Regional Climate Forcing Data Explorer


All figures shown in this tab are based on the Observation-based climate related forcing (obsclim) outputs from the GFDL-MOM6-COBALT2 model. These data were originally obtained from the ISIMIP Data Repository.

The Climatological map tab below shows the mean climatology (1961-2010) for the environmental variable and within the boundaries of the regional model of interest selected on the left.

The Time series plot tab below shows the area-weighted monthly mean between 1961 and 2010.

Note: The variable names and units shown in the dropdown list and plots come from the GFDL-MOM6-COBALT2 model. We have chosen not apply any transformation to the original model outputs. Instead, we summarised data so we could create the map and time series plots within the limits of all FishMIP regional models. If your model requires environmental data to be in a unit or grid that is different to the one available in the GFDL-MOM6-COBALT2 model, you can download the data from this website and post-process it to meet your needs.




Figures shown in this tab use data from the World Ocean Atlas 2023 (WOA23) . We used the objectively analysed climatologies field to create the climatological maps and area-weighted monthly climatology time series plot. While, the number of observations variable was used to create the maps shown in the sub-tab under the same name.

Note: The variable names and units shown in the dropdown list and plots come from the WOA23. We have chosen not apply any transformation to the original data. Instead, we summarised data so we could create maps and time series plots within the limits of all FishMIP regional models. If your model requires environmental data to be in a unit or grid that is different to the one available in the WOA23 you can download the data from this website and post-process it to meet your needs.

For some regions, the WOA23 dataset may have a very limited number of observations and so it may not offer the most realistic representation of your area of interest. In this case, you may choose to use a different observational product to assess the performance of GFDL-MOM6-COBALT2 outputs. We have an example notebook showing how you can regrid this data to match the grid used by the GFDL-MOM6-COBALT2 model.







Note: The grey ribbon in the plot above shows the spatial variance in the variable of interest.




The following processing steps were taken before comparing GFDL model outputs and WOA data:
1. Climatological mean was calculated using GFDL outputs between 1981 and 2010.
2. WOA data was regridded to match the GFDL outputs.
3. Difference was calculated by substracting WOA data from GFDL model outputs.

This means that positive values in the maps identify areas where GFDL overestimated mean conditions.




The fishing effort and catch data used to create plots in this tab were obtained from 'ISIMIP3a reconstructed fishing activity data (v1.0)' (Novaglio et al. 2024).

The fishing effort and catch data start in 1950, but the fishing effort forcing was reconstructed starting in 1841, which is available for download on the left panel.


About this website

This tool allows regional modellers to visualise environmental data from GFDL-MOM6-COBALT2 and from observations to determine if bias correction (Step 3 below) needs to be applied to the data prior to its use as forcings of a regional marine ecosystem model.



Who is FishMIP?

The Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) is an network of more than 100 marine ecosystem modellers and researchers from around the world. Our goal is to bring together our collective understanding to help better project the long-term impacts of climate change on fisheries and marine ecosystems, and to use our findings to help inform policy. You can find more information about FishMIP on our website.



How should I use this tool?

This site has three main tabs:

1. GFDL model outputs: Here you can download the GFDL-MOM6-COBALT2 ocean outputs as originally available in the ISIMIP data repository. Data available for download in this tab has not been processed in any way, we have simply extracted all available data within the boundaries of your region of interest.

2. World Ocean Atlas 2023 data: In this tab you can download World Ocean Atlas 2023 (WOA23) data that has been extracted for your region of interest. Note that data available for downloaded here has not been processed in any way and it is excatly as available in the original form. For more information refer to their documentation.

3. Model outputs against observations: In this tab you can download GFDL-MOM6-COBALT2 and WOA23 data for your region of interest. The WOA23 data available for download in this tab has been regridded to match GFDL-MOM6-COBALT2 to allow users to compare these products with ease.

4: Fishing effort and catch data: Here you can download the fishing effort and catch data that should be used to force your regional marine ecosystem models following FishMIP protocol 3a.

What are .zarr and .parquet files?

Although these two file formats store different types of data: zarr is designed for gridded data, while parquet files store tabular data. Both of them are cloud optimised file formats that are designed to make data storage and retrieval more efficient. This means that filesizes are smaller and you can load them faster than other files formats storing the same type of data (e.g., .csv, .txt, .nc).

Using these file formats also have the benefit of decreasing the time you need to wait for data to be downloaded from this website. This is especially true for regional models that cover a large geographical area.

To load parquet files into R we recommend you install the arrow package. Then use the read_parquet() function to load the parquet file as a tibble. From here, you can use tidyverse or base R to process the data as you would with any tabular dataset. If you are a Linux user, you may also want to consider the nanoparquet package.

To load zarr files in R, we recommend you use the Rarr package. For instructions on how to load these files in R, we created an example notebook.


How should I cite data from this site?

You can download the data used to create the plots shown in this interactive tool using the 'Download' button included under each tab. As a condition of this tool to access data, you must cite its use. Please use the following citations:

- Fierro-Arcos, D., Blanchard, J. L., Clawson, G., Flynn, C., Ortega Cisneros, K., Reimer, T. (2024). FishMIP input explorer for regional ecosystem modellers.

When using the data products in a publication, please include the following citation in addition to the data product citation provided above:

- Ortega-Cisneros, K., Fierro-Arcos, D. Lindmark, M., et al. (2025). An Integrated Global-to-Regional Scale Workflow for Simulating Climate Change Impacts on Marine Ecosystems. Earth's Future, 13, e2024EF004826. DOI: https://doi.org/10.1029/2024EF004826

When using GFDL-MOM6-COBALT2 model outputs, you also need to include the following citation:

- Xiao Liu, Charles Stock, John Dunne, Minjin Lee, Elena Shevliakova, Sergey Malyshev, Paul C.D. Milly, Matthias Büchner (2022): ISIMIP3a ocean physical and biogeochemical input data [GFDL-MOM6-COBALT2 dataset] (v1.0). ISIMIP Repository. DOI: 10.48364/ISIMIP.920945

If using WOA23 data, please refer to their product documentation for the most appropriate citation.

The fishing and catch data should be cited as follows:

- Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Julia L. Blanchard (2024): ISIMIP3a reconstructed fishing activity data (v1.0). ISIMIP Repository. DOI: 10.48364/ISIMIP.240282


How can I contact you?

If you are interested in our regional modelling work and would like to be part of the FishMIP community, you can head to the 'Join us' section of our website for more information.

If you would like to suggest changes or have spotted an issue with this app, you can create an issue in our GitHub repository.


Acknowledgments

The development of this tool was funded by the Australian Government through the Australian Research Council (ARC) Future Fellowship Project FT210100798. We gratefully acknowledge contributions from coordinators and contributing modellers of the FishMIP and ISIMIP communities. We would also like to acknowledge OceanHackWeek participants for contributing to the development of this tool. Finally, we would also like to acknowledge the use of computing facilities provided by Digital Research Services, IT Services at the University of Tasmania.