Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2017-558
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
29 Sep 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).
Evaluation of Multiple Climate Data Sources for Managing Environmental Resources in East Africa
Solomon H. Gebrechorkos1,2, Stephan Hülsmann1, and Christian Bernhofer2 1United Nations University Institute for Integrated Management of Material Fluxes and of Resources (UNU-FLORES), 01067 Dresden, Germany
2Faculty of Environmental Sciences, Institute of Hydrology and Meteorology, Technische Universität Dresden, 01062 Dresden, Germany
Abstract. Managing environmental resources under conditions of climate change and extreme climate events remains among the most challenging research tasks in the field of sustainable development. A particular challenge in many regions such as East Africa is often the lack of sufficiently long-term and spatially representative observed climate data. To overcome this data challenge we used a combination of accessible data sources based on station data, earth observation by remote sensing, and regional climate models. The accuracy of the Africa Rainfall Climatology version 2 (ARC2), Climate Hazards Group InfraRed Precipitation (CHIRP), CHIRP with Station data (CHIRPS), Observational-Reanalysis hybrid (ORH), and Regional Climate Models (RCMs) are evaluated against station data obtained from the respective national weather services and international databases. We did so by relating point to pixel, point to area grid cell average, and stations average to area grid cell average over 21 regions of East Africa: 17 in Ethiopia, two in Kenya and two in Tanzania. We found that the latter method provides better correlation and significantly reduces biases and errors. The correlations were analyzed at daily, dekadal (10 days), and monthly resolution for rainfall and maximum and minimum temperature (T-max and T-min) covering the period of 1983–2005. At daily time scale, CHIRPS, followed by ARC2 and CHIRP are the best performing rainfall products compared to ORH, RCM, and RCMS. CHIRPS captures well the daily rainfall characteristics such as rainfall intensity, amount of wet days, and total rainfall. Compared to CHIRPS, ARC2 showed higher underestimation of the total rainfall (−30 %) and daily intensity (−14 %). CHIRP on the other hand, showed higher underestimation of the daily intensity (−53 %) and duration of dry days (−29 %). Overall, the evaluation revealed that in terms of multiple statistical measures used on daily, dekadal, and monthly time scale, CHIRPS, CHIRP, and ARC2 are the best performing rainfall products while ORH, individual RCM, and RCMs are the least performing products. For T-max and T-min, ORH was identified as the most suitable product compared to RCM and RCMs. Our results indicate that CHIRPS (rainfall) and ORH (T-max and T-min), with higher spatial resolution, should be the preferential data sources to be used for climate change and hydrological studies in areas where station data are not accessible.

Citation: Gebrechorkos, S. H., Hülsmann, S., and Bernhofer, C.: Evaluation of Multiple Climate Data Sources for Managing Environmental Resources in East Africa, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-558, in review, 2017.
Solomon H. Gebrechorkos et al.
Solomon H. Gebrechorkos et al.
Solomon H. Gebrechorkos et al.

Viewed

Total article views: 286 (including HTML, PDF, and XML)

HTML PDF XML Total Supplement BibTeX EndNote
232 46 8 286 5 2 7

Views and downloads (calculated since 29 Sep 2017)

Cumulative views and downloads (calculated since 29 Sep 2017)

Viewed (geographical distribution)

Total article views: 286 (including HTML, PDF, and XML)

Thereof 283 with geography defined and 3 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 18 Oct 2017
Publications Copernicus
Download
Short summary
In Africa field-based meteorological data are scarce, therefore global data sources based on remote sensing and climate models are often used as alternative. To assess their suitability for a large and topographically complex area in East Africa, we evaluated multiple climate data products with available ground station data at multiple time scales over 21 regions. The comprehensive evaluation resulted in identification of preferential data sources to be used for climate and hydrological studies.
In Africa field-based meteorological data are scarce, therefore global data sources based on...
Share