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| Titel |
A layer-averaged relative humidity profile retrieval for microwave observations: design and results for the Megha-Tropiques payload |
| VerfasserIn |
R. G. Sivira, H. Brogniez, C. Mallet, Y. Oussar |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 8, no. 3 ; Nr. 8, no. 3 (2015-03-04), S.1055-1071 |
| Datensatznummer |
250116200
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| Publikation (Nr.) |
 copernicus.org/amt-8-1055-2015.pdf |
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| Zusammenfassung |
| A statistical method trained and optimized to retrieve seven-layer relative
humidity (RH) profiles is presented and evaluated with measurements from
radiosondes. The method makes use of the microwave payload of the
Megha-Tropiques platform, namely the SAPHIR sounder and the MADRAS imager.
The approach, based on a generalized additive model (GAM), embeds both the
physical and statistical characteristics of the inverse problem in the
training phase, and no explicit thermodynamical constraint – such as a
temperature profile or an integrated water vapor content – is provided to the
model at the stage of retrieval. The model is built for cloud-free conditions
in order to avoid the cases of scattering of the microwave radiation in the
18.7–183.31 GHz range covered by the payload. Two instrumental
configurations are tested: a SAPHIR-MADRAS scheme and a SAPHIR-only scheme
to deal with the stop of data acquisition of MADRAS in January 2013 for
technical reasons. A comparison to learning machine algorithms (artificial
neural network and support-vector machine) shows equivalent performance over
a large realistic set, promising low errors (biases < 2.2%RH) and
scatters (correlations > 0.8) throughout the troposphere (150–900 hPa). A
comparison to radiosonde measurements performed during the international
field experiment CINDY/DYNAMO/AMIE (winter 2011–2012) confirms these results
for the mid-tropospheric layers (correlations between 0.6 and 0.92), with an
expected degradation of the quality of the estimates at the surface and top
layers. Finally a rapid insight of the estimated large-scale RH field from
Megha-Tropiques is presented and compared to ERA-Interim. |
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