Exploiting multi-wavelength radar Doppler spectra to characterise the microphysics of ice hydrometeors

Lead Research Organisation: University of Reading
Department Name: Meteorology


The formation of ice particles in cold clouds is a vital component of the hydrological cycle. These particles redistribute water in the troposphere, as well as reflecting and absorbing visible and infrared light. Recent studies have shown that the evolution of these particles and the way in which they are distributed throughout a cloud layer is important if we are going to correctly simulate the earth's present and future climate. This evolution and distribution is a subject of considerable uncertainty however.

Remote-sensing techniques such as radar are a powerful tool to probe the ice particles in natural clouds. The small amount of power reflected back to the radar by the ice particles contains information on the mass, shape and dimensions of the particles, while changes in the phase of the reflected wave contain information on how fast those particles fall (the Doppler spectrum).

In this project we will develop a new technique to derive the properties of ice particles from radar measurements at 3 different wavelengths. While in the past many assumptions would need to be made a-priori when interpreting the radar data, the extra information content of the full Doppler spectrum at 3 wavelengths allows us to straightforwardly resolve these uncertainties.

Once the technique has been developed, we can derive the microphysical properties of the cloud, such as the distribution of ice particles with size, the relationship between a particle's mass and its size, and how fast the particles fall as a function of their size. This information is key to the accurate representation of clouds and precipitation in numerical weather prediction and climate models, and the results will be used to validate/improve those models, in collaboration with the Met Office.

We can also use the microphysical information to develop an improved understanding of the mechanisms by which ice particles grow and evolve in clouds, and use this to constrain currently-unknown parameters such as the aggregation efficiency ('stickiness') of natural ice crystals.

Planned Impact

The primary non-academic beneficiaries of this project are:

The Met Office. Numerical weather prediction and climate models need to parameterise ice cloud microphysical processes in order to simulate rainfall and the globe's future climate. To do this accurately, a physically-based approach is needed. The results from this project will inform improvements to the Met Office's large scale cloud scheme, hence improving weather and climate prediction, and giving us greater confidence in those forecasts. This is important for government bodies, businesses and members of the public.

The European Centre for Medium-range Weather Forecasts (ECMWF). ECMWF have recently upgraded their cloud microphysics scheme to a more physically-based approach which is amenable to improvements based on the results from this project. Incorporation of the results from this project should lead ultimately to better medium-range forecasts of cloud and rainfall which are important for businesses, government organisations and members of the public.

The European Space Agency (ESA). ESA is currently building the satellite EarthCARE. Scheduled for launch in 2015, EarthCARE's aim is to advance our understanding of the role that clouds and aerosols play in our climate, and to use this information to improve climate predictions and weather forecasts. Our results will be used to improve the accuracy of the retrievals from the satellite.


10 25 50
Description We have found that aggregates snowflakes (many ice crystals stuck together) are fractal - this means the way the crystals stick together forms a pattern which is similar over a wide range of spatial scales (or when viewed at different magnifications). This has important implications for how we represent these snowflakes in weather forecast models, and also how we measure snowfall using radar.

We have also discovered that the formation of dendritic ice crystals near -15C can have an extremely dramatic impact on the rate of aggregation and formation of large snowflakes.
Exploitation Route We are only part way through the project, and there are still other tasks to do. We are working on exploiting the maximum information content of the Doppler spectra at various radar wavelengths which tells us how fast particles of a given size and shape fall. We are currently collaborating with the Met Office to apply our retrievals to clouds also being sampled by the FAAM aircraft to validate our methodology. Some of the work done in this project is being further developed in NERC-funded PICASSO project, which involves exploiting the multi-wavelength techniques developed here in tandem with state-of-the-art in-situ measurements from the FAAM aircraft. This powerful combination should help improve our understanding of the microphysics and scattering properties of snowflakes.
Sectors Environment