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Advances in Science and Research Contributions in Applied Meteorology and Climatology
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Volume 14
Adv. Sci. Res., 14, 163–173, 2017
https://doi.org/10.5194/asr-14-163-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Adv. Sci. Res., 14, 163–173, 2017
https://doi.org/10.5194/asr-14-163-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

  15 Jun 2017

15 Jun 2017

Evaluation of gridding procedures for air temperature over Southern Africa

Kai-Uwe Eiselt1,2, Frank Kaspar1, Thomas Mölg2, Stefan Krähenmann1, Rafael Posada1, and Jens O. Riede1 Kai-Uwe Eiselt et al.
  • 1Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany
  • 2Friedrich-Alexander Universität Erlangen-Nürnberg, Institute for Geography, Erlangen, Germany

Abstract. Africa is considered to be highly vulnerable to climate change, yet the availability of observational data and derived products is limited. As one element of the SASSCAL initiative (Southern African Science Service Centre for Climate Change and Adaptive Land Management), a cooperation of Angola, Botswana, Namibia, Zambia, South Africa and Germany, networks of automatic weather stations have been installed or improved (http://www.sasscalweathernet.org). The increased availability of meteorological observations improves the quality of gridded products for the region. Here we compare interpolation methods for monthly minimum and maximum temperatures which were calculated from hourly measurements. Due to a lack of longterm records we focused on data ranging from September 2014 to August 2016. The best interpolation results have been achieved combining multiple linear regression (elevation, a continentality index and latitude as predictors) with three dimensional inverse distance weighted interpolation.

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As one element of the SASSCAL initiative (a cooperation of Angola, Botswana, Namibia, Zambia, South Africa and Germany) networks of automatic weather stations have been installed or improved in Southern Africa. Here we compare interpolation methods for monthly minimum and maximum temperatures which were calculated from hourly measurements. The best interpolation results have been achieved combining multiple linear regression with three dimensional inverse distance weighted interpolation.
As one element of the SASSCAL initiative (a cooperation of Angola, Botswana, Namibia, Zambia,...
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