Publication | Open Access
A quantitative analysis of short‐term <sup>18</sup>O variability with a Rayleigh‐type isotope circulation model
126
Citations
37
References
2003
Year
EngineeringClimate ModelingOxygen IsotopeEarth System ScienceWater MassesEarth ScienceAtmospheric ScienceQuantitative AnalysisStable Water IsotopesHydroclimate ModelingHydroclimate SystemsClimate ChangeClimate VariabilityHydrometeorologyMeteorologyClimate SystemEarth's ClimateClimate DynamicsClimatologyIsotope GeochemistrySummer MonsoonGlobal ClimateGeochemistryClimate ModellingShort-term Variability
Stable water isotopes (D and 18 O) in precipitation have large spatial and temporal variability and are used widely to trace the global hydrologic cycle. The two models that have been used in the past to examine the variability of precipitation isotopes are Rayleigh‐type models and isotope‐atmospheric general circulation models. The causes of short‐term (1–10 day) variability in precipitation isotopes, however, remain unclear. This study seeks to explain isotope variability quantitatively at such scale. A new water isotope circulation model on a global scale that includes a Rayleigh equation and the use of external meteorological forcings is developed. Transport and mixing processes of water masses and isotopes that have been neglected in earlier Rayleigh models are included in the new model. A simulation of 18 O for 1998 is forced with data from the Global Energy and Water Cycle Experiment (GEWEX) Asian Monsoon Experiments (GAME) reanalysis. The results are validated by Global Network of Isotopes in Precipitation (GNIP) monthly observations with correlation R = 0.76 and a significance level >99% and by daily observations at three sites in Thailand with similar correlation and significance. A quantitative analysis of the results shows that among three factors that cause isotopic variability, the contribution of moisture flux is the largest, accounting for 37% at Chiangmai, and 46% globally. This highlights the importance of transport and mixing of air masses with different isotopic concentrations. A sensitivity analysis of the temporal and spatial resolution required for each variable is also made, and the model is applied to two additional data sets. The more accurate Global Precipitation Climatology Project (GPCP) precipitation data set yields improved model results at all three observation sites in Thailand. The National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis allows the simulation to cover 2 years, reproducing reasonable interannual isotopic variability.
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