Setting Up `dev-MC_100km_jra_iaf+wombatlite` Configuration

by Alex Johnson 59 views

This article provides a detailed guide on setting up the dev-MC_100km_jra_iaf+wombatlite configuration, based on discussions within the ACCESS-NRI and access-om3-configs categories. This configuration involves running a single Ice-ocean-atmosphere Flux (IAF) cycle of the Marine Chemistry (MC) model with WOMBATlite at a 100km resolution. This setup is essential for various research activities and simulations, making it crucial to have a clear understanding of the steps involved.

Initial Considerations and Background

In our last OSIT meeting, there was significant interest in executing a single IAF cycle using the MC model with WOMBATlite at a 100km resolution. This specific configuration, dev-MC_100km_jra_iaf+wombatlite, was identified as a key area for development and implementation. The goal is to establish a functional and reliable setup that can be used for future simulations and experiments. To achieve this, several steps need to be carefully considered and executed.

Before diving into the setup process, it’s important to understand the components involved. The Marine Chemistry (MC) model is a sophisticated tool used for simulating ocean biogeochemistry. WOMBATlite is a simplified version of the more comprehensive WOMBAT (Whole-Ocean Model for Biogeochemistry and Trophic interactions) model, making it computationally efficient for certain applications. The IAF cycle represents a specific type of simulation where the model is forced with observed atmospheric data, allowing for a more realistic representation of ocean conditions. Combining these elements at a 100km resolution provides a balance between computational cost and model fidelity, making it suitable for a range of research questions.

Understanding the requirements and the purpose of this configuration is crucial for its successful implementation. This setup will enable researchers to explore various aspects of ocean biogeochemistry under realistic forcing conditions. The ability to run single IAF cycles efficiently is particularly valuable for sensitivity studies and model validation exercises. Therefore, ensuring that the configuration is set up correctly is a foundational step for many subsequent analyses and simulations.

Step 1: Decide on WOMBATlite Initial Conditions

Choosing the appropriate initial conditions for WOMBATlite is a critical first step in setting up the dev-MC_100km_jra_iaf+wombatlite configuration. The initial conditions provide the starting point for the simulation, and their accuracy can significantly influence the model's behavior and results. In consultation with @pearseb, we decided to adopt the same initial conditions that are currently used in the Routine Year Forcing (RYF) configuration. This decision ensures consistency and comparability with existing simulations, leveraging established practices within the research group.

The specific initial conditions selected for WOMBATlite include a range of biogeochemical variables, each playing a crucial role in the model's dynamics. These variables are:

  • no3: Nitrate concentration, sourced from GLODAP v2
  • phy: Phytoplankton concentration, set to 1e-08 mol kg-1
  • phyfe: Phytoplankton iron concentration, set to 1e-13 mol kg-1
  • o2: Oxygen concentration, sourced from GLODAP v2
  • zoo: Zooplankton concentration, set to 1e-08 mol kg-1
  • zoofe: Zooplankton iron concentration, set to 1e-13 mol kg-1
  • det: Detritus concentration, set to 1e-08 mol kg-1
  • detfe: Detritus iron concentration, set to 1e-13 mol kg-1
  • caco3: Calcium carbonate concentration, set to 1e-08 mol kg-1
  • dic: Dissolved inorganic carbon concentration, sourced from GLODAP v2
  • dicp: Dissolved inorganic phosphorus concentration, set to 0.0 mol kg-1
  • dicr: Dissolved inorganic radiocarbon concentration, set to 0.0 mol kg-1
  • alk: Alkalinity, sourced from GLODAP v2
  • fe: Iron concentration, sourced from FEMIP
  • pchl: Phytoplankton chlorophyll concentration, set to 2e-10 mol kg-1
  • caco3_sediment: Calcium carbonate sediment concentration, set to 0.0 mol kg-1
  • det_sediment: Detritus sediment concentration, set to 0.0 mol kg-1
  • detfe_sediment: Detritus iron sediment concentration, set to 0.0 mol kg-1
  • caco3bury: Calcium carbonate burial rate, set to 0.0 mol kg-1
  • detbury: Detritus burial rate, set to 0.0 mol kg-1

The selection of these initial conditions is based on a combination of empirical data and model requirements. GLODAP v2 (Global Ocean Data Analysis Project version 2) provides high-quality, observation-based data for various ocean biogeochemical parameters, ensuring that the model starts with realistic representations of nutrient and carbon distributions. FEMIP (iron model) data is used for iron concentrations, which are crucial for phytoplankton growth and overall marine productivity. The other variables are set to low values to minimize their initial impact on the simulation, allowing the model to evolve based on its internal dynamics and forcing conditions.

Step 2: Script for Generating IAF CO2 Forcing

Generating the appropriate Ice-ocean-atmosphere Flux (IAF) CO2 forcing is a pivotal step in configuring the dev-MC_100km_jra_iaf+wombatlite setup. The CO2 forcing acts as a crucial driver for the model, influencing ocean carbon uptake, pH levels, and overall biogeochemical dynamics. Therefore, creating an accurate and reliable script for generating this forcing is essential for the integrity of the simulation.

The process of generating IAF CO2 forcing typically involves utilizing observational data and atmospheric models to create a time-varying representation of CO2 concentrations at the ocean surface. This forcing data is then used to drive the ocean model, simulating how the ocean responds to changing atmospheric CO2 levels. The script needs to handle various data formats, interpolation methods, and temporal resolutions to ensure compatibility with the ocean model.

Key considerations in developing the script include:

  • Data Sources: Identifying and accessing reliable sources of atmospheric CO2 data, such as observations from monitoring stations or output from atmospheric models.
  • Temporal Resolution: Ensuring that the CO2 forcing data has an appropriate temporal resolution (e.g., daily, monthly) to capture seasonal and interannual variability.
  • Spatial Interpolation: Handling spatial variations in CO2 concentrations, potentially requiring interpolation techniques to map the data onto the model grid.
  • Data Format: Converting the CO2 data into a format that is compatible with the ocean model, often requiring specific file formats and data structures.
  • Error Handling: Implementing robust error handling to address missing data, outliers, or other potential issues in the input data.

Developing this script requires a combination of scientific understanding and technical expertise. It is crucial to validate the generated CO2 forcing data against independent observations or model outputs to ensure its accuracy and reliability. This validation process may involve comparing the generated forcing data with historical records or other datasets to identify any discrepancies or biases.

The script for generating IAF CO2 forcing is not just a technical tool; it represents a critical link between atmospheric conditions and ocean biogeochemical processes in the model. A well-designed script ensures that the model is forced with realistic and accurate CO2 data, leading to more reliable and meaningful simulation results.

Step 3: Create Configuration Branch

Creating a dedicated configuration branch is an essential step in setting up the dev-MC_100km_jra_iaf+wombatlite configuration. This practice ensures that the new setup is isolated from the main codebase, allowing for experimentation and development without disrupting existing configurations. A well-managed configuration branch provides a structured environment for making changes, testing, and ultimately integrating the new setup into the broader model framework.

The process of creating a configuration branch typically involves using a version control system, such as Git. The branch serves as a parallel line of development, where modifications and additions specific to the dev-MC_100km_jra_iaf+wombatlite setup can be made. This isolation is crucial for maintaining the stability and integrity of the main codebase, while simultaneously enabling focused development on the new configuration.

Key aspects of creating and managing a configuration branch include:

  • Branch Naming: Adopting a clear and consistent naming convention for the branch, such as dev-MC_100km_jra_iaf+wombatlite, to facilitate easy identification and organization.
  • Branching Strategy: Following a well-defined branching strategy, such as Gitflow, to manage the flow of changes and ensure that the main codebase remains stable.
  • Code Modifications: Making all necessary code modifications and additions within the branch, ensuring that the new configuration is self-contained and does not introduce conflicts with other parts of the codebase.
  • Testing and Validation: Thoroughly testing and validating the new configuration within the branch, ensuring that it functions as expected and produces reliable results.
  • Merge Process: Once the configuration is deemed stable and validated, merging the branch back into the main codebase, typically through a pull request or similar mechanism.

By creating a dedicated configuration branch, developers can work collaboratively and efficiently on the dev-MC_100km_jra_iaf+wombatlite setup. This approach allows for parallel development, reduces the risk of introducing bugs into the main codebase, and provides a clear audit trail of changes made to the configuration.

Conclusion

Setting up the dev-MC_100km_jra_iaf+wombatlite configuration involves a series of critical steps, each contributing to the overall success of the simulation. From deciding on the appropriate initial conditions and generating accurate CO2 forcing to creating a dedicated configuration branch, every aspect requires careful consideration and execution. This comprehensive guide provides a detailed roadmap for navigating the setup process, ensuring that researchers and developers can confidently implement this configuration for their specific needs.

By following these steps, you can establish a robust and reliable setup for running single IAF cycles of the MC model with WOMBATlite at a 100km resolution. This capability opens doors to a wide range of research opportunities, from sensitivity studies to model validation exercises. The dev-MC_100km_jra_iaf+wombatlite configuration represents a valuable tool for advancing our understanding of ocean biogeochemistry and its response to changing environmental conditions.

For more information on ocean modeling and related topics, you can visit NOAA's Ocean Modeling website.