Diagnostic evaluation of river discharge into the Arctic Ocean and its impact on oceanic volume transports

This study analyses river discharge into the Arctic Ocean using state-of-the-art reanalyses such as the fifth-generation European Reanalysis (ERA5) and the reanalysis component from the Global Flood Awareness System (GloFAS). GloFAS, in its operational version 2.1, combines the land surface model (H...

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Bibliographic Details
Published in:Hydrology and Earth System Sciences
Main Authors: S. Winkelbauer, M. Mayer, V. Seitner, E. Zsoter, H. Zuo, L. Haimberger
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
Subjects:
geo
Online Access:https://doi.org/10.5194/hess-26-279-2022
https://hess.copernicus.org/articles/26/279/2022/hess-26-279-2022.pdf
https://doaj.org/article/70b593a9fd18492d9284432d2f2c7e86
Description
Summary:This study analyses river discharge into the Arctic Ocean using state-of-the-art reanalyses such as the fifth-generation European Reanalysis (ERA5) and the reanalysis component from the Global Flood Awareness System (GloFAS). GloFAS, in its operational version 2.1, combines the land surface model (Hydrology Tiled European Centre for Medium-Range Weather Forecasts – ECMWF – Scheme for Surface Exchanges over Land, HTESSEL) from ECMWF’s ERA5 with a hydrological and channel routing model (LISFLOOD). Furthermore, we analyse GloFAS' most recent version 3.1, which is not coupled to HTESSEL but uses the full configuration of LISFLOOD. Seasonal cycles as well as annual runoff trends are analysed for the major Arctic watersheds – Yenisei, Ob, Lena, and Mackenzie – where reanalysis-based runoff can be compared to available observed river discharge records. Furthermore, we calculate river discharge over the whole pan-Arctic region and, by combination with atmospheric inputs, storage changes from the Gravity Recovery and Climate Experiment (GRACE) and oceanic volume transports from ocean reanalyses, we assess closure of the non-steric water volume budget. Finally, we provide best estimates for every budget equation term using a variational adjustment scheme. Runoff from ERA5 and GloFAS v2.1 features pronounced declining trends induced by two temporal inhomogeneities in ERA5's data assimilation system, and seasonal river discharge peaks are underestimated by up to 50 % compared to observations. The new GloFAS v3.1 product exhibits distinct improvements and performs best in terms of seasonality and long-term means; however, in contrast to gauge observations, it also features declining runoff trends. Calculating runoff indirectly through the divergence of moisture flux is the only reanalysis-based estimate that is able to reproduce the river discharge increases measured by gauge observations (pan-Arctic increase of 2 % per decade). In addition, we examine Greenlandic discharge, which contributes about 10 % of the total ...