Matthew McGill

Professor

Iowa State University

United States

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Matthew McGill is a Professor at the University of Iowa, USA. His research focuses on the application of machine learning techniques in the analysis of atmospheric data, particularly in the detection and classification of clouds and aerosols using space-based lidar measurements. Recent publications include studies on global aerosol climatology, real-time layer detection, and the impacts of aerosols on climate dynamics.

Articles (12)

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2025

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2025

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2024

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2023

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2022

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2021

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2021

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2021

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2021

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2020

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2020

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2020

Collaborators (6)

Sha Feng

Affiliate Assistant Research Professor

Pennsylvania State University

UNITED STATES

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Kenneth Davis

Professor of Atmospheric and Climate Science

Pennsylvania State University

UNITED STATES

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Sandip Pal

UNITED STATES

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Tobias Gerken

Assistant Professor

James Madison University

UNITED STATES

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Natasha Miles

Associate Research Professor

Pennsylvania State University

UNITED STATES

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Antonio Di Noia

University of Bremen

GERMANY

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Matthew McGill

Research Interests

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About

Articles (12)

Using Multitask Machine Learning to Type Clouds and Aerosols from Space-Based Photon-Counting Lidar Measurements

Global Aerosol Climatology from ICESat-2 Lidar Observations

Leveraging Deep Learning as a New Approach to Layer Detection and Cloud–Aerosol Classification Using ICESat-2 Atmospheric Data

Machine learning-enabled real-time detection of cloud and aerosol layers using airborne lidar

Aerosol Detection from the Cloud-Aerosol Transport System on the International Space Station: Algorithm Overview and Implications for Diurnal Sampling

Atmospheric Carbon and Transport – America (ACT-America) Data Sets: Description, Management, and Delivery

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

First retrieval of absorbing aerosol height over dark target using TROPOMI oxygen B band: Algorithm development and application for surface particulate matter estimates

Wildfire-Induced CO Plume Observations From NAST-I During the FIREX-AQ Field Campaign

Observation and quantification of aerosol outflow from southern Africa using spaceborne lidar

Sensitivities in Satellite Lidar-Derived Estimates of Daytime Top-of-the-Atmosphere Optically Thin Cirrus Cloud Radiative Forcing: A Case Study

The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) airborne field campaign

Collaborators (6)

Sha Feng

Kenneth Davis

Sandip Pal

Tobias Gerken

Natasha Miles

Antonio Di Noia

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