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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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doi:10.5194/amt-2016-304
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
19 Oct 2016
Review status
A revision of this discussion paper was accepted for the journal Atmospheric Measurement Techniques (AMT) and is expected to appear here in due course.
An intercalibrated dataset of Total Column Water Vapour and Wet Tropospheric Correction based on MWR on board ERS-1, ERS-2 and Envisat
Ralf Bennartz1,2, Heidrun Höschen3, Bruno Picard4, Marc Schröder3, Martin Stengel3, Oliver Sus3, Bojan Bojkov5,a, Stefano Casadio5, Hannnes Diedrich6, Salomon Eliasson7, Frank Fell8, Jürgen Fischer6, Rainer Hollmann3, Rene Preusker6, and Ulrika Willén7 1Earth & Env. Science Department, Vanderbilt University, Nashville, TN, USA
2Space Science and Engineering Center, University of Wisconsin- Madison, USA
3German Meteorological Service (DWD), Offenbach, Germany
4Collecte Localisation Satellite (CLS), Toulouse, France
5European Space Agency (ESA-ESRIN), Frascati, Italy
6Institute for Space Sciences, Freie Universität Berlin, Germany
7Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden
8Informus GmbH, Berlin, Germany
anow at: EUMETSAT, Darmstadt, Germany
Abstract. The Microwave Radiometers (MWR) on-board ERS-1, ERS-2, and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new Total Column Water Vapour (TCWV) and Wet Tropospheric Correction (WTC) dataset that builds on this time series. We use a one-dimensional variational approach to derive TCWV from MWR observations and ERA-Interim background information. A particular focus of this study lies on the intercalibration of the three different instruments, which is performed using constraints on liquid water path (LWP) and TCWV. Comparing our MWR-derived time series of TCWV against TCWV derived from Global Navigation Satellite System (GNSS) we find that the MWR-derived TCWV time series is stable over time. However, observations potentially affected by precipitation show a degraded performance compared to precipitation-free observations in terms of the accuracy of retrieved TCWV. An analysis of WTC shows further that the retrieved WTC is superior to purely model-derived WTC for all satellites and for the entire time series. Even compared to operational WTC retrievals, which incorporate additional observational data, the here-described dataset shows improvements in particular for the mid-latitudes and for the two earlier satellites ERS-1 and ERS-2. The dataset is publicly available under doi:10.5676/DWD_EMIR/V001.

Citation: Bennartz, R., Höschen, H., Picard, B., Schröder, M., Stengel, M., Sus, O., Bojkov, B., Casadio, S., Diedrich, H., Eliasson, S., Fell, F., Fischer, J., Hollmann, R., Preusker, R., and Willén, U.: An intercalibrated dataset of Total Column Water Vapour and Wet Tropospheric Correction based on MWR on board ERS-1, ERS-2 and Envisat, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-304, in review, 2016.
Ralf Bennartz et al.
Ralf Bennartz et al.

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The Microwave Radiometers (MWR) on-board ERS-1, ERS-2, and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new Total Column Water Vapour (TCWV) and Wet Tropospheric Correction (WTC) dataset that builds on this time series.The dataset is publicly available under doi:10.5676/DWD_EMIR/V001.
The Microwave Radiometers (MWR) on-board ERS-1, ERS-2, and Envisat provide a continuous time...
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