Holger Tost

Professor

Johannes Gutenberg Universität Mainz

Germany

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Professor Holger Tost is a faculty member at Johannes Gutenberg Universität Mainz, Germany. His research primarily focuses on atmospheric science, particularly in the areas of deep convective clouds, aerosol chemistry, and the impact of land cover changes on climate. Recent works include studies on machine learning applications for cloud organization and improvements in particle measurement techniques, contributing to a deeper understanding of global atmospheric dynamics.

Articles (18)

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2025

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2023

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2021

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2020

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2020

Collaborators (8)

Patrick Jöckel

Deutsches Zentrum für Luft- und Raumfahrt (DLR)

GERMANY

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Konrad Kandler

Technische Universität Darmstadt

GERMANY

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Odran Sourdeval

Associate Professor

Université de Lille

FRANCE

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Ryan Vella

ETH Zürich

SWITZERLAND

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Steffen Beirle

Max Planck Institute for Chemistry

GERMANY

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Georgiy Stenchikov

SAUDI ARABIA

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Klaus Klingmüller

Max Planck Institute for Chemistry

GERMANY

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Michael Höpfner

Karlsruhe Institute of Technology

GERMANY

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Holger Tost

Research Interests

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About

Articles (18)

New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)

Improving the accuracy in particle concentration measurements of a balloon-borne optical particle counter, UCASS

A machine-learning-based perspective on deep convective clouds and their organisation in 3D – Part 1: Influence of deep convective cores on the cloud life cycle

A machine-learning-based perspective on deep convective clouds and their organisation in 3D – Part 2: Spatial–temporal patterns of convective organisation

Changes in global atmospheric oxidant chemistry from land cover conversion

Influence of land cover change on atmospheric organic gases, aerosols, and radiative effects

Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4

Divergent convective outflow in ICON deep-convection-permitting and parameterised deep convection simulations

How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy

Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data

Divergent convective outflow in large-eddy simulations

Isoprene and monoterpene simulations using the chemistry–climate model EMAC (v2.55) with interactive vegetation from LPJ-GUESS (v4.0)

Evolution of squall line variability and error growth in an ensemble of large eddy simulations

The effect of ash, water vapor, and heterogeneous chemistry on the evolution of a Pinatubo-size volcanic cloud

Changes in biogenic volatile organic compound emissions in response to the El Niño–Southern Oscillation

Cold cloud microphysical process rates in a global chemistry–climate model

Superparameterised cloud effects in the EMAC general circulation model (v2.50) – influences of model configuration

Including vegetation dynamics in an atmospheric chemistry-enabled general circulation model: linking LPJ-GUESS (v4.0) with the EMAC modelling system (v2.53)

Collaborators (8)

Patrick Jöckel

Konrad Kandler

Odran Sourdeval

Ryan Vella

Steffen Beirle

Georgiy Stenchikov

Klaus Klingmüller

Michael Höpfner

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