A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 1995 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades without tagging until 1984 and, then, from 1985 to 1994 with tagging (see below). The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html IOW: Leibniz Institute for Baltic Sea Research Warnemünde) and from the HELCOM database which, now, is part of the ICES Oceanography Data Portal (https://www.ices.dk/data/data-portals/Pages/ocean.aspx; HELCOM: Helsinki Commissionm; ICES: International Council for the Exploration of the Seas). The model simulation was forced by coastDat2 COSMO-CLM data (doi:10.1594/WDCC/coastDat-2_COSMO-CLM). Riverine phosphorus input of the Warnow River was calculated with the Soil & Water Assessment Tool (SWAT; Bauwe et al., 2019, doi:10.1016/j.ecohyd.2019.03.003). Phosphorus from the Warnow River has been tagged in the model simulation according to a method by Menésguen et al. (2006, doi:10.4319/lo.2006.51.1_part_2.0591). Therefore, all phosphorus-containing model variables exist twice in the output: once as regular variables and once as tagged variable.
The default phosphorus input by the Warnow River based on real phosphorus release patterns and real atmospheric conditions was used ("base scenario"; PhosWaM SWAT case "ist"). The turnover of phosphorus compounds in the Unterwarnow was calculated based on the "Unterwarnow turnover estimation v04" (see final project report of PhosWaM for details).
The simulation was performed at the North-German Supercomputing Alliance (HLRN). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
Technical details:
model run on MPP1 Cluster of the HLRN-III Konrad Comlpex
each simulation performed on 527 cores distributed on 22 nodes (24 cores per node; one core on one node not used) configuration of one node:
Processor: 2x Intel Xeon E5-2695v2 CPUs (12 cores per CPU), R_peak: 230 GFlop/s
RAM: 64 GiB DDR3-1866
OS: SuSE Linux Enterprise Server (SLES) version 11
Interconnect: Cray Aries
Neumann, Daniel; Bauwe, Andreas; Radtke, Hagen; Neumann, Thomas (2019). MOM-ERGOM western Baltic Sea simulations with tagging of phosphorus inputs of the Warnow River, base scenario, v04 Unterwarnow turnover. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/MOMERGOMBSWRU_3873381
There are not gaps in the spatial and temporal coverage. Land grid cells are indicated by missing values (-1.e+20f).
...
Description
There are not gaps in the spatial and temporal coverage. Land grid cells are indicated by missing values (-1.e+20f).
All prognostic biogeochemical model variables and a few relevant physical model variables are provided. Each phosphorus-containing prognostic variable has a counterpart with the suffix "_warnow_P" indicating phosphorus from Warnow River input in this variable.
Consistency report
In the used ERGOM version, the biogeochemical system is represented by 31 state variables of which 26 are in the water column and 5 in the surface sed...
Description
In the used ERGOM version, the biogeochemical system is represented by 31 state variables of which 26 are in the water column and 5 in the surface sediment. Basic nutrients - e.g. nitrate or phosphate- enter the system via river input, atmospheric deposition, or recycling of organic matter. They are consumed by phytoplankton including cyanobacteria. Cyanobacteria do not consume nitrate or ammonium but fixate molecular nitrogen to obtain needed nitrogen. Phytoplankton including cyanobacteria is grazed by zooplankton. Plankton respirates and dies. Dead plankton becomes detritus that sinks to the sediment. The sediment is represented by an one-layer sediment only but contains relevant sediment processes such as phosphate release under anoxic conditions or denitrification.
FAIR
F-UJI result: total 66 %
Description
Summary: Findable: 6 of 7 level; Accessible: 2 of 3 level; Interoperable: 3 of 4 level; Reusable: 5 of 10 level
SQA - Scientific Quality Assurance 'approved by author'
Result Date
2019-11-20
Technical Quality Assurance (TQA)
TQA - Technical Quality Assurance 'approved by WDCC'
Description
1. Number of data sets is correct and > 0: passed; 2. Size of every data set is > 0: passed; 3. The data sets and corresponding metadata are accessible: passed; 4. The data sizes are controlled and correct: passed; 5. The temporal coverage description (metadata) is consistent to the data: passed; 6. The format is correct: passed; 7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
[1] DOINeumann, Daniel. (2019). Abschätzung der biogeochemischen Umsetzung, Sedimentation und Resuspension von Phosphorverbindungen in der Unterwarnow. doi:10.12754/misc-2019-0002
Is documented by
[1] DOIBauwe, Andreas; Eckhardt, Kai-Uwe; Lennartz, Bernd. (2019). Predicting dissolved reactive phosphorus in tile-drained catchments using a modified SWAT model. doi:10.1016/j.ecohyd.2019.03.003
[3] DOIMénesguen, Alain; Cugier, Philippe; Leblond, Isabelle. (2006). A new numerical technique for tracking chemical species in a multi-source, coastal ecosystem, applied to nitrogen causing Ulva blooms in the Bay of Brest (France). doi:10.4319/lo.2006.51.1_part_2.0591
[5] DOIRadtke, H.; Neumann, T.; Voss, M.; Fennel, W. (2012). Modeling pathways of riverine nitrogen and phosphorus in the Baltic Sea. doi:10.1029/2012jc008119
[6] DOISchernewski, Gerald; Friedland, Rene; Carstens, Marina; Hirt, Ulrike; Leujak, Wera; Nausch, Günther; Neumann, Thomas; Petenati, Thorkild; Sagert, Sigrid; Wasmund, Norbert; Weber, Mario von. (2015). Implementation of European marine policy: New water quality targets for German Baltic waters. doi:10.1016/j.marpol.2014.09.002
[7] DOINeumann, Thomas; Schernewski, Gerald. (2005). An ecological model evaluation of two nutrient abatement strategies for the Baltic Sea. doi:10.1016/j.jmarsys.2004.10.002
[3] DOINeumann, Thomas; Fennel, Wolfgang; Kremp, Christine. (2002). Experimental simulations with an ecosystem model of the Baltic Sea: A nutrient load reduction experiment. doi:10.1029/2001gb001450
[5] DOIRadtke, Hagen; Neumann, Thomas; Fennel, Wolfgang. (2013). A Eulerian nutrient to fish model of the Baltic Sea — A feasibility-study. doi:10.1016/j.jmarsys.2012.07.010