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| Titel |
The Global Network of Isotopes in Precipitation after 55 years: assessing past, present and future developments |
| VerfasserIn |
Stefan Terzer, Luis Araguas-Araguas, Leonard I. Wassenaar, Pradeep K. Aggarwal |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250111162
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| Publikation (Nr.) |
 EGU/EGU2015-11248.pdf |
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| Zusammenfassung |
| The Global Network of Isotopes in Precipitation (GNIP) is a global observation programme
operated by the International Atomic Energy Agency (IAEA), in cooperation with the World
Meteorological Organization (WMO) and more than 100 contributing institutions worldwide.
GNIP has been the primary repository for baseline stable (δ18O, δ2H) and radioactive (3H)
isotope data since its foundation in 1960. The impetus for GNIP was the monitoring of
radioactive fallout from atmospheric thermonuclear testing and resulting tritium levels of
precipitation, but tritium together with stable isotopes was recognized as a key to
understanding hydrological processes. Later, new applications were developed focusing on
hydrometeorology and paleoclimatic research. Increasingly, GNIP data are being used
more widely in ecological and forensic investigations, e.g. for tracking of migratory
animals.
The GNIP database comprises more than 135,000 isotopic records (δ18O: 63,000; δ2H:
55,000; 3H: 63,000) of monthly composite precipitation samples from more than 1,000
stations worldwide. About 300 stations are currently active for stable isotopes and ca. 100 for
tritium. Data for most of the active stations is available up to 2013. Several national
isotopic observation networks (e.g. in Austria, Australia, China or the United States of
America) exist besides GNIP, complementing precipitation isotope data at national
levels.
The spatially and temporally discrete nature of the GNIP dataset induces coverage gaps.
Recently, highly-resolved gridded datasets were established to help overcome this deficiency
through geostatistical prediction models. These ‘isoscape’ (isotopic landscapes)
are based on combinations of multiple regression and interpolation methods, with
a range of parameterization available at regional and global levels. Attempts to
bridge the gap between ‘one-size-fits-all’ global parameterization and improved
predictions at regional and local levels led to the establishment of a regionalized
cluster-based water isotope prediction model (RCWIP) which uses fuzzy clustering to
delineate regions of climatic similarity, and to determine regionalized regression
models for each climatic cluster in order to lower prediction uncertainty of isotope
values.
Here, we present new data and figures on the spatial and temporal evolution of the GNIP
network, including station spatial density and coverage analysis. Moreover, we assess
outstanding deficits in the spatial coverage of the GNIP network by applying the clustering
structure of the RCWIP approach to identify those regions which would benefit most from an
improved GNIP sampling. Finally, we present an updated global meteoric water (GMWL)
line based on different calculation methods (ordinary least squares method, weighted least
squares, or based on weighted means). |
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