1 / 10

Liquid Water Path from radiometers and lidar.

Liquid Water Path from radiometers and lidar. Nicolas Gaussiat, Anthony Illingworth and Robin Hogan. Beeskow, 12 Oct 2005. Radiometers measure brightness temperatures. T b , that are converted into optical depths,  . Optical depths are linearly related LWP and VWP :

sheena
Download Presentation

Liquid Water Path from radiometers and lidar.

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Liquid Water Path from radiometers and lidar. Nicolas Gaussiat, Anthony Illingworth and Robin Hogan Beeskow, 12 Oct 2005

  2. Radiometers measure brightness temperatures. Tb, that are converted into optical depths, . Optical depths are linearly related LWP and VWP : kl and kv are path averaged coefficients. d is the ‘dry’ optical depth Two frequencies, two equations, two unknowns – find LWP and VWP. PROBLEM: Calibration errors, uncertainty over ‘k’ coefficients Cause errors in lwp – it can even go negative.

  3. In clear sky conditions non-zero values of LWP are retrieved. Some values negative. SOLUTION: Add a calibration error, ‘C’ to the  equations. When lidar identifies no water cloud, set LWP = 0, use this to constrain ‘C.

  4. Assuming calibrations errors : Principe of the lidar+radiometer technique: In clear sky conditions LWP = 0: Radiometers have same perf : Radiometers have different perf : where s22 and s28 are the expected standard deviations of respectively C22 and C28.

  5. Example :‘C’ factors reset each time no water cloud.LWP forcedto zero whenno water cloud.

  6. Another Another example:

  7. Sensitivity to drift in T:old technique Add 5K to Tb (28GHz)  and then to Tb(22GHz)  LWP OFFSET +200 g m-2 - 60g m-2

  8. Robustness of the new technique : One month’s data: apply 1 to 5K offsets. 5 5 NEW METHOD: Tb error 5K: introduces only 2% error in LWP 1 1 (a) old technique (b) new method

  9. LWP error as function of time between clear sky events Error about 5-10 g m-2 10hr 1hr 6min

  10. Comparison of three methods old remove mean lwp new before and after cloud

More Related