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Advances in Geosciences An open-access journal for refereed proceedings and special publications
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Volume 31
Adv. Geosci., 31, 57-65, 2012
https://doi.org/10.5194/adgeo-31-57-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Adv. Geosci., 31, 57-65, 2012
https://doi.org/10.5194/adgeo-31-57-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

  27 Jul 2012

27 Jul 2012

Assessment of data uncertainty and plausibility over the Nam Co Region, Tibet

S. Biskop1, P. Krause1, J. Helmschrot1,2, M. Fink1, and W.-A. Flügel1 S. Biskop et al.
  • 1Department for Geoinformatics, Hydrology and Modelling, Friedrich-Schiller-University, Jena, Germany
  • 2Department of Civil and Environmental Engineering, University of Washington, Seattle, USA

Abstract. One of the major challenges for water balance studies in the remote and mostly ungauged region of the Tibetan Plateau is the lack of suitable and reliable climate data to drive hydrological models. Ground observations are rare in the high-mountainous region of the Nam Co basin and only global and regional gridded climate products are available as model input data, but these data sets need to be carefully analysed if used as driving force for hydrological modelling. In this study, various global and regional gridded data products for temperature and precipitation were compared to assess spatio-temporal deviations between several data sets. For the comparison absolute and relative differences of annual and seasonal long-term means were calculated. Climatic trends were analysed by using the non-parametric Mann-Kendall trend test. In addition, gridded climate data sets were compared to meteorological observations in order to evaluate their plausibility. The comparative statistical analysis showed significant differences in the magnitude, the seasonality, the spatial pattern and the trend behaviour of the analysed climate variables, in particular for precipitation data. The identified inconsistencies underpin the necessity to quantify the uncertainty of such climate data. Moreover, the presented study highlights the importance of further research efforts to develop regional climate data sets with finer resolutions to reduce the model's uncertainty resulting from climate input data. Such higher resolution is needed for a sufficient representation of regional topographic and orographic effects in order to simulate important hydrological processes in mountainous areas like snow accumulation and melting.

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