References

ACP

Atmospheric Chemistry and Physics

ACP

1680-7324

Copernicus GmbH

Göttingen, Germany

10.5194/acp-7-5531-2007

A cloud filtering method for microwave upper tropospheric humidity measurements

Buehler

S. A.

¹ Kuvatov

² Sreerekha

T. R.

³ John

V. O.

⁴ Rydberg

⁵ Eriksson

⁵ Notholt

Lulea Technical University, Dept. of Space Science, Kiruna, Sweden

IUP, University of Bremen, Bremen, Germany

Satellite Applications, Met Office, Exeter, UK

RSMAS, University of Miami, USA

Dept. of Radio and Space Science, Chalmers University of Technology, Gothenburg, Sweden

05 11 2007

7 21 5531 5542

This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

This article is available from http://www.atmos-chem-phys.net/7/5531/2007/acp-7-5531-2007.html

The full text article is available as a PDF file from http://www.atmos-chem-phys.net/7/5531/2007/acp-7-5531-2007.pdf

The paper presents a cloud filtering method for upper tropospheric humidity (UTH) measurements at 183.31±1.00 GHz. The method uses two criteria: a viewing angle dependent threshold on the brightness temperature at 183.31±1.00 GHz, and a threshold on the brightness temperature difference between another channel and 183.31±1.00 GHz. Two different alternatives, using 183.31±3.00 GHz or 183.31±7.00 GHz as the other channel, are studied. The robustness of this cloud filtering method is demonstrated by a mid-latitudes winter case study. The paper then studies different biases on UTH climatologies. Clouds are associated with high humidity, therefore the possible dry bias introduced by cloud filtering is discussed and compared to the wet biases introduced by the clouds radiative effect if no filtering is done. This is done by means of a case study, and by means of a stochastic cloud database with representative statistics for midlatitude conditions. Both studied filter alternatives perform nearly equally well, but the alternative using 183.31±3.00 GHz as other channel is preferable, because that channel is less likely to see the Earth's surface than the one at 183.31±7.00 GHz. The consistent result of all case studies and for both filter alternatives is that both cloud wet bias and cloud filtering dry bias are modest for microwave data. The recommended strategy is to use the cloud filtered data as an estimate for the true all-sky UTH value, but retain the unfiltered data to have an estimate of the cloud induced uncertainty. The focus of the paper is on midlatitude data, since atmospheric data to test the filter for that case were readily available. The filter is expected to be applicable also to subtropical and tropical data, but should be further validated with case studies similar to the one presented here for those cases.

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