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Ewan OConnor, Robin Hogan, Anthony Illingworth, Nicolas Gaussiat Liquid water path from microwave radiometers.

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Presentation on theme: "Ewan OConnor, Robin Hogan, Anthony Illingworth, Nicolas Gaussiat Liquid water path from microwave radiometers."— Presentation transcript:

1 Ewan OConnor, Robin Hogan, Anthony Illingworth, Nicolas Gaussiat Liquid water path from microwave radiometers

2 –Take radiative transfer model (RTM) Choose from Liebe, Rosenkranz etc. –Model atmospheric attenuation at surface LWP Retrieval Attenuation due to oxygen Attenuation due to water vapour: typical values Niamey – humid Chilbolton - dry

3 –Note that water vapour path varies from site to site. Shape of peak near 20 GHz varies with amount of saturation. –No liquid clouds yet! LWP Retrieval Attenuation due to oxygen Attenuation due to water vapour: fully saturated Niamey – humid Chilbolton - dry

4 –Add liquid water layer 1 km deep with LWC = 1 g m -3. –Attenuation depends on temperature (dielectric constant) LWP Retrieval 20 C 0 C Chilbolton – typical atmosphere, no cloud -20 C Note: dielectric constant not well known for supercooled liquid water!

5 Dual wavelength microwave radiometer –Brightness temperatures -> Liquid water path –Improved technique – Nicolas Gaussiat Use lidar to determine whether clear sky or not Adjust coefficients to account for instrument drift Removes offset for low LWP

6 Dual wavelength microwave radiometer –Brightness temperatures -> Liquid water path –Improved technique – Nicolas Gaussiat Use lidar to determine whether clear sky or not Adjust coefficients to account for instrument drift Removes offset for low LWP LWP - initial LWP - lidar corrected

7 Radiometrics MP1516A Water vapor profiler –21 frequencies from GHz Possible to determine profile of humidity –Half-power beamwidth degrees

8 Brightness temperatures

9 Interested in LWP Column integrated liquid water –Warm liquid layers usually have g m -2 –Supercooled layers may have as little as 10-20g m -2 This is close to the uncertainty in the radiative transfer models

10 Case: 6 October 2008

11 Case: 10 October 2008

12 Case: 5 October 2008

13 Conclusions Radiometrics algorithm misses low values –Any values close to or less than 0 set to 0 Assumed to be noise Can be caused by a slight offset Problematic for supercooled clouds Noise is useful check! –Can see how algorithm is performing –Spot drifts in Instrument Synoptic conditions –Can average to retrieve low LWP in certain situations


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