Trends in the GloFAS-ERA5 river discharge reanalysis

Zsótér, E., Cloke, H. L. ORCID: https://orcid.org/0000-0002-1472-868X, Prudhomme, C., Harrigan, S., de Rosnay, P., Munoz-Sabater, J. and Stephens, E. ORCID: https://orcid.org/0000-0002-5439-7563, (2020) Trends in the GloFAS-ERA5 river discharge reanalysis. ECMWF Technical Memoranda. 871. Technical Report. ECMWF doi: 10.21957/p9jrh0xp

Abstract/Summary

The main objective of this study is to analyse the GloFAS-ERA5 river discharge reanalysis for any noticeable change (including gradual trends or discontinuities) in the annual mean time series across the 1979-2018 (40-year) period, and to evaluate how realistic these are compared with available observed river discharge time series. These variabilities are quantified by linear regression in order to highlight any concerning features in the GloFAS-ERA5 time series. This work is particularly important for GloFAS, as large trends, discontinuities or other similar features could have a major consequence on the GloFAS flood thresholds in around 50% of catchments, which are based on GloFAS-ERA5, and thus subsequently on the issuing of flood warnings. In addition, this study also contributes to the understanding of the water cycle variable behaviour in ERA5 (driver of GloFAS-ERA5) and ERA5-Land (higher resolution land reanalysis forced by ERA5, produced offline) by exploring the linear trends in river discharge and related hydrological variables. In exploring the stability of the time series in ERA5, we seek to trigger potential further discussions and research studies, which subsequently should help with the planning and development for the next generation ECMWF reanalysis, ERA6.

Item Type	Report (Technical Report)
URI	https://reading-clone.eprints-hosting.org/id/eprint/93047
Item Type	Report
Refereed	Yes
Divisions	Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	ECMWF
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