Data used in "BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean"

<div> <p>This repository contains the data used to generate the figures for the submitted manuscript "BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean".</p> </div> <h3>Contents</h3> <div> <ul> <li> <p>Model input:</p> <ul> <li> <p>INPUTS: ocean model input/grid files</p> </li> <li> <p>PISCES_INPUTS: BGC input files</p> </li> <li> <p>OBC: open boundary forcing&nbsp;</p> </li> <li> <p>WEIGHTS: weight files for ERA interim forcing</p> </li> </ul> </li> </ul> </div> <div> <ul> <li> <p>Manuscript files:</p> <ul> <li> <p>data: files used to generate manuscript images</p> </li> <li> <p>config, src, notebooks: Python code and Jupyter notebooks used to generate images</p> </li> <li> <p>figures, supplementary: manuscript figures and supplementary figures</p> </li> </ul> </li> </ul> </div> <div>&nbsp;</div> <div><strong>Abstract: </strong>"We present BIOPERIANT12, a regional model configuration of the Southern Ocean (SO) at a mesoscale-resolving&nbsp;1/12 degree. This is a stable, ocean&ndash;ice&ndash;biogeochemical configuration derived from the Nucleus for European Modelling of the&nbsp;Ocean (NEMO) modelling platform. It is specifically designed to investigate questions related to the mean state, seasonal cycle&nbsp;variability and mesoscale processes in the mixed layer and within the upper ocean (&lt;1000 m). In particular, the focus is on understanding processes behind carbon and heat exchange, systematic errors in biogeochemistry and assumptions underlying&nbsp;the parameters chosen to represent these SO processes. The dynamics of the ocean model play a large role in driving ocean&nbsp;biogeochemistry and we show that over the chosen period of analysis 2000&ndash;2009 that the simulated dynamics in the upper&nbsp;ocean provide a stable mean state, as compared to observation-based datasets (themselves subject to biases such as sparsity of&nbsp;data, cloud cover, etc.), and through which the characteristics of variability can be described. Using ocean biomes to delineate&nbsp;the major regions of the SO, the model demonstrates a useful representation of ocean biogeochemistry and partial pressure&nbsp;of carbon dioxide (pCO2). In addition to a reasonable model mean state performance, through model&ndash;data metrics BIOPERIANT12&nbsp;highlights several pathways for improving Southern Ocean model simulations such as the representation of temporal&nbsp;variability and the overestimation of biological biomass."</div>