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Identification of atmospheric and oceanic teleconnection patterns in a 20-year global data set of the atmospheric water vapor column measured from satellites in the red spectral range

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Wagner,  Thomas
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

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Beirle,  Steffen
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

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Dörner,  Steffen
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

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Borger,  Christian
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

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Citation

Wagner, T., Beirle, S., Dörner, S., Borger, C., & Van Malderen, R. (2020). Identification of atmospheric and oceanic teleconnection patterns in a 20-year global data set of the atmospheric water vapor column measured from satellites in the red spectral range. Atmospheric Chemistry and Physics Discussions, 20. doi:10.5194/acp-2020-565.


Cite as: http://hdl.handle.net/21.11116/0000-0007-9718-4
Abstract
We used a global long-term (1995–2015) data set of total column water vapor (TCVW) derived from satellite observations to quantify the influence of teleconnections. To our knowledge, such a comprehensive global TCWV data set was rarely used for teleconnection studies. One important property of the TCWV data set is that it is purely based on observational data. We developed a new empirical method to decide whether a teleconnection index is significantly detected in the global data set. Based on this method more than 40 teleconnection indices were significantly detected in the global TCWV data set derived from satellite observations. In addition to the satellite data we also investigated the influence of teleconnection indices on other global data sets derived from ECMWF reanalysis (ERA). One important finding is that the results obtained for the ERA TCWV data are very similar to the observational TCWV data set indicating a high consistency between the satellite and ERA data. Moreover, similar results are also found for two selections of ERA data (either all data or mainly clear sky data). This finding indicates that the clear-sky bias of the satellite data set is negligible for the results of this study. For most "traditional" teleconnection data sets (surface temperature, surface pressure, geopotential heights and meridional winds at different altitudes) a smaller number of significant teleconnection indices was found than for the TCWV data sets, while for zonal winds at different altitudes, the number of significant teleconnection indices (up to > 50) was higher. In all global data sets, no "other indices" (solar variability, stratospheric AOD or hurricane frequency) were significantly detected. Since many teleconnection indices are strongly correlated, we also applied our method to a set of orthogonalised indices. The number of significantly detected orthogonalised indices (20) was found to be much smaller than for the original indices (42). Based on the orthogonalised indices we derived the global distribution of the cumulative influence of teleconnection indices. The strongest influence on the TCWV is found in the tropics and high latitudes.