Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools
This study investigates different aspects of the Integrated Water Vapour (IWV) variability at 118 globally distributed Global Positioning System (GPS) sites, using additionally UV/VIS satellite retrievals by GOME, SCIAMACHY and GOME-2 (denoted as GOMESCIA below), and ERA-Interim reanalysis output at...
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ftcopernicus:oai:publications.copernicus.org:acpd72639 2023-05-15T17:35:08+02:00 Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools Malderen, Roeland Pottiaux, Eric Stankunavicius, Gintautas Beirle, Steffen Wagner, Thomas Brenot, Hugues Bruyninx, Carine 2018-11-21 application/pdf https://doi.org/10.5194/acp-2018-1170 https://www.atmos-chem-phys-discuss.net/acp-2018-1170/ eng eng doi:10.5194/acp-2018-1170 https://www.atmos-chem-phys-discuss.net/acp-2018-1170/ eISSN: 1680-7324 Text 2018 ftcopernicus https://doi.org/10.5194/acp-2018-1170 2019-12-24T09:49:39Z This study investigates different aspects of the Integrated Water Vapour (IWV) variability at 118 globally distributed Global Positioning System (GPS) sites, using additionally UV/VIS satellite retrievals by GOME, SCIAMACHY and GOME-2 (denoted as GOMESCIA below), and ERA-Interim reanalysis output at these site locations. Apart from some spatial representativeness issues at especially coastal and island sites, those three datasets correlate rather well, the lowest correlation found between GPS and GOMESCIA (0.865 on average). In this paper, we first study the geographical distribution of the frequency distributions of the IWV time series, and subsequently analyse the seasonal IWV cycle and linear trend differences among the three different datasets. Finally, both the seasonal behaviour and the long-term variability are fitted together by means of a stepwise multiple linear regression of the station’s time series, with a selection of regionally dependent candidate explanatory variables. Overall, the variables that are most frequently used and explain the largest fractions of the IWV variability are the surface temperature and precipitation. Also the surface pressure and tropopause pressure (in particular for higher latitude sites) are important contributors to the IWV time variability. All these variables also seem to account for the sign of long-term trend in the IWV time series to a large extent, when considered as explanatory variable. Furthermore, the multiple linear regression linked the IWV variability at some particular regions to teleconnection patterns or climate/oceanic indices like the North Oscillation index for West USA, the El Niňo Southern Oscillation (ENSO) for East Asia, the East Atlantic (associated with the North Atlantic Oscillation, NAO) index for Europe. Text North Atlantic North Atlantic oscillation Copernicus Publications: E-Journals |
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Open Polar |
collection |
Copernicus Publications: E-Journals |
op_collection_id |
ftcopernicus |
language |
English |
description |
This study investigates different aspects of the Integrated Water Vapour (IWV) variability at 118 globally distributed Global Positioning System (GPS) sites, using additionally UV/VIS satellite retrievals by GOME, SCIAMACHY and GOME-2 (denoted as GOMESCIA below), and ERA-Interim reanalysis output at these site locations. Apart from some spatial representativeness issues at especially coastal and island sites, those three datasets correlate rather well, the lowest correlation found between GPS and GOMESCIA (0.865 on average). In this paper, we first study the geographical distribution of the frequency distributions of the IWV time series, and subsequently analyse the seasonal IWV cycle and linear trend differences among the three different datasets. Finally, both the seasonal behaviour and the long-term variability are fitted together by means of a stepwise multiple linear regression of the station’s time series, with a selection of regionally dependent candidate explanatory variables. Overall, the variables that are most frequently used and explain the largest fractions of the IWV variability are the surface temperature and precipitation. Also the surface pressure and tropopause pressure (in particular for higher latitude sites) are important contributors to the IWV time variability. All these variables also seem to account for the sign of long-term trend in the IWV time series to a large extent, when considered as explanatory variable. Furthermore, the multiple linear regression linked the IWV variability at some particular regions to teleconnection patterns or climate/oceanic indices like the North Oscillation index for West USA, the El Niňo Southern Oscillation (ENSO) for East Asia, the East Atlantic (associated with the North Atlantic Oscillation, NAO) index for Europe. |
format |
Text |
author |
Malderen, Roeland Pottiaux, Eric Stankunavicius, Gintautas Beirle, Steffen Wagner, Thomas Brenot, Hugues Bruyninx, Carine |
spellingShingle |
Malderen, Roeland Pottiaux, Eric Stankunavicius, Gintautas Beirle, Steffen Wagner, Thomas Brenot, Hugues Bruyninx, Carine Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools |
author_facet |
Malderen, Roeland Pottiaux, Eric Stankunavicius, Gintautas Beirle, Steffen Wagner, Thomas Brenot, Hugues Bruyninx, Carine |
author_sort |
Malderen, Roeland |
title |
Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools |
title_short |
Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools |
title_full |
Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools |
title_fullStr |
Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools |
title_full_unstemmed |
Interpreting the time variability of world-wide GPS and GOME/SCIAMACHY integrated water vapour retrievals, using reanalyses as auxiliary tools |
title_sort |
interpreting the time variability of world-wide gps and gome/sciamachy integrated water vapour retrievals, using reanalyses as auxiliary tools |
publishDate |
2018 |
url |
https://doi.org/10.5194/acp-2018-1170 https://www.atmos-chem-phys-discuss.net/acp-2018-1170/ |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
eISSN: 1680-7324 |
op_relation |
doi:10.5194/acp-2018-1170 https://www.atmos-chem-phys-discuss.net/acp-2018-1170/ |
op_doi |
https://doi.org/10.5194/acp-2018-1170 |
_version_ |
1766134197500510208 |