GloFAS-ERA5 operational global river discharge reanalysis 1979–present

Abstract

Abstract. Estimating how much water is flowing through rivers at the global scale is challenging due to a lack of observations in space and time. A way forward is to optimally combine the global network of earth system observations with advanced numerical weather prediction (NWP) models to generate consistent spatio-temporal maps of land, ocean, and atmospheric variables of interest, which is known as a reanalysis. While the current generation of NWP models output runoff at each grid cell, they currently do not produce river discharge at catchment scales directly and thus have limited utility in hydrological applications such as flood and drought monitoring and forecasting. This is overcome in the Global Flood Awareness System (GloFAS; http://www.globalfloods.eu/, last access: 28 June 2020) by coupling surface and sub-surface runoff from the Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (HTESSEL) land surface model used within ECMWF's latest global atmospheric reanalysis (ERA5) with the LISFLOOD hydrological and channel routing model. The aim of this paper is to describe and evaluate the GloFAS-ERA5 global river discharge reanalysis dataset launched on 5 November 2019 (version 2.1 release). The river discharge reanalysis is a global gridded dataset with a horizontal resolution of 0.1∘ at a daily time step. An innovative feature is that it is produced in an operational environment so is available to users from 1 January 1979 until near real time (2 to 5 d behind real time). The reanalysis was evaluated against a global network of 1801 daily river discharge observation stations. Results found that the GloFAS-ERA5 reanalysis was skilful against a mean flow benchmark in 86 % of catchments according to the modified Kling–Gupta efficiency skill score, although the strength of skill varied considerably with location. The global median Pearson correlation coefficient was 0.61 with an interquartile range of 0.44 to 0.74. The long-term and operational nature of the GloFAS-ERA5 reanalysis dataset provides a valuable dataset to the user community for applications ranging from monitoring global flood and drought conditions to the identification of hydroclimatic variability and change and as raw input for post-processing and machine learning methods that can add further value. The dataset is openly available from the Copernicus Climate Change Service Climate Data Store: https://cds.climate.copernicus.eu/cdsapp#!/dataset/cems-glofas-historical?tab=overview (last access: 28 June 2020) with the following DOI: https://doi.org/10.24381/cds.a4fdd6b9 (C3S, 2019).

Characteristics of Propagation From Meteorological Drought to Hydrological Drought in the Pearl River Basin

“…Although station observations are regarded to be relatively reliable at the point where a meteorological station locates, the density of the meteorological station network is generally not high enough to fully describe the spatial distributions of meteorological variables (Shi et al., 2020). From the perspective of spatial coverage, grid‐based data sets (Harrigan, et al., 2020; Mishra, et al., 2011) can be considered as a viable substitute or supplement for station observations when conducting drought analysis. Therefore, the precipitation and runoff data provided by European Centre for Medium‐Range Weather Forecasts (ECMWF) are used in this study, which are from 1981 to 2019 with a spatial resolution of 0.1°.…”

ERA5-Land: A state-of-the-art global reanalysis dataset for land applications

“…This is the process used within the Global Flood Awareness System (GloFAS; https://www.globalfloods.eu/). More details can be found in Harrigan et al (2020). River discharge estimates from ERA5 (GloFAS-ERA5) and ERA5-Land (GloFAS-ERA5-Land) were obtained for the period January 2001 to December 2018.…”

Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System

“…CC BY 4.0 License. discharge reanalysis (Harrigan et al (2020) and Section 2.3), a product publicly available to users to 5 days behind real time through the CDS. To fill this 2 to 5-day gap between the latest available GloFAS-ERA5 data and real-time initialisation of the GloFAS forecast, the first 24 h period from the single ECMWF ENS CTL member from the preceding days forecast is used as 'fill up' (see Figure 2).…”

“…The GloFAS-ERA5 reanalysis dataset (Harrigan et al, 2020) provides a spatio-temporally consistent estimate of daily historic river discharge. It is produced for every 0.1° river cell globally from 1979 to the present.…”

“…this would contribute to poorer forecasts. An evaluation of GloFAS-ERA5 against a global network of 1801 in-situ river discharge observation stations is given inHarrigan et al (2020). They found the reanalysis is skilful in 86 % of catchments according to the modified Kling-Gupta Efficiency Skill Score against a mean flow benchmark.…”