Use the future to build the present
Physical Models
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Stakeholder Type
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1Quantum Revolution& Advanced AI2HumanAugmentation3Eco-Regeneration& Geo-Engineering4Science& Diplomacy1.11.21.31.42.12.22.32.43.13.23.33.43.54.14.24.34.44.5HIGHEST ANTICIPATIONPOTENTIALAdvancedArtificial IntelligenceQuantumTechnologiesBrain-inspiredComputingBiologicalComputingCognitiveEnhancementHuman Applications of Genetic EngineeringRadical HealthExtensionConsciousnessAugmentation DecarbonisationWorldSimulationFuture FoodSystemsSpaceResourcesOceanStewardshipComplex Systems forSocial EnhancementScience-basedDiplomacyInnovationsin EducationSustainableEconomicsCollaborativeScience Diplomacy
1Quantum Revolution& Advanced AI2HumanAugmentation3Eco-Regeneration& Geo-Engineering4Science& Diplomacy1.11.21.31.42.12.22.32.43.13.23.33.43.54.14.24.34.44.5HIGHEST ANTICIPATIONPOTENTIALAdvancedArtificial IntelligenceQuantumTechnologiesBrain-inspiredComputingBiologicalComputingCognitiveEnhancementHuman Applications of Genetic EngineeringRadical HealthExtensionConsciousnessAugmentation DecarbonisationWorldSimulationFuture FoodSystemsSpaceResourcesOceanStewardshipComplex Systems forSocial EnhancementScience-basedDiplomacyInnovationsin EducationSustainableEconomicsCollaborativeScience Diplomacy

Sub-Field:

3.2.1Physical Models

Predicting the future state of the physical world under the influence of human activities includes sensing and modelling of weather and climate, ocean flows, terrestrial hydrology and erosion. Global climate models, seismological models and sea-ice models, for example, already draw on a vast web of physical-chemical observational and socio-economic data, giving us an unprecedented capacity to predict future states of land, sea, and air. The development of cheaper and improved sensors, increased availability of autonomous research craft, including underwater vehicles, and remote sensing from space will lead to an explosion of available data.
But we are just getting started — our data-driven physical models of Earth's systems are set to grow ever more refined. Consider, for example, Destination Earth (DestinE), a major initiative of the European Commission.4 Its ambitious aim is to create “a digital twin of planet Earth that would simulate the atmosphere, ocean, ice, and land with unrivalled precision, providing forecasts of floods, droughts, and fires from days to years in advance.”5

Future Horizons:

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5-yearhorizon

High-resolution modelling enables urban weather simulations

Physical modelling is already an advanced science, utilising models at a planetary scale. But high-resolution refinements are on the horizon, initially for densely populated areas, including micro-climate weather simulations in urban areas. Global ocean flows are routinely modelled as part of climate models and can be coupled to increasingly accurate models of local scales and near-shore circulation patterns, including physical and chemical water properties, which are particularly complex, and important, for coastal ecosystems.

10-yearhorizon

Abundant contextualised data becomes available

High-resolution models for physical processes, initially demonstrated for select locations, become both more accurate and more widely available. This is driven by increased availability of computational resources, but more importantly, by increased availability of well-contextualized FAIR data. That is, data which meet principles of Findability, Accessibility, Interoperability, and Reusability. As these FAIR data become linked to downstream use and reuse, value is unleashed throughout the data lifecycle, accelerating the deployment of machine learning.6

25-yearhorizon

Accurate simulations extended to remote populations

The availability, spatial and temporal resolution of data continues to improve, with geostationary and stratospheric platforms for recording of high-frequency processes able to investigate even remote areas of the planet with high fidelity. Computing capabilities and modelling improves for even more accurate predictions at finer scales that will now be rolled out also to remote and less densely populated areas.

Physical Models - Anticipation Scores

How the experts see this field in terms of the expected time to maturity, transformational effect across science and industries, current state of awareness among stakeholders and its possible impact on people, society and the planet. See methodology for more information.

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