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https://doi.org/10.5194/hess-2020-517
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-517
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  28 Oct 2020

28 Oct 2020

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This preprint is currently under review for the journal HESS.

Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies

Mostafa Tarek1,2, François Brissette1, and Richard Arsenault1 Mostafa Tarek et al.
  • 1Hydrology, Climate and Climate Change Laboratory, École de technologie supérieure, 1100 Notre-Dame West, Montreal, Quebec, Canada, H3C 1K3
  • 2Department of Civil Engineering, Military Technical College, Egypt

Abstract. Climate change impact studies require a reference climatological dataset providing a baseline period to assess future changes and post-process climate model biases. High-resolution gridded precipitation and temperature datasets interpolated from weather stations are available in regions of high-density networks of weather stations, as is the case in most parts of Europe and the United States. In many of the world’s regions, however, the low density of observational networks renders gauge-based datasets highly uncertain. Satellite, reanalysis and merged products dataset have been used to overcome this deficiency. However, it is not known how much uncertainty the choice of a reference dataset may bring to impact studies. To tackle this issue, this study compares nine precipitation and two temperature datasets over 1145 African catchments to evaluate the dataset uncertainty contribution to the results of climate change studies. These datasets all cover a common 30-year period needed to define the reference period climate. The precipitation datasets include two gauged-only products (GPCC, CPC Unified), two satellite products (CHIRPS and PERSIANN-CDR) corrected using ground-based observations, four reanalysis products (JRA55, NCEP-CFSR, ERA-I, and ERA5) and one gauged, satellite, and reanalysis merged product (MSWEP). The temperature datasets include one gauged-only (CPC Unified) product and one reanalysis (ERA5) product.

All combinations of these precipitation and temperature datasets were used to assess changes in future streamflows. To assess dataset uncertainty against that of other sources of uncertainty, the climate change impact study used a top-down hydroclimatic modeling chain using 10 CMIP5 GCMs under RCP8.5 and two lumped hydrological models (HMETS and GR4J) to generate future streamflows over the 2071–2100 period. Variance decomposition was performed to compare how much the different uncertainty sources contribute to actual uncertainty.

Results show that all precipitation and temperature datasets provide good streamflow simulations over the reference period, but 4 precipitation datasets outperformed the others for most catchments: they are, in order: MSWEP, CHIRPS, PERSIANN, and ERA5. For the present study, the 2-member ensemble of temperature datasets provided negligible levels of uncertainty. However, the ensemble of nine precipitation datasets provided uncertainty that was equal to or larger than that related to GCMs for most of the streamflow metrics and over most of the catchments. A selection of the best 4 performing reference datasets (credibility ensemble) significantly reduced the uncertainty attributed to precipitation for most metrics, but still remained the main source of uncertainty for some streamflow metrics. The choice of a reference dataset can therefore be critical to climate change impact studies as apparently small differences between datasets over a common reference period can propagate to generate large amounts of uncertainty in future climate streamflows.

Mostafa Tarek et al.

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Mostafa Tarek et al.

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Short summary
It is not known how much uncertainty the choice of a reference dataset may bring to impact studies. This study compares nine precipitation and two temperature datasets to evaluate the dataset uncertainty contribution to the results of climate change studies. Results show that all datasets provide good streamflow simulations over the reference period. The reference datasets also provided uncertainty that was equal to or larger than that related to GCMs over most of the catchments.
It is not known how much uncertainty the choice of a reference dataset may bring to impact...
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