exploring the Dynamic Architecture of the Critical Zone 72.2.2 Discovering the processes that shape the Critical Zone and its transformation 72.2.3 Predict the future evolution of services offered by the critical area 8

2.3 Inhabited territories, agriculture, cities and health 82.3.1 Cities and health 82.3.2 The urban exposome 92.3.3 Agriculture, food security and climate 9

2.4 Climate system and interactions 102.4.1 Interactions clouds – water vapour – aerosols 112.4.2 Interactions between climate and land surfaces 112.4.3 Attribution of observed changes 112.4.4 Determining fluxes at interfaces 122.4.5 Ocean evaporation/precipitation balances 13

2.5 Hazards impacts on society 132.5.1 Seismic and volcanic hazards 132.5.2 Intensification of hydrometeorological cycles 142.5.3 Mineral and energy resources 14

3 Strategic needs on data 153.1 The FAIR principles 153.2 Processing, calculations et services 16

3.2.1 Processing facilities and services 163.2.2 Mathematical method and Artificial Intelligence 173.2.3 Data mining and added value products 17

4 Methodological challenges 184.1 Uncertainties and signal separation 184.2 Assimilation and combination of multi-temporal and multi-disciplinary data 184.3 Citizen science 18

5 Training and communication need 195.1 Internal training of dataterra actors 195.2 Scientific community training: 19

5.2.1 From harvesting to data FAIRisation 195.2.2 Learning the use of observational and modelling data sets 195.2.3 On-demand service utilization learning 19

5.3 Communications about our work: 20

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PREAMBULE

The scientific strategy of the DataTerra IR encompasses the scientific issues specific to each thematic pole and the transversal issues. The motivation of this document is to develop several priority transversal challenges at the interfaces of the thematic clusters for which the new integrated services developed by DataTerra IR are essential to overcome science and technology challenges to access to the full range of data sources, their extraction and combination for developing high-quality synthesised data products. It is not intended to describe all of the challenges that scientific communities must tackle: the scientific perspectives of research organisations (INSU, CNES, IRD) describe them more exhaustively.

The digital infrastructure, proposed in the PIA3 ESR-EquipEx+ GAIA Data project, will make it possible to remove the technical barriers to integrating data from observations and modelling at different spatial and temporal scales and to backing them up with high-performance computers and a very high-speed network.

1 INTRODUCTION

Society and our Planet are facing major changes at an unprecedented rate. Anthropic pressure requires a better understanding of the multiple issues impacting our societies: climate change, pollution, environmental and health risks, resources, energy, digital transition, etc. These issues call for a development of knowledge about the Earth system. The Earth system is a complex system made up of physical and living environments in which Man has his full place. These environments are characterized by processes acting on a very broad continuum of time and space scales that often interact with each other. To be able to predict the evolutions and extreme events that affect the Earth system, and their societal impacts, requires knowledge of its history and an understanding of its functioning. This traditionally requires scientific works based on the integrated and cross-analysis of numerous data from lab experiments, from observations on land, at sea, or from airborne or space observations and from modelling.

The complexities of the studied systems and processes, on the one hand, and the huge progress in data resolution and accuracy, on the other, imply that works in a specific theme or compartment of the Earth system increasingly require the integration and consideration of information or data from other themes. It has become essential to implement multi- or inter-disciplinary approaches that require easy access to qualified data from other themes but also to products (transformed data) with well-known uncertainties that can be easily used also by non-specialists of the considered theme, as illustrated below by several examples of these cross-cutting challenges.

In recent years, the scientific community has benefited from numerous technological advances and breaks in satellite and in-situ acquisition systems which, at the same time, have led to an unprecedented volume of data. This is the case, for example, with developments based on fibre optics for the measurement of deformations or the evolution from nadir to wide-swath altimetry (another example: the evolution of the accuracy of satellite measurements (by radar altimetry) of

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lake and river levels coupled with ground measurements has made it possible to analyse and reconstruct hydrological records in poorly informed regions (tropical zones) and to better understand and predict the evolution and impacts of hydroclimatic processes). The scientific community is also benefiting, or will benefit in the near future, from the intensive digitisation (2D and 3D) of archives: writings, analogue recordings of the past but also physical samples (e.g. in paleontology). Finally, data from citizen science networks are now increasingly integrated into studies.

As a result, the various scientific communities studying the Earth system are facing the same paradigm shift in the way they analyse data and extract knowledge from it. The current and foreseeable rate of increase in the volume of digital data cannot be absorbed by existing public or private digital infrastructures and creates new challenges. It is necessary to ensure not only the qualification of the data, as close as possible to the producers, and their fairisation1, but also their processing and analysis. The new data generate new dedicated methods of analysis, especially for source separation, and the same applies to aspects related to their massive increase.

This new landscape also calls for the development of new techniques, or even new professions such as data scientists2, and specific training to be incorporated into traditional teaching paths.

2 SCIENTIFIC CHALLENGES

2.1 LAND-OCEAN CONTINUUM AND INTERFACES

The land-sea continuum can be defined by the geographic perimeter that connects watersheds to the continental margin through the river system. It concentrates a wide range of natural environmental interfaces and gradients, generating a very high heterogeneity at different spatio-temporal scales. This mosaic of environments is among the most productive and most populated; the coastal zone is a source of biodiversity. The attractiveness of coastal areas is one of the causes of the amplification of the coastalisation that threatens the socio-ecosystems at the land-ocean interface. However, it is also the site of a wide variety of resource issues: food, energy, materials.

2.1.1 Observing and modelling the impacts of global change

There is a need to assess the impacts of global changes on the vulnerability of the land-ocean continuum, on functions at different interfaces (deltas, coastal areas, estuaries, etc.) and on continental and sea landscapes. Expected changes include a reduction in water and sediment flows, an increase in relative sea level and coastal erosion processes. However, there are still many uncertainties about the evolution of the continuum due to multiple interfaces. While the tendency to view these systems as separate entities remains dominant, the functioning and evolutionary trajectories of the land-ocean continuum in the face of global change require an integrated approach. Although coastal zones and watersheds have been/were the subject of numerous studies and observations, monitoring remains highly focused and limited to one type of environment. This is notably the case for many monitoring activities carried out by research observation services (National Observation Services, SNO), or within the framework of regulatory monitoring. The challenge is to develop an integrated approach that considers the continuum as a whole and to reduce the uncertainties related to the difficulty of identifying and modelling the indirect effects and feedbacks related to anthropogenic activities and climate change, in comparison with their direct impacts.

1 The goal of the FAIR principles is to promote the discovery, access, interoperability and reuse of shared data.2 In charge of the management, analysis and exploitation of massive data

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Challenges: being able to access all data on a given continuum to promote the integrated approach; need for tools to compile, make available, combine in situ/satelites/sat observation/model outputs simulations availability of statistical tools to extract trends/variability or reveal events or even shifts; need for interaction with civil society and managers and for knowledge transfer and exchanges on changes in practices and observations.

2.1.2 Towards a reference climatology of the French coastal environment

While there are reference climatologies, approved by the international scientific community, of the essential physico-chemical parameters of the deep oceans, the situation is much less mature in coastal and littoral environments. This is due in particular to the limitations of satellite observation very close to the coasts, to the diversity and disparity of in-situ measurements (low and high frequency measurements, at different immersions and/or tidal stages, diversity of sensors, problem of discovering areas, etc.), and to the lack of operational modelling tools that correctly assimilate observation data in all this diversity. Thus, there is no single answer, referring to simple and topical questions such as how is the coastal ocean warming along our coasts? This is true for parameters such as salinity, dissolved oxygen, turbidity, chlorophyll, sea states, etc. Such an atlas is also essential for making projections, climate models, multi-decadal evolution scenarios of the coastal ocean and its socio-ecosystems. The production of a climatological atlas of the coastal ocean along the French coast will require a vast methodological and data processing project, and should be developed jointly by DataTerra and ILICO3 Research Infrastructures.

Challenges: need to access a combination of all the data acquired at the continent-ocean interface (in situ, satellites); to develop algorithms for processing satellite observations at the continent-ocean interface, data assimilation; statistical visualization and anomaly identification products.

2.1.3 Sea level change

The sea surface is at the interface of several components of the Earth system (oceans, atmosphere and continents). Thus, sea level is from the outset a parameter at the interface of disciplines, and a precise knowledge of its variations requires an interdisciplinary approach. Monitoring and modelling of sea level requires the definition of a precise frame of reference, which is essential for identifying and describing the contributions correctly, separating them from the observation that integrates them all (climatic, meteorological, astronomical, post-glacial rebound, tectonics), modelling them and combining them to study their resultant, for example to assess the risks of submersion.

Thus the risks of marine submersion, which is one of the consequences of the global sea rise, also depend on the local effects of solid earth (subsidence) due, for example, to the exploitation of water tables in urbanised coastal areas (and more generally to the reshaping of these coastal areas by man), or to the presence of tsunamigenic submarine faults.

Predicting the risks of submersion on small scales, which affect coastal populations in particular, therefore requires better account to be taken of local specificities and multidisciplinary data. Freshwater resources, used for drinking water supply in coastal cities with growing populations, are limited in quantity and quality and threatened by increasing demand and rising sea levels.

3 Coastal Ocean and Nearshore Observation Research Infrastructure: www.ir-ilico.fr

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Assessment of the available resource and its current and future sustainable use also requires multidisciplinary data and studies.

Barriers: Need to access in situ data (ocean/ geosphere/ geodesy/ hydrology/ tectonics), model outputs (hydrological, ocean overload, post-glacial rebound and seismic cycle, ...) on geographical areas at different scales; Improvement of water level accuracy in hydrological networks.

2.1.4 Management of fisheries, energy and mineral resources:

The preservation of fisheries resources is based on the need to ensure the management of the resource, or even its restoration, in a sustainable development approach. This approach presents specific challenges to the scientific community. The first concerns the preservation of ecosystems, which involves in particular the establishment of management zones and the creation of marine protected areas (MPAs) in the open ocean. The delimitation of MPAs must include not only the observed spatial variability but also that expected in the coming decades, induced by climate change. This requires access to the fine spatial scales of data (satellite and in situ) and climate scenarios. A second challenge concerns the four major upwelling systems (Eastern Boundary Upwelling Systems; EBUS): these areas are biologically highly productive regions, covering less than 1% of the ocean surface, but providing up to 20% of the world's capture fisheries. A better understanding of the links between upwelling dynamics, marine ecosystems and atmospheric chemistry is needed to address the requirement of sustainable management of fisheries resources.

The marine environment, and in particular the coastline, is also a privileged place where decarbonated power generation devices can be set up (wind farms, tidal power, wave use, etc.). In offshore environments, the hydrothermal zones on the ridges are also potential sites for energy resources. In addition, the subsoil of the marine environment is rich in mineral resources (metal ores, rare earths, aggregates, etc.) which are essential for the implementation of the energy transition. Again, multidisciplinary approaches are essential for exploration, sustainable exploitation and the assessment of environmental impacts (see section 2.5.3).

Barriers: Need to access in situ data (ocean/atmosphere), water colour products on mesoscale geographical areas and model outputs; Need for access to an integrative approach taking into account all land-atmosphere-ocean interaction processes at all scales (combining in situ and satellite observations, and coupled modelling).

2.2 UNDERSTAND THE CRITICAL ZONE

The Critical Areas Science Initiative aims to promote the work of different scientific disciplines in geoscience and bioscience on the same object and to develop an integrated understanding of the habitable part of the planet as a system.

While the monitoring of the energy balance at the surface has made it possible to make reliable predictions of global warming in recent decades, the explicit consideration of other fluxes is still fragile and partial: the description of soils, their heterogeneity and interactions with the underground compartment are still very fragmentary; the nature and quantity of matter, gases, emitted by different sources depending on their location are incompletely documented, with a precision and representativeness that are difficult to assess. The interactions between biotic and abiotic components need to be taken into account more closely to provide a better representation of the

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functioning of the Earth system. One of the major scientific questions of the critical zone is how to model the integrated functioning of the critical zone and predict its response to environmental constraints at the local and global levels (Gaillardet et al., 2018 4). Challenges to studying and understanding the critical zone include the following.

2.2.1 Exploring the Dynamic Architecture of the Critical Zone

There is a need to better describe and understand the structural, chemical and biological organization of the critical area. This implies characterizing the extension of the critical zone and its dynamic evolution (hydrodynamic and chemical properties of soils and their depths), understanding the role of its various interfaces and their connectivity, and knowing how to quantify the impact of spatial heterogeneity and intermittency on the fluxes and residence times of water and associated materials. It is also necessary to be able to describe and take into account the concentrations of microorganisms and their role in the dynamics of the critical zone.

Barriers: Availability and accessibility of 3D maps of soil and subsoil properties (hydrodynamic, chemical, biological, etc.) in sufficient quality and resolution.

2.2.2 Discovering the processes that shape the Critical Zone and its transformation

The processes that shape the critical zone operate on spatial and temporal scales ranging from seconds to millions of years, from local to global. Understanding these processes first requires the ability to quantify the balances and fluxes of water, energy, carbon and sediment in the critical zone on different spatial and temporal scales. It is also necessary to understand the biogeochemical cycles that orchestrate its evolution, the biotic and abiotic interactions and to identify how the small scale influences the large and vice versa, where and when (hot spots, hot moments) these processes are active and thus document the role of heterogeneity. Many scientific studies related to the critical area are based on the development, feeding, or use of emission inventories that record the nature and quantity of matter, gases, emitted by different sources depending on their location. However, the error associated with the calculation of emissions is sometimes difficult to assess, especially when those of the basic data are not well known.

Barriers: to have access to long-term data series to develop/calibrate/evaluate the models. To be able to describe the heterogeneities of the processes and to quantify the related uncertainties: to develop the banking of very high spatial and temporal frequency data in the critical zone, including citizen sciences (in collaboration with the IR OZCAR5 and the Zones Ateliers (ZA)); to have tools for the acquisition, exploitation and availability of these future data lakes6.

2.2.3 Predict the future evolution of services offered by the critical area

It is necessary to be able to predict the responses of the critical area to local natural and/or anthropogenic disturbances in a context of global change and to provide elements of decision support to policy makers. All acquired data should be assimilated into integrated modelling of the critical zone, taking into account all compartments, including the biological compartment and

4 Gaillardet, J., I. Braud, F. Hankard, et al. « OZCAR: The French Network of Critical Zone Observatories ». Vadose Zone Journal 17, no 1 (2018): 0. https://doi.org/10.2136/vzj2018.04.0067.5 Observatoires de la Zone Critique : Applications et Recherche6 Data lake: very large dataset of data from multiple and heterogeneous sources.

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human-environment feedbacks, and leading to reanalyses of the critical zone. These tools should help us to understand the feedback between the compartments of the critical zone, the ocean and the atmosphere and to contribute to the major societal challenges posed by global changes (natural hazards, food, living environments). Modelling and forecasting fluxes in the critical zone are complex and highly dependent on the resolution and accuracy of available data. Some variables play a major role but are still poorly described at the necessary precision (rainfall intensity, aerosols, root depth, etc.). A challenge for all the compartments is certainly to have data series, but also to identify data gaps or redundancies: data inventory via the DataTerra portal should make it possible to visualise the sites and to improve, or even optimise, the strategies of the observatories.

Barriers: availability and accessibility of data in sufficient quality and resolution for forcing numerical models and their evaluation in all compartments. To have data assimilation and interpolation tools; to have climate and land-use scenarios available; To promote dialogue between observers/modellers/ computer scientists/ system engineers/ decision makers/ citizens in Continental Surface and Interface Sciences.

2.3 INHABITED TERRITORIES, AGRICULTURE, CITIES AND HEALTH

This chapter concerns the inhabited part of our planet, including urban areas and the agricultural territories that feed them. These two types of territories are closely linked and of course have strong interactions. The link between agricultural areas and activities and the climate and the water cycle is obvious, but urban territories are also increasingly sensitive to climate change and the ever-increasing consumption of resources in cities.

2.3.1 Cities and health

The scientific community needs to come together in a very multidisciplinary way to study urban systems in order to form a community of urban sciences that is still very poorly structured, from the national to the international level7. This should enable the necessary advances required to improve the understanding and quantification of the impacts of urbanization on different spatio-temporal scales. This includes not only the major environmental impacts of urbanization on air, water, soil, biodiversity, energy and regional climate with health impacts (air pollution, food security, new contaminants, etc.), but also the issue of the impacts of the city on resources (water, air, soil, food, etc.) and risks, including emerging risks in urban environments.

There are many examples where climate change has been blamed as a cause of illness or death: heat-related mortality; diseases linked to aerosols or insects, which spread in geographical areas that have become favourable (Lyme, malaria, dengue fever, meningitis, ...). Other consequences, mainly negative, are expected on human health and well-being, and ecosystems in general, in connection with climate change (increase in temperature; increase in extreme weather events: heat waves, floods, drought, storms).

To answer these questions, studies must be conducted at different spatio-temporal scales (from individual to ecosystem, from parcel to region) and by combining several disciplinary fields to understand the functionality of urban ecosystems. This requires the input of various databases (emission inventories, air quality, surface temperature, land use, biodiversity, epidemiology, etc.), multi-parameter and on different spatial and temporal scales (very fine scales and on short time scales). For example, the evolution of metrology (screening, chemical fingerprints, better detection capabilities, individual and networked mobile samplers and sensors, satellite sensors with very high

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spatial and temporal resolutions) will allow better perception and quantification of contamination and exposure levels. In addition, this monitoring should make it possible to assess the advantages or disadvantages of new developments in order to propose indicators likely to help decision-making in cities, to promote the adaptation of humans, animals and plants to climate change.

Global impact assessments are necessary, taking into account the outside of the city (from its periphery to the region) and transition zones (e.g. urban and peri-urban land management, the city's food dependency on its hinterland). An interdisciplinary approach should be promoted, for example, combining civil engineering and urban planning with economics, geography, sociology, health, ecology, climate and atmospheric sciences.

Barriers: Need for various databases (emission inventories, air quality, surface temperature, land use, biodiversity, epidemiology, ...) on various spatial and temporal scales. need for the development of numerical models (and their validation) integrating different scales of processes (from the territory as a whole to the individual, i.e. its spatial scale and the determinants of its exposure).

2.3.2 The urban exposome

The concept of the exposome is the totality of exposures to environmental (i.e. non-genetic) factors that a human organism undergoes from conception through in utero development to the end of life, complementing the effect of the genome. It illustrates fairly well the difficulties of taking into account in an integrated manner the different exposures of the urban dweller and their sources (air, water, food, medicines, radiation, etc.) and the need for "intelligent" tools to cross-reference and query multiple databases, often heterogeneous and constructed with very different purposes or origins. Urban vegetation, urban hydrology, urban microclimate or urban pollution are already studied, but a structuring of the observation on these urban environments remains to be done. Moreover, the study of the city at the scale of the district, the street, the housing will generate large volume of data in order to allow coupled observation/modelling studies.

Barriers: the need to develop numerical models integrating very fine scales, the need to manage and analyse large amount of data of various origins and nature.

2.3.3 Agriculture, food security and climate

Global agriculture faces multiple challenges7. It needs to increase its production by 70% by 2050 to keep pace with the more than 30% increase in population and changes in food preferences. At the same time, agriculture has to cope with climate change, extreme events, changing demand and pressures to reduce its impact on soil, water, biodiversity, climate and to contribute to climate change mitigation.

If food and agricultural systems continue to evolve in line with current trends, it is now clear that the future will be characterized by persistent food insecurity and unsustainable economic growth8.

Meeting this challenge requires the mobilization of almost all the disciplines of the so-called hard sciences (biology, chemistry, agronomy, ecology, hydrology, meteorology, climatology, etc.) but also

7 FAO, 2017 : The Future of Food and Agriculture: Trends and Challenges www.fao.org/publications/fofa/fr8 FAO. 2018. The Future of Food and Agriculture - Alternative pathways to 2050. Abstract. Rome. 64 pp. http://www.fao.org/3/CA1553FR/ca1553fr.pdf

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the human and social sciences. Producing more, producing better, reducing malnutrition, adapting to climate change while contributing to its mitigation, is as much a matter of political and social organization, economics as of agronomic techniques. The challenge posed by the evolution of agriculture can only be met by building on advances in other areas mentioned in this document ("Understanding the critical zone", "Climate and the water cycle").

The analysis grid below is based on the geographical dimension, from the agricultural plot and the catchment area to the whole world. However, the temporal dimension is present at all spatial scales, to describe processes, seasonal management or scenarios.

Scale Issues

Parcel provide the farmer with decision-support tools that will enable him, for example, to choose the crop to be sown according to demand, resources (soil, water, labour, equipment), seasonal weather forecasting, and to optimize inputs (water, fertilizers, pesticides)

Watershed allocation of water for irrigation, phytosanitary alert, and on a more strategic level, studies on the creation of water reserves, measures to reduce soil degradation and carbon storage

Contries crisis anticipation and insurance policies, general climate change adaptation and mitigation measures (e.g. 4 for 1000 initiative9,10 ), regional statistics and monitoring of world markets, monitoring of agricultural land consumption.

International11 production levels and global food security, crisis anticipation and management, price stability and the fight against speculation, trade regulation, exchange of information, knowledge, best practices and tools.

Barriers: The need to store, manage and process very large volumes of data, including the temporal dimension: long data series, multi-yearly, associated with short time steps needed to capture the events that determine agriculture, and high resolution at the scale of the agricultural plot. Near-data processing to avoid long data transfers and multiple storage of information Need for access to in-situ data necessary for model calibration, learning AI algorithms, and validation.

2.4 CLIMATE SYSTEM AND INTERACTIONS

Understanding the climate system in all its components fundamentally underpins our ability to model different climate change scenarios and their environmental, social, economic and political consequences. The diversity and masses of observation and simulation data required for this understanding make climate and water cycle a showcase for the need for an infrastructure that allows for the convergence of these data and means of analysis. The many issues associated with

9 The international "4 for 1000" initiative, launched by France on 1 December 2015 at COP 21, aims at an annual growth rate of 0.4% of soil carbon stocks per year, in the first 30 to 40 cm of soil, in order to reduce the concentration of CO2 in the atmosphere due to human activities. https://www.4p1000.org/fr10 https://www.inrae.fr/actualites/stocker-4-1000-carbone-sols-potentiel-france11 Multilateralism and international institutions or agencies (Banque Mondiale, FAO, FMI, PNUD, …)

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these questions often have in common the need to better characterize the processes brought into play within the compartments or at their interfaces.

2.4.1 Interactions clouds – water vapour – aerosols

The interactions between water vapour, aerosols, clouds and precipitation still remain today questions not fully resolved by the scientific community and a source of significant uncertainties for numerical weather and climate prediction. Understanding processes from satellite observations is probably one of the major challenges of today and the many parameters that need to be described simultaneously can only be observed by combining information from different sensors and platforms. This poses both scientific challenges for the coherent interpretation and simulation of observations over a wide spectral range and technical challenges, given the diversity and volumes of data involved.

In the near future, Europe will be equipped with two new operational observing systems for meteorology12 that will provide unprecedented observations for the study of atmospheric processes. Those will however represent a huge challenge in terms of analysis, particularly on the issue of multi-sensor approaches for which the operational agencies (EUMETSAT) do not necessarily have pre-existing workflows. The obvious contribution of data from models (ERA5 for example) must also be considered.

Barriers: The need for centralized access to these data (observations and models) and analysis tools to develop multi-sensor approaches for better characterization of the properties of the atmosphere and to analyse very large volumes of data crossing observations and atmospheric reanalyses for the study of processes.

2.4.2 Interactions between climate and land surfaces

The interface between the atmosphere and the continental surfaces is a place of important exchanges of energy and of liquid, solid or gaseous matter. Therefore, understanding and quantifying the interactions between surfaces and the atmosphere is a major challenge in order to try to anticipate the consequences of new and future changes in continental surfaces, whether as a result of climate change or changes in land use. One of the challenges is also to represent the soil and subsoil and the interactions with the surface in a much more explicit and detailed way than has been done up to now (cf. section on the critical zone). For example, the root depth that conditions the uptake of groundwater by plants is still poorly known, and often limited to one meter in models, which may lead to underestimating actual evapotranspiration, particularly in tropical areas.

Barriers: Need for centralized access to data on soil and subsoil, cultivated and natural vegetation in temperate and tropical climates.

2.4.3 Attribution of observed changes

In the climate sciences, attribution has aggregated together a community that has developed theoretical and methodological concepts to better respond to these issues, both in terms of attributing extreme events and long-term climate trends. Similar questions arise for the assessment of the respective roles of climate change, on the one hand, and land use, on the other, on changes in the input and output fluxes of energy, water and gaseous, dissolved or particulate trace species. The

12 European Polar System – Second Generation » (EPS-SG) and « Meteosat Third Generation » (MTG)

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land surface community is, however, less well equipped for this topic due to the complexity of socio-eco-hydrological systems and the interaction of influencing factors.

Thus, understanding and quantifying the interactions in the soil-water-plant-atmosphere continuum is a major challenge in order to better anticipate the consequences of new and future changes in continental surfaces, whether as a result of climate change (intensity, intermittency, etc.) or man: changes in land use, cropping practices, modification of the water cycle (dams, structures, irrigation, drinking water withdrawals). And hereafter provide well-founded answers to the questions raised by public decision-makers.

The particular complexity of the analysis of exchanges between the surface and the atmosphere is largely due to the spatial heterogeneities of the surface (in nature, coverage, type of use, etc.), its temporal evolution and the non-linearity of the processes.

Barriers: Need for centralized access to data (surface/atmosphere) at high spatial and temporal resolutions.

2.4.4 Determining fluxes at interfaces

The physical, chemical and biological processes that occur at the interfaces between the different compartments of the Earth system are critical to understand in order to estimate the fluxes of energy and matter and to comprehend and model the system as a whole. Among these, the estimation of heat and carbon fluxes are two major challenges, in particular for climate change anticipation, mitigation and adaptation, which involve both scientific and policy issues.

Where does half of the CO2 emitted by mankind go? What are the parameters that control the natural exchange of carbon? Will the "natural" (rather "forced") sink continue into the 21 st century with the predicted climate change? How can we assess the current and future capacity of terrestrial ecosystems to store carbon? What are the fluxes associated with the long-term component of the carbon cycle linked to chemical weathering? Is it possible to verify the emissions declared by states? Is it possible to measure these emissions at a finer scale (city, industry) to "monitor" an activity? These questions are all the more complex as they involve characterising fluxes that vary greatly in time and space, in particular anthropogenic fluxes of energy and materials. Concerning the storage capacity of ecosystems, it is necessary to be able to quantify separately and on a large scale the fluxes of photosynthesis and respiration.

On a global scale, spatial remote sensing allows CO2 concentrations to be measured, but not the fluxes that must be derived from spatial-temporal gradients of concentrations by combining observations and models. For CO2, as for all carbon fluxes, it is clear that the diagnostic approaches and climate-carbon models developed for these purposes produce divergent results in terms of the spatial distribution, seasonal variations and intensity of biosphere fluxes, both in the present and in the future.

The example of carbon is a perfect illustration of the complexity of determining fluxes and the strict need to be able to address the problem by having simultaneous observations and modelling facilities at different scales and by integrating the different compartments of the Earth system. It is therefore a particularly unifying challenge for the DataTerra IR activities.

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Barriers: To make a successful transition from observations of instantaneous quantities (i.e. CO2 concentration) to their spatial and temporal gradients with sufficient precision to allow the determination of fluxes by coupling gradient observations and interface modelling.

2.4.5 Ocean evaporation/precipitation balances

The ocean accounts for 97% of the total water on the planet and therefore plays a key role in the water cycle. In addition to affecting the amount of atmospheric water vapour and thus precipitation, evaporation from the sea surface is important in the movement of heat in the climate system. The water balance and salinity are closely linked by evaporation and precipitation. The Global Conveyer Belt illustrates how ocean currents transport warm surface water from the equator to the poles and thus temper the global climate. Sea Surface Salinity (SSS) is a key tracer for understanding the freshwater cycle in the ocean.

The interface between the ocean and the atmosphere is a place of water and latent heat exchange. A challenge is to assess how melting ice caps and warming of ocean surface waters will affect ocean-atmosphere exchanges, ocean evaporation/precipitation budgets and thermohaline circulation. This will require the ability to track in particular changes in ocean surface salinity.

Barriers: To be able to access a combination of all the data acquired at the ocean-atmosphere interface (in situ, satellites, airborne …); to develop algorithms for processing satellite observations, data assimilation; visualization products statistics.

2.5 HAZARDS IMPACTS ON SOCIETY

Whether they are of natural origin or induced by human activities, the different types of hazards to which the Earth System is subject can have considerable impacts on our societies, depending on the local settings of demographic, urban and industrial development, and in a more global context of globalization. Monitoring and understanding of these hazards thus requires an integrated, cross-cutting approach, combining in-situ and remote sensing data covering all the spatial and temporal scales involved in the underlying physical processes.

2.5.1 Seismic and volcanic hazards

With the increase in the world's population and its densification, many fault zones or active volcanoes are now located near major urban centres. The consequences of an earthquake or an eruption can be local as well as global (e.g. tsunamis, interruption of air traffic...). Better quantification of seismic and volcanic hazards therefore remains a major challenge, upstream of the assessment of associated risks and their management. A key challenge is to provide high-resolution and accurate spatio-temporal monitoring of the deformations associated with these natural objects. This monitoring must be possible at the scale of rocks, at the scale of fault and volcanic systems, as well as at the scale of continents, since the physics of telluric events involves the Earth's internal movements as well as the circulation of fluids on a very small scale. Advances in instrumentation and remote sensing in recent decades (technical or methodological progress) have led to major advances and discoveries: the discovery of slow earthquakes on faults questioning our vision of the seismic cycle, the prediction of certain eruptions and the monitoring of emissions, for example. However, the profusion of data available has led to the emergence of new blockades for the joint analysis of data from various disciplines, the improvement of signal-to-noise ratios (specific to each discipline but

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interconnected, since noise in internal geophysics can be the signal in atmospheric physics and vice versa), or even mechanical modelling integrating all scales of the seismic cycle.

One of the challenges for seismic hazard is to be able to provide global probabilistic models, evolving over time, based on the combination of tectonic, seismological and geodetic (deformation and gravimetry) data. For volcanic hazards, monitoring and warning systems require real-time or near-real-time (NRT) availability of space observations for both high-resolution imagery and products (gas, SO2, aerosols, ...). The development of NRT processing and dissemination capabilities for remote sensing data for the monitored areas must be carried out in conjunction with the availability of other ground and in-situ observation data, both for atmospheric composition and for temperature, deformation and seismicity measurements. The creation of a multidisciplinary data access and visualisation platform for monitoring and studying volcanoes, bringing together observation and modelling capabilities, would be a significant contribution compared with existing systems13.

Barriers: Multi-disciplinary platform for data access and visualization; joint analyses, improved signal-to-noise ratios, signal separation, modelling, real-time calculations (NRT), dissemination of NRT information.

2.5.2 Intensification of hydrometeorological cycles

Climate change induces an intensification of the hydro-meteorological cycle which leads to droughts as well as floods. The operational needs are real but the hydro-meteorological hazards are still poorly identified in the existing series and poorly forecast in the operational services. It is necessary today to better know their variability on a multi-year scale and to provide information on their evolution in the context of climate change. Identifying the laws of extremes in time series poses a theoretical challenge in a changing climate, yet it is necessary to know these laws in order to evaluate models, but also to predict the dimensioning of dams and structures and prevent floods. In recent years, significant advances in the forecasting of intense rainfall events have been made possible by the operational commissioning of non-hydrostatic forecasting models with a resolution of a few kilometres (such as Météo-France's AROME model) allowing the forecasting of flows in catchment basins with a rapid response (such as in the Mediterranean). However, for small basins, an error of a few tens of kilometres can lead to forecasting the flood on the neighbouring basin. The challenge is now to integrate the impacts into coupled hydro-meteorological models. It is therefore necessary to be able to access information on the material and human issues at stake.

Barriers: In order to better predict and model intense rainfall and flash floods, need to better quantify and reduce uncertainties in regional climate predictions and projections by improving our understanding of the processes involved and their representation in numerical models, by developing data assimilation in domains poor in observations, and by developing ensemble prediction methods that make it possible to quantify the predictability of an event. Then it is very crucial to have access for observational data at various scales and over the long term.

2.5.3 Mineral and energy resources

The transition towards decarbonated energies is now inevitable but requires new and considerable needs in mineral resources (metals, rare earths, aggregates...). A number of challenges need to be

13 Par exemple: www.mounts-project.com/ ou //www.mirovaweb.it/

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addressed in order to make this transition a success. Regardless of the technologies used for the production and exploitation of resources, better spatiotemporal monitoring of their environmental impact is essential: in-situ or remote sensing analyses of local pollution, monitoring by geodesy (ground or space) and seismology of soil deformation and stability in the exploitation zones, optimisation of wind turbine networks, etc. Innovative approaches are also to be developed for the search for new resources and their sustainable exploitation minimising the impact on societies and the environment. One example is the development of new imaging (hyperspectral...) and image processing systems for exploration from space (search for lithium...). Another example concerns developments associated with the urban mine.

Barriers: Better quantifying and reducing these hazards therefore requires the mobilization of several compartments of the Earth system (see also section 2.1.5), one of the current obstacles being to be able to cross-reference, among other things, in-situ geological and environmental data, remote sensing imagery data, and even, for some types of resources, our knowledge of the environment (urban, marine, etc.).

3 STRATEGIC NEEDS ON DATA

The priority challenges at the interfaces of the thematic clusters have made it possible to identify common needs in terms of both the availability of data and the ability to combine data from different sources (satellite, in situ, modelling, simulation) and on different scales.

3.1 THE FAIR PRINCIPLES

DataTerra fully subscribes to the principles of Open Science, which aims to make FAIR scientific data, i.e: easily discoverable, accessible, interoperable and reusable. The FAIRisation of data is therefore a priority for DataTerra. Among the diversity of data repositories accessible via the portals of DataTerra, often associated with labelled observation services, have already achieved a high level of FAIRisation. However, there are still many datasets that do not respect this principle.

For the study of the Earth System, through permanent and temporary observations, the basic principle is that the data must be discoverable and accessible, in order to allow interoperability and reuse by all scientific communities. These concepts can be described according to:

- Findable : Being findable means being described by rich metadata, following recognized international standards, in data discovery portals and having a unique persistent identifier (e.g. DOI).

- Accessible : Being accessible means that data can be easily obtained through human intervention or machine-to-machine interaction according to defined protocols. The nature, conditions of access and reuse must be clearly defined (origin, format, license, ...). The metadata, as a minimum, must be accessible in order to keep the dataset discoverable and to allow the author of the dataset to be contacted for a request for access to the data. The licence information must be updatable by the user. DataTerra prefers licenses that require the attribution of the source of the data.

These requirements are coupled with standard principles for repository and service management, including data security and service continuity and robustness. That's why DataTerra promotes the certification of repositories.

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- Interoperable : Interoperability is mandatory for the integration of different datasets into a unique portal. This implies the use of a standards-based vocabulary and a common programming language. DataTerra's Technical WG aims to harmonise these practices across all of the data and service centres.

- Reusable : The optimal application of the three previous principles allows the data to be reused. It is imperative that the data, metadata and user licences are extremely detailed. The producer must be notified of the download of his data.

The application of FAIR principles to the datasets accessible by the DataTerra portal will encourage cross-domain works, where multi-domain interpretations imply that non-specialist researchers are able to use, at least to some extent, data from another domain.

3.2 PROCESSING, CALCULATIONS ET SERVICES

The diversity and volume of data acquired through observation or generated by modelling face fundamental problems from both a methodological and technical point of view. For example, the interpretation, linking and integration into models of data of very different natures (e.g. cross-referencing of geophysical information with biochemical measurements) face methodological problems, even when the volumes of data are limited.

Moreover, the combined growth of data from space observation, modelling and numerical simulation is gradually leading to the need to consider and manipulate volumes of the order of exascale. Developments in these data sources are fuelling a convergence of infrastructures supporting science and mixing observation data and simulations.

To set the orders of magnitude, the reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF, ERA-5) alone represent 9 petabytes (Po) of data. The archive of observations from the various Sentinel satellites reached nearly 10 Po of data in 2018, including 5 Po produced for the year 2018 alone. The forthcoming arrival of Meteosat Third Generation (MTG) data, in particular the infrared sounder, will only amplify this trend.

Technical barriers for the accessibility, handling and processing of such volumes of data are inseparable from infrastructure cost issues. The complexity and heterogeneity of IT systems is increasing even as it becomes more and more expensive to move data. At the same time, the need for scientific expertise and localized user communities close to the data remains important to mobilize the various actors (users and stakeholders). This balance can be achieved through a distributed architecture based on centres with the critical size necessary to meet the need for pooling while guaranteeing a local dynamic and emulation at the national level. This logic has led to the emergence of new distributed service platforms supported by a continuum of infrastructures to accelerate the logistics of this data and facilitate access to these resources. This is the strategy chosen for the construction of the IR DataTerra.

3.2.1 Processing facilities and services

The analysis of very large volumes of data or diverse data hosted in different centres requires the development and implementation of a set of interdisciplinary services and tools based on high-performance computing (HPC). This is a major challenge supported by the European community, in particular through the H2020 PHIDIAS project, to which the IR DataTerra community is contributing. The PHIDIAS objective is to develop the first concrete solutions for this type of massive processing services. Data discovery and logistics services are naturally to be designed in the FAIR spirit. HPC and

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HPDA (High Performance Data Analysis) resources must be put in place to meet the growing need for on-demand analysis and processing. The development of on-demand processing services and the implementation of virtual research environments is also based on:

- open access to standardised high-performance computing (HPC) services;

- the development of new data processing models that can be coupled to HPC means;

- the deployment of processing methods available as services.

Finally, the indispensable reproducibility of the analysis results requires that the processing and analysis chains can be preserved, especially if the volumes of data generated are large and the storage/processing cost ratio becomes important. It then becomes more economical to secure the processing chains and replay them on demand rather than storing voluminous results.

3.2.2 Mathematical method and Artificial Intelligence

On a technical level, apart from the aspects related to the provision of access and the possibility of carrying out massive processing operations on increasingly varied and voluminous data, DataTerra must also make it possible to open up the databases to new communities for which mega-data (big data) is an object of study in itself. Interactions between the geophysical and computer science communities must be encouraged, particularly that of Artificial Intelligence (AI). Sophisticated techniques, particularly those derived from AI, are particularly effective for processing time series, such as the separation of signals from different sources, the detection of anomalies or precursors, and the improvement of the signal-to-noise ratio.

3.2.3 Data mining and added value products

The increase in the quantity and volume of data is leading to difficulties in the appropriation of data by scientific teams, not only at the discovery level, but also in their actual content, their variability, their interdependencies, etc. This leads to the need for an online visualization service: cartography, time series, etc. and geostatistical analysis, inverse modelling, etc.

As it becomes more and more difficult to download data on your workstation, the idea here is to propose virtual laboratories for data analysis and data mining, implemented where the data is stored, on the basis of existing software or libraries (e.g. PANGEO, ...). This includes the prototyping of new algorithms (e.g. through the development of Python, R, ... scripts).

These services require significant computing resources and virtual research environments (VRE): data lake, work storage space (intermediate results), computing resources (CPU, GPU, ...), nodes for interactive links with users. The data lake concept brings together a family of storage tools for searching very large sets of data from multiple and heterogeneous sources.

Downstream products can take many forms, for example:

● Pre-processed data: raw data that has been cleaned of what may be considered noise or false data (e.g. GPS time series corrected for atmospheric effects; or qualification of in situ sensor data against standards).

● Secondary products derived from raw data (e.g. earthquake locations, evapotranspiration fluxes, water quality indicator production)

● Products involving a mixture of modelling and raw data (e.g. wave height models).

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4 METHODOLOGICAL CHALLENGES

The current methodological challenges are related to the explosion in the number and flow of ground and space data and the nesting and multiplicity of spatial and temporal scales involved in the study of the Earth System. These challenges are common to different communities and require strong bridges and interactions between them, which DataTerra must help build. Simplified access to data and common computing means adapted to the massive processing of voluminous data is a first basis (sections 3.1 and 3.2). Other challenges concern more specifically the stages of data processing and analysis (improvement of precision requiring the contribution of complementary disciplines), methods for the joint combination and inversion of data of different origin, resolution and sources of error, and physical modelling approaches which must be able to integrate the different scales of the data.

4.1 UNCERTAINTIES AND SIGNAL SEPARATION

In order to extract observables or parameters useful for a research field, the identification of sources of error, their possible corrections and the quantification of residual uncertainties are essential. Independently of the improvement in the understanding of the physical phenomena causing the errors, it appears important to develop new methods of separating signals in the data, based on the cross-referencing of knowledge specific to each research field, or on the use of data mining and artificial intelligence methods capable of recognising the spatio-temporal signature specific to each signal. In Solid Earth for example, obtaining precise displacement time series from spatial data requires better separation of the ground deformation signals sought (potentially of various origins: tectonic, geodynamic or anthropogenic...) from noise, associated with variations in the hydrological load or delays in wave propagation in the atmosphere. In order to push back the detection limits of some observables, even locally, it is also important to improve global models such as reference systems in geodesy or global atmospheric models, and to make them available to non-specialists.

4.2 ASSIMILATION AND COMBINATION OF MULTI-TEMPORAL AND MULTI-DISCIPLINARY DATA

The analysis of certain phenomena at different spatial and temporal scales, the comparison with existing models or the development of new models, strongly imply being able to use spatial and non-spatial (ground-based in situ) data together. This requires easy access to the data by users and developers of scientific applications and processing facilities to allow joint analyses. In terms of analysis, the steps of collocation of all data, interpolation, inversion and modelling will need to be further improved. This will make it possible to better take into account the specificity of each type of data in terms of spatial and/or temporal resolution and uncertainties, and thus strengthen their complementarity.

4.3 CITIZEN SCIENCE

Recent years have seen the emergence of new types of multidisciplinary projects, at the crossroads of scientific research, participatory democracy and technological innovation. These projects propose concrete modalities of action in favour of better environmental monitoring and an inclusive ecological transition. However, the life cycle of a citizen science project raises new issues and unique challenges.

Participatory science must in the future enable the acquisition of mass data that can be used by researchers. They must also make it possible to develop communication towards the citizen and to

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provide expert feedback. However, the success of this type of project requires the control and implementation of processes, many of which must be developed, shared and pooled: calibration (when sensors are used), data production, validation, data distribution, quality control, correction of drift over time, project management, restitution of results, etc. The FAIR principle generally takes on great importance in these projects. The data centres can be the reference for many of the processes implemented in these projects.

5 TRAINING AND COMMUNICATION NEED

The project aims to promote the use and analysis of observational and modelling data of increasing volume and complexity. The management of such databases is a dynamic field, where computer tools are constantly evolving and still unfamiliar to most scientists, and almost inaccessible to civil society. This creates new training challenges for the communities concerned.

5.1 INTERNAL TRAINING OF DATA TERRA ACTORS

The project will enable the use and analysis of data from multiple sources. This requires rigorous production mechanisms for increasingly large and complex data sets. The challenge for data centres will be to maintain long-term quality assurance and accessibility of archived data by keeping them up to date, archiving and data conservation protocols such as vocabulary, support for changes in format, storage medium, harvesting protocols, etc... in concertation with DataTerra. They must also comply with the FAIR approach and recognised certifications (e.g. Core Trust Seal). This implies continuous training of colleagues in the data and service centres. This training will be carried out through DataTerra internal technical workshops, which will allow exchanges of experience and practical work. The personnel of DataTerra data and service centres will also benefit from training provided by other national and European organisations such as RDA-France, EOSC (seminars, webinars).

5.2 SCIENTIFIC COMMUNITY TRAINING:

Structuring DataTerra will provide access to an unprecedented flow of observational and modelling data and innovative virtual tools. However, many scientists are not yet familiar with such uses, or even have no in-depth training in data science and programming. The training challenge for the scientific community is threefold:

5.2.1 From harvesting to data FAIRisation

Improve the training of scientists in the design and implementation of effective Data Management Plans (DMPs) in line with FAIR principles;

These training sessions can be carried out on a self-training basis using documents, videos and webinars made available on the IR DataTerra and Data Pole websites.

5.2.2 Learning the use of observational and modelling data sets

The aim is to develop specialized training to provide a practical approach to the system to inform about available data and products, and how to discover data as an online visualization service, mapping, time series. It will also be necessary to train on the conditions of use of the data and respect of sources (DOI, common creative licenses).

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5.2.3 On-demand service utilization learning

There will be two levels to consider:

● initiation: strengthen the capacities of scientists to adopt in their work the use of the tools made

available (remote work, cloud, geostatistical analyses, combination of data from different sources for the same area, ...) ;

● expert: gain experience on how to analyze and interpret data with given options on coding

languages (Python).

These trainings can be organised by DataTerra or in collaboration with the Universities involved in DataTerra.

5.3 COMMUNICATIONS ABOUT OUR WORK:

DataTerra will continue:

- its voluntary approach of informing the scientific community through participation in national symposia and seminars in the research units. The aim of these participations is to inform about the existence of IR DataTerra and its services.

- the diffusion of news on their web pages and via social networks (twitter, ...).

Communications to civil society: Special attention should be paid to the transfer of knowledge to civil society. Many data are of interest to managers and stakeholders, and even citizens, who are often not used to or have the scientific bases to navigate the data and services portal. A communication effort will have to be put in place by DataTerra to present data in a simple and synthetic way. For example, the climatology of coastal waters can be declined in a public version with a presentation of the year's data and comparison with historical data or comparison of different sites. This data communication action is very important in a context of global changes to provide factual information on the evolution of the Earth and the Environment.

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