1 Dataset description

In ocean model or Earth System model applications, the riverine freshwater inflow is an important flux affecting salinity and marine stratification in coastal areas. However, in climate change studies, the river runoff based on climate model output often has large biases on local, regional or even basin wide scales. If these biases are too large, the ocean model forced by the runoff will drift into a different climate state compared to the observed state, which is especially relevant for semi-enclosed seas like the Baltic Sea. In order to fulfil the demands for low biases in river runoff, a three-part bias correction was developed by Hagemann et al. (in prep.) that comprises different correction factors for low, medium and high percentile ranges of river runoff over Europe. First, we utilized the global hydrology model HydroPy (Stacke and Hagemann 2021) and the Hydrological Discharge (HD) model (Hagemann et al. 2020) to simulate daily discharge time series over the European domain at 1/12° horizontal resolution Sect. 1.1) from 1901-2019. Then, we bias-corrected these time series as described in Sect. 1.2 to generate bias-corrected discharges at coastal ocean boxes of the European HD model domain from 1901-2019.

1.1 Century-long high-resolution discharge simulation over Europe

Analogous to Hagemann and Stacke (2022), the global hydrology model HydroPy (Vs. 1.0.2 Stacke and Hagemann 2021) and the Hydrological Discharge (HD) model (Vs. 5.2.0, Hagemann et al. 2023) were used to simulate daily discharge time series over the European domain at 1/12° horizontal resolution. Daily data of two atmospheric datasets were utilized to force HydroPy that provided the input to the HD model. The Global Soil Wetness Project Phase 3 (GWSP3; Dirmeyer et al. 2006; Kim 2017) dataset is available at 0.5° resolution from 1901-2014. Here, we used the data from 1901-1978, and then the simulated time series were continued by using the WFDE5 dataset (Cucchi et al. 2020; 0.5° resolution) from 1979-2019.

1.2 Generation of bias corrected HD discharge data

In order to apply the bias correction of Hagemann et al. (in prep.) to the simulated time series of daily discharge from 1901-2019, two sets of bias correction factors were derived. The first set uses the WFDE5-based discharges and discharge station observations for the period 1979-2014. This set was used to bias-correct the simulated discharge at HD river mouths from 1979-2019. The second set uses a further discharge simulation where we continued the GSWP3-based simulation with GSWP3 forcing until 2014. Again, the set of bias-correction factors was derived for the period 1979-2014 using discharge station observations. Then, this set was applied to bias-correct the simulated discharge at HD river mouths from 1901-1978.

Detailed information you can find in the specified sections of the attached PDF ( https://www.wdc-climate.de/ui/entry?acronym=Biasc_hr_riverro_Eu_AdI_v1_ 1).

Recently, a bug has been discovered in the part of the bias correction procedure, which transfers the bias correction factors from the station locations to the river mouths. Here, accidentally the bias correction factors from a previous simulation, which had utilized GSWP3 data, HydroPy and the HD model, were transferred to the river mouths for the whole considered period from 1901-2019. It can be noted that these factors still have improved the simulated inflows for most of the basins compared to the uncorrected HD model discharges. However, fixing this bug has led to general improvement for most of the basins. Fig. 1 in the attached PDF ( https://www.wdc-climate.de/ui/entry?acronym=Biasc_hr_riverro_Eu_AdI_v1_ 1) provides an example for the major Baltic Sea sub-basins and shows the inflow biases compared to HELCOM observational estimates.

Note that the other datasets of Version 1.0 ( https://doi.org/10.26050/WDCC/Biasc_hr_riverro_Eu ) did not change.