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Earth Systems: Oceans to Near Space icon
Earth Systems: Oceans to Near Space

Earth is the epitome of interconnection. Greatly transcending the sum of its parts, the planet functions and sustains life through a complex web of interdependence. Observing the full expanse of these connections and interactions – from the depths of the ocean to the furthest reaches of the atmosphere – is essential for understanding Earth’s subsystems of oceans, land, air and near space, and the intricate dynamics among them.

In this area, MPP researchers are putting particular emphasis on measurement and monitoring. Projects involve developing technologies and capabilities through technological innovation, big data and comprehensive systems analysis. There is also a focus on autonomous operations to enable exploration and research, including field deployment of autonomous ocean research vessels. Human-machine concept of operations (ConOps) applied to small-satellite technology and launch capabilities is another research focus.

Funded Projects

  • Calls: 2025 Call for Seed Grant Proposals

    Research Areas: Earth Systems: Oceans to Near Space

    Abstract

    Near the sea surface, interactions between small-scale ocean processes, turbulence, and Earth’s climate are not fully resolved by either models or observations. However, we can make decisive progress by fusing models with data through innovative AI techniques. We propose to advance understanding by integrating MIT’s ocean models with satellite data from the Azores ESA Lab. Our focus is on two critical regions for climate change, where well developed AI techniques can help address key questions about small-scale processes. In the Azores region, we will forecast thermal fronts, mesoscale eddies, internal waves, and other mixing indices. Additionally, we will train AI to detect and predict internal waves at the equator during La Ninã seasons, where their interactions with thermal fronts have important implications for climate. In both cases, simulation data from MIT models will be used to train generative AI and fine-tune foundation models, which will then be applied to satellite data.

    MIT PI
    Gael Forget, Research Scientist, Department of Earth, Atmospheric & Planetary Sciences

    PT PI
    Dr. Adriana Ferreira (AIR Centre)
    Dr. Jorge M. Magalhães (CIIMAR)
    M. João Pinelo (AIR Centre)
    Pr. José da Silva (FCUP)

    This is a two-year grant

  • Calls: 2024 Call for Seed Grant Proposals

    Research Areas: Earth Systems: Oceans to Near Space

    Abstract

    There are a variety of high-impact opportunities in Portugal to leverage advanced membrane technologies for desalination, ion recovery, and power generation. Unfortunately, current membrane materials lack the structural and functional-group characteristics needed to enable these technologies, so this proposal aims to infuse new materials concepts into membrane technology to address the water–mineral–energy nexus. The two research teams are uniquely positioned for this work. The Smith lab is a world leader in membrane materials but has not focused significant prior effort on aqueous separations. In contrast, the Crespo group has a longstanding effort in aqueous separations for desalination, lithium recovery, and energy generation. Taken together, this proposal will leverage a unique series of membrane materials developed by the Smith lab to address major application challenges in water, minerals, and energy through a robust collaboration and exchange with the Crespo group.

    MIT PI
    Zachary P. Smith, Associate Professor, Department of Chemical Engineering

    PT PI
    Prof. João Crespo, Full Professor of Chemical and Biological Engineering, NOVA University Lisbon

    This project is extended

  • Calls: 2026 Call for Joint Integrated and Seed Grant Proposals

    Research Areas: Earth Systems: Oceans to Near Space

    Abstract 

    Autonomous systems are rapidly advancing in both aerial and maritime domains, yet integrated air-sea autonomy remains rare. Our “Adaptive Intelligent Sea and Air Formations for Environmental Responses” (AI-SAFER) project will pioneer robust, reproducible coordination of air-sea robots for environmental monitoring, security, infrastructure protection, disaster response, and adaptive sensing in the Portugal-Azores region. AI-SAFER combines multiscale probabilistic ocean and acoustic modeling with Bayesian and generative data assimilation, principled multi-objective reachability analysis and path planning based on differential equations, and deep reinforcement learning for rapid optimization. These components will enable autonomous air-sea formations to execute optimal hazards-time-coverage missions, adapting to uncertain ocean and weather conditions. Our MIT-Portugal collaboration will simulate and field-test the system in Portugal. AI-SAFER will advance robust air-sea autonomy, contributing to climate resilience, maritime operations, transport, and security, with benefits for Portugal, the EU, the US, and global ocean-monitoring initiatives.

    MIT PI
    Pierre F.J Lermusiaux, Professor, Department of Mechanical Engineering 

    PT PI
    João Borges de Sousa, Professor, Department of Electrical and Computer Engineering Department, Porto University in Portugal

    Additional collaborators
    John Leonard, Professor, Department of Mechanical Engineering, MIT
    Renato Mendes, Post-doctoral researcher, Faculty of Engineering, University of Porto, LAETA-INEGI
    Leonardo Azevedo, Professor, CERENA, University of Lisbon (IST). 

Posters

PhD Students

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    Headshot of Ana Filipa Duarte

    Ana Filipa Duarte

    Portugal
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    Photo of Andry Castro

    Andry Castro

    PhD Student

    Portugal
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    Photo of Beatriz Biguino

    Beatriz Biguino

    PhD Student

    Portugal
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    Photo of Camila Penso

    Camila Penso

    PhD Student

    Portugal
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    Photo of Catarina Santos

    Catarina Santos

    PhD Student

    Portugal
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    Photo of Erany Constantino

    Erany Constantino

    PhD Student

    Portugal
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    Photo of Gil Serrano

    Gil Serrano

    PhD Student

    Portugal
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    Photo of Giulia Sent

    Giulia Sent

    PhD Student

    Portugal
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    Photo of Glauco Nobrega

    Glauco Nobrega

    PhD Student

    Portugal
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    Photo of Joana Couceiro

    Joana Couceiro

    PhD Student

    Portugal
  • Image
    Photo of João Fonseca

    João Fonseca

    PhD Student

    Portugal
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    Photo of João Rocha

    João Rocha

    PhD Student

    Portugal
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    Photo of Leandro Madureira

    Leandro Madureira

    PhD Student

    Portugal
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    Photo of Matilde Marques

    Matilde Marques

    PhD Student

    Portugal
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    Photo of Miguel Fernandes

    Miguel Fernandes

    PhD Student

    Portugal
  • Image
    Photo of Raquel Fernandes

    Raquel Fernandes

    PhD Student

    Portugal
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    Photo of Rita Dantas

    Rita Dantas

    PhD Student

    Portugal
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    Photo of Rita Pombo

    Rita Pombo

    PhD Student

    Portugal
  • Image
    Photo of Sara Aparício

    Sara Aparício

    PhD Student

    Portugal

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