DOI: 10.5281/zenodo.3702351
title: ENS-LARSIM_ME Monthly Streamflow Forecasts for German Waterways

description: The datasets provided here were produced as part of the IMPREX project for work package 4, task 1 “<em>Development of the regional and European scale reforecast dataset of hydrological extremes</em>“ and work package 9, task 3 “<em>Case studies</em>”. Analysis of the datasets are published in Deliverable 9.4 “<em>Semi-operational forecasting system for Rhine, Danube and Elbe to support improved transport cost planning</em>“ (Klein & Meißner 2019). The aim was to evaluate the potential skill of monthly streamflow forecasting for the German waterways Rhine, Elbe and Danube. As meteorological forcing data to calculate monthly flow forecasts the extended-range forecasts from ECMWF-ENS are applied. Twice a week (Monday and Thursday), the ENS model is extended to a lead time up to 46 days by ECMWF. The horizontal resolution for the first 15 days is 0.2°x0.2° (approx. 18 km) and from day 15 to day 46 it is 0.4°x0.4° (approx. 36 km). The ensemble consists of 1 control forecasts and 50 perturbed members, made from slightly different initial atmospheric and oceanic conditions (Owens & Hewson 2018). Re-Forecasts are generated with the same model as used for the operational forecasts for the past 20 years, starting on the same day and month as each real time forecast. The ensemble size is 11-member, which means that in total 20 years x 11 members = 220 forecasts are available for each real time forecast date. The re-forecasts are also created twice a week (Mondays and Thursdays) and are available a week in advance. The hydrological model applied is called LARSIM-ME (ME – MittelEuropa = Central Europe) and is based in the model software LARSIM (Large Area Runoff SImulation Model) originally developed by Ludwig & Bremicker (2006). LARSIM-ME covers the catchments of the rivers Rhine, Elbe, Weser/Ems, Odra and Upper Danube. The total catchment size simulated by the model is approximately 800,000 km². The spatial resolution is 5 km x 5 km and the computational time-step is daily. For more details about the model see Meißner et al. (2017). Real-time meteorological station data (precipitation, temperature and global radiation) was interpolated to the 5 km x 5 km model grid and used as meteorological forcing to initialize LARSIM-ME at the forecast date. Re-forecasts for the hindcast dates 10th March 2016 – 09th March 2017 generating re-forecasts of the last 20 years were used. As station density of real-time meteorological station data is limited before 2000, only reforecasts with a forecast date after 1999 were considered. Daily total precipitation, daily mean air temperature and global radiation of the reforecast dataset of ECMWF-ENS were interpolated to the 5kmx5km model grid and used as forcing to create the streamflow re-forecast dataset with LARSIM-ME. <strong>Dataset Q_OBS.nc:</strong> Mean daily observed flow of the gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe for the period 1951–2017 stored as variable <strong>q_obs(time=24472, stations=8)</strong>. Data originate from the database of gauge measurements of the Federal Waterways and Shipping Administration (WSV). These data were quality checked and published by the gauge-operating WSV offices. Nevertheless, data errors and inconsistencies cannot be ruled out completely, so that neither the WSV nor the BfG do accept any liability for the correctness and completeness of the data. Data source: "German Federal Waterways and Shipping Administration (WSV)", provided by the German Federal Institute of Hydrology (BfG). https://zenodo.org/record/3696446 <strong>Dataset Q_SYNOP_LME.nc:</strong> Mean daily simulated flow of the hydrological model LARSIM-ME forced by observed meteorology from real-time meteorological station data stored as variable float <em><strong>q_sim(time=6210, stations=8)</strong></em>. Period 2000-2016, Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe. <pre><code>float q_sim(time=6210, stations=8); :units = "m3/s"; :_FillValue = -9999.0f; // float :long_name = "simulated streamflow"; :coordinates = "lat lon";</code></pre> <strong>Dataset Q_ENS_LME.nc:</strong> Mean daily forecasted flow of the hydrological model LARSIM-ME forced by air temperature, precipitation and global radiation of the ECMWF ENS re-forecasts for the hindcast dates 10th March 2016 – 09th March 2017 with a lead time of 46 days. Forecast dates 2nd January 2000 to 9th March 2016, in total 1699 forecasts. Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe. Forecast values are stored in the variable <em><strong>q_fcast_ens(time=1699, lead_time=46, realization=11, stations=8)</strong></em>, first dimension forecast dates, second dimension lead time, third dimension realization, fourth dimension station. <pre><code>float q_fcast_ens(time=1699, lead_time=46, realization=11, stations=8); :_FillValue = -9999.0f; // float :long_name = "forecast streamflow ensemble"; :units = "m3/s"; :coordinates = "lat lon";</code></pre> <strong>Literature</strong> Klein, B. & D. Meissner (2019): Semi-operational forecasting system for Rhine, Danube and Elbe to support improved transport cost planning. Deliverable 9.4, IMPREX - Improving Predictions of Hydrological Extremes - Grant Agreement Number 641811, https://imprex.eu/system/files/generated/files/resource/deliverable9-4-imprex-v1-0.pdf Ludwig, K. & M. Bremicker (2006): The Water Balance Model LARSIM –Design, Content and Applications. 22. C. Leibundgut, S. Demuth and J. Lange (Eds), Freiburger Schriften zur Hydrologie, Institut für Hydrologie, Universität Freiburg im Breisgau, Freiburg, 141 pp. Meißner, D., B. Klein & M. Ionita (2017): Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe. Hydrol. Earth Syst. Sci. 21(12), 6401 Owens, R. & T. R. E. Hewson (2018): ECMWF Forecast User Guide. ECMWF, Reading, doi: 10.21957/m1cs7h
description: {"references": ["Klein, B. & D. Meissner (2019): Semi-operational forecasting system for Rhine, Danube and Elbe to support improved transport cost planning. Deliverable 9.4, IMPREX - Improving Predictions of Hydrological Extremes - Grant Agreement Number 641811, https://imprex.eu/system/files/generated/files/resource/deliverable9-4-imprex-v1-0.pdf"]}