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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2019-303
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-303
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 08 Jul 2019

Submitted as: research article | 08 Jul 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Hydrology and Earth System Sciences (HESS).

Cross-validating precipitation datasets in the Indus River basin

Jean-Philippe Baudouin1, Michael Herzog1, and Cameron A. Petrie2 Jean-Philippe Baudouin et al.
  • 1Department of Geography, University of Cambridge
  • 2Department of Archaeology, University of Cambridge

Abstract. Large uncertainty remains about the amount of precipitation falling in the Indus River basin, particularly in the more mountainous northern part. While rain gauge measurements are often considered as a reference they are only punctual and subject to underestimation. Satellite observations and reanalysis output can improve our knowledge but validating their results is often difficult. In this study, we offer a cross-validation of 20 gridded datasets based on rain gauge, satellite and reanalysis, including the most recent and little studied APHRODITE-2, MERRA2, and ERA5. This original approach to cross-validation alternatively uses each dataset as a reference and interprets the result according to their dependency with the reference. Most interestingly, we found that reanalyses represent the daily variability as well as any observational datasets, particularly in winter. Therefore, we suggest that reanalyses offer better estimates than non-corrected rain gauge-based datasets where underestimation is problematic. Specifically, ERA5 has proven to be the most able reanalysis for representing the amounts of precipitation as well as its variability from daily to multi-annual scale. By contrast, satellite observations bring limited improvement at the basin scale. For the rain gauge-based datasets, APHRODITE has the finest representation of the precipitation variability, yet importantly it underestimates the actual amount. GPCC products are the only datasets that include a correction of the measurements but remain likely too small. These findings highlight the need for a systematic characterisation of the underestimation of rain gauge measurements.

Jean-Philippe Baudouin et al.
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Jean-Philippe Baudouin et al.
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Short summary
The amount of precipitation falling in the Indus River basin remains uncertain while its variability impacts 100 million inhabitants. A comparison of datasets from diverse sources (ground remote observations, model outputs) reduces significantly this uncertainty. Grounded observations offer the most reliable long term variability but with important underestimation in winter over the mountains. By contrast, recent model outputs offer better estimation of total amount and short-term variability.
The amount of precipitation falling in the Indus River basin remains uncertain while its...
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