Clouds are one of the main causes of uncertainty in predictions of future climate, and are a key challenge in improving weather forecast models. Led by Professor Robin Hogan, the Clouds Group develops novel radar and lidar techniques to retrieve cloud properties remotely, applies these techniques to understand cloud processes and to evaluate and improve numerical weather forecast and climate models, and develops efficient numerical methods for atmospheric radiative transfer.

Note that since April 2014, Robin Hogan's primary affiliation is ECMWF, so group membership is in decline, but selected threads of research are continuing and these pages are being maintained.

Ongoing projects

Observations and modelling of convective storms

In the NERC-funded project Dynamical and Microphysical Evolution of Convective Storms (DYMECS), we are using the high resolution Chilbolton radar to map the 3D structure of shower clouds and thunderstorms as they evolve. Since spring 2011 we have gathered statistics on over 1000 storms on over 35 individual days. We are now evaluating the high resolution model used for UK weather forecasts in various configurations. This work is being performed in close collaboration with the Met Office Mesoscale Modelling Research Group based in Reading.

Active remote sensing of clouds from satellite

We are leading the European development of synergistic cloud and precipitation retrievals for the EarthCARE mission to be launched in 2015. We have already pioneered operational radar-lidar retrievals of ice clouds from the A-train of satellites, and our retrievals are available for download. We have used these observations to evaluate clouds in forecast models, and supporting developments include a fast model for radar and lidar multiple scattering and a fast software library for automatic differentiation. This work is supported by ESA and NCEO.

Evaluating and improving the physics of clouds in models

We use long-term ground-based radar and lidar observations to evaluate and improve the representation of clouds and associated processes in models. We are involved in the FASTER project to take what was learned in the Cloudnet project to perform long-term evaluation of clouds in weather models. We are using such observations to understand why most models simulate mixed-phase clouds very poorly. We are using Doppler lidar to evaluate the performance of forecasts of boundary-layer type. Our model verification work has led to developments in verification theory, including our finding that the widely used "Equitable Threat Score" is not in fact equitable.

Clouds, radiation and climate

We develop novel radiative transfer techniques for more accurate represention of the interaction of solar and infrared radiation in climate models. Recent work includes using our "Tripleclouds" scheme to estimate the global impact of the neglect of sub-grid cloud structure in climate models, and development of the full-spectrum correlated-k method for efficient treatment of gases in the infrared. We are currently working on a scheme to efficiently represent the flow of radiation through the sides of clouds, which will be used to calculate the impact of this phenomenon in climate models. This work is supported by NERC.

Code for download

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