Mesoscale organisation of tropical convection
MAESTRO aims to develop observational methods to understand mesoscale convection's impact on climate and improve climate models through advanced airborne remote sensing and analysis frameworks.
Projectdetails
Introduction
Recent research has shown that the spatial organisation of convection (and hence clouds) at the mesoscale (20-200 km) dramatically affects the Earth's energy balance and hydrological cycle. This raises the question as to how the organisation of convection will change with warming, and how it will influence the climate.
Challenges in Understanding Convection
A poor understanding of the physical drivers of the mesoscale organisation of convection, compounded by an inability to simulate and observe such processes, has hampered our ability to articulate this challenging question, let alone answer it.
Objectives of MAESTRO
In MAESTRO, I propose to develop observational approaches and analysis frameworks specifically designed to test mechanisms hypothesized to control the mesoscale organisation of both shallow and deep convective clouds.
Methodology
Advances in airborne remote sensing will be exploited to:
- Map the spatial structures of clouds and water vapor.
- Interpret their coupling through the analysis of coherent structures within the clear-air environment around clouds.
- Understand their dependence on environmental conditions.
Expected Outcomes
This will help to understand:
- Why and how convective clouds organise at the mesoscale.
- Why the organisation co-varies with water vapor, clouds, and radiation locally and remotely.
- Why it co-varies with climate conditions.
Integration of Observations
By connecting observations from the airborne measurements to satellite observations and meteorological analyses, the generality of the insights from the field measurements will be tested and tempered.
Assessment of Climate Models
Finally, observational insights will be used to assess the new and emerging generation of climate models whose resolution is fine enough to represent the mesoscale organisation of convection and its interaction with climate.
Conclusion
MAESTRO will lead to:
- New experimental techniques for studying atmospheric processes.
- An improved conceptualization of the interplay between convective organisation and climate.
- A critical assessment of the new generation of climate models for climate change studies.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.994.634 |
Totale projectbegroting | € 2.994.634 |
Tijdlijn
Startdatum | 1-7-2023 |
Einddatum | 30-6-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRSpenvoerder
- METEO-FRANCE
- UNIVERSITE DE VERSAILLES SAINT-QUENTIN EN YVELINES
- ECOLE NORMALE SUPERIEURE
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Unlocking the mesoscale frontier of cloud-climate uncertaintyThe project aims to develop a novel framework for predicting mesoscale cloudiness using satellite imagery to reduce climate projection uncertainties and enhance future cloud research. | ERC Starting... | € 1.499.070 | 2024 | Details |
Order at the Mesoscale: Connecting supercomputing of compressible convection to classical and quantum machine learningMesoComp aims to understand turbulent convection superstructures through high-fidelity simulations and machine learning, enhancing climate predictions and solar activity models. | ERC Advanced... | € 2.500.000 | 2023 | Details |
Rain and cloud Organization in the Trades using ObseRvations and modelsROTOЯ aims to enhance understanding of shallow trade cumulus clouds' response to climate change by analyzing rain evaporation and cold pools through innovative observations and simulations. | ERC Starting... | € 1.499.768 | 2024 | Details |
Revisiting Rainfall Extremes with Ensembles of Convective Objects aNd their Continuum of Interactions with the Large-scale EnvironmentRECONCILE aims to enhance climate models by analyzing storm populations' dynamics, bridging scales to reduce uncertainties in extreme precipitation projections linked to climate change. | ERC Starting... | € 1.322.000 | 2023 | Details |
Observing, Modeling, and Parametrizing Oceanic Mixed Layer Transport ProcessesThis project aims to quantify ocean mixed-layer dynamics by simulating and measuring submesoscale currents' effects on vertical transport, enhancing climate models and biogeochemical understanding. | ERC Starting... | € 2.422.688 | 2025 | Details |
Unlocking the mesoscale frontier of cloud-climate uncertainty
The project aims to develop a novel framework for predicting mesoscale cloudiness using satellite imagery to reduce climate projection uncertainties and enhance future cloud research.
Order at the Mesoscale: Connecting supercomputing of compressible convection to classical and quantum machine learning
MesoComp aims to understand turbulent convection superstructures through high-fidelity simulations and machine learning, enhancing climate predictions and solar activity models.
Rain and cloud Organization in the Trades using ObseRvations and models
ROTOЯ aims to enhance understanding of shallow trade cumulus clouds' response to climate change by analyzing rain evaporation and cold pools through innovative observations and simulations.
Revisiting Rainfall Extremes with Ensembles of Convective Objects aNd their Continuum of Interactions with the Large-scale Environment
RECONCILE aims to enhance climate models by analyzing storm populations' dynamics, bridging scales to reduce uncertainties in extreme precipitation projections linked to climate change.
Observing, Modeling, and Parametrizing Oceanic Mixed Layer Transport Processes
This project aims to quantify ocean mixed-layer dynamics by simulating and measuring submesoscale currents' effects on vertical transport, enhancing climate models and biogeochemical understanding.