Details of Award
NERC Reference : NE/T00147X/1
IMPROVING CIRRUS ESTIMATES OF RADIATIVE FORCING: BACKSCATTERING FOR MODELS AND OBSERVATIONS (ICE-RF)
Grant Award
- Principal Investigator:
- Professor AR Webb, The University of Manchester, Earth Atmospheric and Env Sciences
- Co-Investigator:
- Professor ZJ Ulanowski, University of Hertfordshire, School of Physics, Astronomy and Maths
- Co-Investigator:
- Dr E Hesse, University of Hertfordshire, School of Physics, Eng & Computer Scienc
- Co-Investigator:
- Dr A Baran, University of Hertfordshire, School of Physics, Astronomy and Maths
- Co-Investigator:
- Dr KN Bower, The University of Manchester, Earth Atmospheric and Env Sciences
- Co-Investigator:
- Professor PJ Connolly, The University of Manchester, Earth Atmospheric and Env Sciences
- Co-Investigator:
- Dr JR Dorsey, The University of Manchester, Earth Atmospheric and Env Sciences
- Grant held at:
- The University of Manchester, Earth Atmospheric and Env Sciences
- Science Area:
- Atmospheric
- Overall Classification:
- Panel B
- ENRIs:
- Global Change
- Science Topics:
- Radiative Processes & Effects
- Climate & Climate Change
- Remote Sensing & Earth Obs.
- Abstract:
- One of the big uncertainties in both weather forecasting and prediction of future climate change is cloud. In both cases the models that estimate the future weather and climate must represent cloud in a simplified way. If we can improve the way that clouds are represented in the models, then we can improve the model outputs. Cirrus are the high, often thin and wispy-looking clouds, consisting entirely of ice particles. Their influence on weather and climate change is very hard to determine because of the different ways they interact with radiation. They reflect solar radiation (a cooling effect) but also absorb and re-radiate longwave radiation from the Earth (resulting in a warming effect). Improving the way that cirrus are represented in models will bring advances in both weather forecasting and climate change prediction. This project aims to both develop and test a new scheme for representing cirrus that will be used in the Met Office UKV forecast model and in the Met Office Earth System Model used for climate change prediction. One of the problems with understanding cirrus is the difficulty in knowing the microphysical form of the cloud - that is the size, shape and roughness of the ice particles in the cloud - the properties that determine how the cloud interacts with radiation. Research aircraft can fly through the cloud and sample the ice particles, but that is not a practical method for widespread use or routine monitoring. Alternatively the clouds can be systematically interrogated from below by ground-based lidar, or from above by satellite. Both systems rely on radiation back-scattered from the ice particles, using two wavelengths, one strongly and one weakly absorbed by ice particles. However, to make sense of the lidar data we need to know how different habits (sizes and shapes) of ice crystal backscatter radiation at the lidar wavelengths. This can be determined using the Manchester Ice Cloud Chamber (MICC). Ice clouds of different habits can be made and characterized in the MICC. As the ice particles fall they pass through a scattering chamber. We will shine lasers into the scattering chamber, at paired lidar wavelengths (for ground-based or satellite systems), and measure the exact backscatter from the different ice clouds, as well as polarization and scattering in other directions. The two wavelengths of a pair interact with the particles in different ways, depending on their size, shape and roughness, so we can determine a colour ratio (the ratio of the two backscattered signals) that tells us something about the ice particles in the cloud. Having developed a catalogue of laboratory ice cloud colour ratios and scattering functions we will model these known conditions using the discrete dipole approximation method to ensure that this method can reproduce the laboratory results, and provide for a parameterisation of colour ratio according to particle size distribution (PSD). Further colour ratios will be modeled and parameterised for ice clouds with PSDs that we have not reproduced in the MICC, but are possible in nature. Now, if we take the colour ratio measured from real cirrus by satellite lidars we can use our parameterisation of the backscatter signal to obtain the mean mass weighted ice crystal size (Dmmw). The ice microphysics scheme in the UKV model also predicts the Dmmw, thus we can directly validate the UKV microphysics scheme by comparing the predicted and actual Dmmw for cirrus. The same microphysics scheme is part of the Met Office Earth System Model used for climate change prediction, so its improvement also increases confidence in estimates of future climate change that inform Government policy. The backscatter parameterisations will be made across a range of wavelengths that can be applied to ground-based, current and future satellite missions, to tell us whether particular cirrus are having a net warming or cooling effect on the atmosphere.
- NERC Reference:
- NE/T00147X/1
- Grant Stage:
- Awaiting Completion
- Scheme:
- Standard Grant FEC
- Grant Status:
- Active
- Programme:
- Standard Grant
This grant award has a total value of £625,938
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Equipment | DI - Staff | DA - Other Directly Allocated | DI - T&S |
|---|---|---|---|---|---|---|---|
| £45,326 | £206,654 | £103,593 | £60,480 | £8,239 | £160,883 | £31,453 | £9,309 |
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