Reference datasets needs - FY23-24

ACCESS-NRI would like to know the needs of the Working Groups for Reference Datasets. We would like to know what datasets of significance for the working group you would like to have hosted in a published data collection at NCI within the financial year 23-24. We need to create a list of likely datasets that will be ready within this timeframe so we can start the data management process for these datasets with you and NCI.

What is a Reference Dataset

A Reference Dataset is data that is of significance to the community and will be used by a range of users. Possible examples:

  • Datasets for input in climate models (forcings, ancillary datasets etc.)
  • Datasets for evaluation of model outputs
  • Reference model outputs that are used widely

What we need from you

If you have a dataset you think 1. can be considered as a Reference Dataset, 2. will be ready for publication before June 2024, please reply to this topic before 20th October with:

  • Dataset name
  • Contact name to liaise with publishing data (Forum handle)
  • Dataset URL if it exists
  • Dataset details to show its importance to the community, e.g. temporal and spatial coverage, nature of dataset (observations, reanalysis …), static or regularly updated
  • Current required storage in GB, projection for next year if not a static dataset

Consider watching this topic if you want to stay updated on what is happening with datasets for the working group.

Datasets list

Below is a table summarising datasets proposed by the working group:

Dataset Contact Storage (in GB)

Suggestions for global forcing datasets to share across community:
ERA5
ISIMIP
WDFE5
CRU-JRA

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LUH2 land use change dataset (historic and future).

https://luh.umd.edu/data.shtml

Note that this one is slightly different to what TRENDY uses, which is a merged product.

New gridinfo for CABLE using newest datasets and documented how the file was created. Would be good to have a separate Australia (5km?) and global file (25km?). A big effort but noting it here as one for the wishlist

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Fei Li - ML-based upscaling of FLUXNET @ MF-CW

Comment from @gab about MF-CW dataset:

As with FLUXCOM it’s an ensemble of products that I would not treat it as a well distributed ensemble estimate, or the spread as a good measure of observational uncertainty… possibly after careful ensemble sub-selection though

GlobAlbedo product via http://www.globalbedo.org/

Various incarnations of other remote sensing products (MODIS LAI and NDVI, Landsat).

IGBP soils and land cover, Soils Atlas of Australia (v2) (and other TERN landscapes data layers) - possibly better done as pointers to existing libraries