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Daniel Grosvenor

Research Fellow, School of Earth & Environment, University of Leeds

Daniel Grosvenor did his Physics w/ Astrophysics Mphys at UMIST. This was followed by a PhD at the University of Manchester supervised by Prof. Tom Choularton entitled “Tropical Deep Convection: The Effect on the Water Content of the Upper Troposphere and Lower Stratosphere and the Response to Aerosol”. Whilst there he also worked on aircraft observations and modelling of Antarctic clouds and flow over the Antarctic Peninsula. He then moved to Seattle, USA to work at the University of Washington with Prof. Rob Wood where he developed improved satellite microphysical observational datasets and applied them to investigating science problems and assessing the representation of low clouds in climate models.

Research Interests


It is known that aerosol-cloud interactions are involved in a number of radiatively important phenomena that are not yet captured in climate models. For example, aerosol is known to play a key role in the formation of Pockets of Open Cells in stratocumulus, which are huge areas of low albedo open cells that form in regions that are normally dominated by high albedo closed cells (see image above). Such processes involve scales and feedbacks that are sub-grid for current climate models and so need to be parameterized. Yet, important aerosol-cloud-dynamical feedbacks may also occur at scales beyond those of single cloud cells and the small spatial regions that are often simulated in parcel and LES models.

We aim to simulate a variety of aerosol-cloud feedback regimes using a system-wide approach through the use of large-domain simulations at convection resolving horizontal resolution. A new sophisticated microphysics scheme has recently been added to the Met Office Unified Model (UM) that facilitates the simulation of the effects of aerosols upon clouds and vice versa (e.g. cloud processing of aerosol). The coupling of the UKCA aerosol model will produce a powerful tool for examining the effects of realistic aerosol fields upon clouds. The model will also be combined with a new parameterization to represent sub-grid updraft spectra and potentially other parameterizations (e.g. entrainment) in order to capture physics occurring at scales smaller than the resolved resolution of the mesoscale model. This new version of the UM will be tested against observations and high resolution LES simulations to determine whether it accurately captures the aerosol-cloud interaction processes for a variety of cloud regimes. The model will then be used to understand the dominant physics acting for the different situations to enable the development of a practical framework for parameterizing aerosol-cloud interactions in coarse scale models.


This work concerns the development of improved satellite microphysical observational datasets and their application to investigating science problems. The main effort of this work has been to produce reliable cloud droplet concentration data. Droplet concentration is a valuable quantity since it is fundamentally connected with aerosol processes and thus gives insight into the aerosol and CCN budget.

The dataset that I have produced is unique because it allows the study of high latitude clouds, such as those in the Arctic and in the Southern Ocean; we have demonstrated that the standard MODIS climatology cannot be reliably used in these regions because of retrieval artefacts at high solar zenith angles. I have quantified the impacts of these artefacts and then reprocessed individual MODIS granules from one year of global data to remove the data that was likely to be bad. The aforementioned regions are the cloudiest on Earth with consequently very large Cloud Radiative Forcing effects, despite the reduced short wave input relative to low latitudes. We are in the process of exploiting this dataset to look at the seasonal cycle of Southern Ocean droplet concentrations and the impact of this upon the Earth's solar radiation budget.


We have been working towards the development of a test-bed to assess the representation of low clouds in GCMs. This utilizes aircraft observations, satellite observations of cloud fraction, liquid water path, boundary layer height, precipitation rates and a cloud droplet dataset from MODIS. The work takes place as part of a Climate Process Team and with the aim of testing of a new PDF based cloud parameterization called CLUBB.

Teaching Interests

I feel that passing on knowledge to the next generation of students is vital for the future of science and society, but I also find teaching personally fulfilling and highly rewarding. I am always willing to take several opportunities to teach and to take part in outreach events. Here is a brief summary of some of my experience.

I have worked closely, as de facto advisor, with two Ph.D. students, helping them to design and implement their research projects.
Gave undergraduate tutorial classes during which I came to realise that very little of the lectures had sunk in for the students and I received several comments from the students that my explanations had helped them to gain a firm understanding of the material, which was demonstrated by their ability to answer further related questions. It also shows that lectures need to be improved!
Helped to staff a table on weather forecasting at a public science fair. It was very rewarding to have many children and parents thank us for giving up our time in order to communicate the exciting nature of atmospheric science and its applications!
Through the auditing of classes from the Atmospheric Sciences graduate programme at the University of Washington I have had recent exposure to high quality teaching methods and syllabus material, as well as gaining renewed first-hand insight into how lectures and course materials are received by the students.


  • –present
    Research Fellow, School of Earth & Environment, University of Leeds