A multi-instrument comparison of integrated water vapour measurements at a high latitude site

We compare measurements of integrated water vapour (IWV) over a subarctic site (Kiruna, Northern Sweden) from five different sensors and retrieval methods: Radiosondes, Global Positioning System (GPS), ground-based Fourier-transform infrared (FTIR) spectrometer, ground-based microwave radiometer, an...

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Bibliographic Details
Published in:Atmospheric Chemistry and Physics
Main Authors: S. A. Buehler, S. Östman, C. Melsheimer, G. Holl, S. Eliasson, V. O. John, T. Blumenstock, F. Hase, G. Elgered, U. Raffalski, T. Nasuno, M. Satoh, M. Milz, J. Mendrok
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2012
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Online Access:https://doi.org/10.5194/acp-12-10925-2012
https://doaj.org/article/9993995cc13a43c3a117dfa982f73eae
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Summary:We compare measurements of integrated water vapour (IWV) over a subarctic site (Kiruna, Northern Sweden) from five different sensors and retrieval methods: Radiosondes, Global Positioning System (GPS), ground-based Fourier-transform infrared (FTIR) spectrometer, ground-based microwave radiometer, and satellite-based microwave radiometer (AMSU-B). Additionally, we compare also to ERA-Interim model reanalysis data. GPS-based IWV data have the highest temporal coverage and resolution and are chosen as reference data set. All datasets agree reasonably well, but the ground-based microwave instrument only if the data are cloud-filtered. We also address two issues that are general for such intercomparison studies, the impact of different lower altitude limits for the IWV integration, and the impact of representativeness error. We develop methods for correcting for the former, and estimating the random error contribution of the latter. A literature survey reveals that reported systematic differences between different techniques are study-dependent and show no overall consistent pattern. Further improving the absolute accuracy of IWV measurements and providing climate-quality time series therefore remain challenging problems.