There is a newer version of the record available.

Published June 5, 2024 | Version v1
Dataset Open

In situ dataset for initialization and validation of the Copernicus Med-MFC biogeochemical model system (MedBGCins)

  • 1. ROR icon National Institute of Oceanography and Applied Geophysics
  • 2. Istituto Nazionale di Oceanografia e Geofisica Sperimentale

Description

The biogeochemical model system in use by the Mediterranean Monitoring Forecasting Centre (Med-MFC) of the EU Copernicus Marine Service requires several observational datasets for data assimilation and model initialization and validation (Coppini et al., 2023; Cossarini et al., 2021; Salon et al., 2019). The present MedBGCins dataset consists of the in situ measurements, coming from selected platforms, on which the initialization and validation of the biogeochemical model system are built. The MedBGCins dataset collects in situ measurements along the Mediterranean Sea water column and during the 1995-2023 time period for nutrients (i.e., nitrate, nitrite, phosphate, silicate, ammonium), dissolved oxygen, dissolved inorganic carbon, total alkalinity, total scale pH at 25°C. The dataset also provides pCO2 and total scale pH at in situ conditions, reconstructed by using the PyCO2SYS Python toolbox (Humpreys et al., 2024). The complete list of variables is indicated in Table 1. The largest subset of the original data are from EMODnet Chemistry Mediterranean Sea - Eutrophication and Acidity aggregated datasets 1911/2022 v2023 (reference in Table 2), including both profiles and time series, plus other documented cruises (same table).

Additional information and references are included in the UserGuide file.

 

Files

UserGuide.pdf

Files (124.7 MB)

Name Size Download all
md5:32c6f51ad2c801f7dac90d43487fe66f
1.3 MB Download
md5:14014aa74b219ade68b46aa96282e810
1.3 MB Download
md5:3fc706b17ab78a29fc91915dfe7c0d83
1.2 kB Preview Download
md5:e1d51a2b4d4805cc7f1d8681822fa304
60.0 MB Download
md5:57f665588151b92584bed5a6132d444d
61.8 MB Download
md5:f17bd1e39fec7e02977d59634d633806
130.4 kB Preview Download
md5:13f62faedb20fad5a0febc205524863e
123.2 kB Preview Download