Hamish Gordon

About

Hamish Gordon is an Associate Professor in the Department of Chemical Engineering at Carnegie Mellon University, with courtesy appointments in Civil and Environmental Engineering and Mechanical Engineering. His research interests are centered on the effects of air pollution and natural airborne particles on clouds and climate. He is involved in developing weather prediction and climate models to better represent airborne particulate matter and its influence on cloud formation and atmospheric processes. His work includes simulating specific regions at high resolution, comparing these simulations with detailed atmospheric observations, and participating in laboratory experiments to improve model accuracy. Gordon's research also involves participation in significant atmospheric science experiments, such as the CLOUD experiment at CERN, which studies the formation of new particles in the atmosphere from gases like sulfuric acid, and aircraft studies examining how smoke interacts with clouds over the South Atlantic Ocean. His educational background includes a BA and MS from the University of Cambridge and a Ph.D. in Physics from the University of Oxford. He joined Carnegie Mellon University in 2019 after a postdoctoral position at the University of Leeds. Gordon has been recognized with awards such as the NSF CAREER award and the DOE atmospheric research grant, reflecting his contributions to understanding aerosol-cloud interactions, air pollution, and climate resilience.

Research topics

• Geology
• Geography
• Meteorology
• Climatology
• Physics
• Environmental science
• Atmospheric sciences
• Remote sensing
• Optics
• Oceanography

Selected publications

• The ATLAS Experiment at the CERN Large Hadron Collider

  2008 · 2387 citations

  The Large Hadron Collider (LHC) at CERN will extend the frontiers of particle physics with its
\nunprecedented high energy and luminosity. Inside the LHC, bunches of up to 1011 protons (p)
\nwill collide 40 million times per second to provide 14 TeV proton-proton collisions at a design
\nluminosity of 1034 cm􀀀2s􀀀1. The LHC will also collide heavy ions (A), in particular lead nuclei, at
\n5.5 TeV per nucleon pair, at a design luminosity of 1027 cm􀀀2s􀀀1.
\nThe high interact…

• The hemispheric contrast in cloud microphysical properties constrains aerosol forcing

  Proceedings of the National Academy of Sciences · 2020 · 172 citations

  Senior authorCorresponding

  The robustness of this constraint depends upon the assumption that pristine Southern Ocean droplet number concentration is a suitable proxy for preindustrial concentrations. Droplet number concentrations calculated from satellite data over the Southern Ocean are high in austral summer. Near Antarctica, they reach values typical of Northern Hemisphere polluted outflows. These concentrations are found to agree with several in situ datasets. In contrast, climate models show systematic underpredicti…

  DOI

• Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble

  Atmospheric chemistry and physics · 2025-04-25 · 5 citations

  articleOpen access

  Abstract. Aerosol–cloud interactions (ACIs) are the largest source of uncertainty in inferring the magnitude of future warming consistent with the observational record. The effective radiative forcing due to ACI (ERFaci) is dominated by liquid clouds and is composed of two terms: the change in cloud albedo due to redistributing liquid over a larger number of cloud droplets (Nd) and the change in cloud macrophysical properties due to changes in cloud microphysics. These terms are, respectively, r…

  PublisherOA PDFDOI

• Development of an Integrated Modeling Framework for Visibility and Air Quality Forecasting in Delhi

  Bulletin of the American Meteorological Society · 2025-01-16 · 5 citations

  articleOpen access

  Abstract Rapid urbanization has subjected the megacities of developing countries to various environmental stresses. Delhi, a major Indian megacity, faces increasing urban stress leading to reduction in air quality and visibility. These challenges necessitate an integrated modeling framework to mitigate adverse environmental impacts on public health. Therefore, we have developed an advanced version of the high-resolution Delhi Model with Chemistry and aerosol framework (DM-Chem) at the National C…

  PublisherOA PDFDOI

• Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0)

  Geoscientific model development · 2025-08-11 · 5 citations

  articleOpen accessSenior author

  Abstract. The representation of aerosol activation is a key source of uncertainty in global composition-climate model simulations of aerosol–cloud interactions. The Abdul-Razzak and Ghan (ARG) activation parameterization is used in several global and regional models that employ modal aerosol microphysics schemes. In this study, we investigate the ability of the ARG parameterization to reproduce simulations with a cloud parcel model and find its performance is sensitive to the geometric standard…

  PublisherOA PDFDOI

Frequent coauthors

• S. De Cecco

  Radboud University Nijmegen

  573 shared

• L. Li

  535 shared

• B. Trocmé

  Laboratoire AstroParticule et Cosmologie

  504 shared

• T. Beau

  Consejo Nacional de Investigaciones Científicas y Técnicas

  501 shared

• L. Roos

  Laboratoire de Physique Nucléaire et de Hautes Énergies

  480 shared

• M. Ridel

  Université Paris Cité

  480 shared

• S. Trincaz-Duvoid

  Laboratoire de Physique Nucléaire et de Hautes Énergies

  480 shared

• J. Ocariz

  Université Paris Cité

  467 shared

Labs

• Hamish Gordon's LabPI

  Not provided

Education

• B.S.

  University of Cambridge

  2009

• Ph.D., Experimental High Energy Physics

  University of Oxford

  2013

Awards & honors

• NSF CAREER Award (2023)
• National Defense Science and Engineering Graduate Fellowship…
• Conference on Probability and Statistics Oral Student Presen…

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