TornikeO/era5-5.625deg

Dataset Card for ERA5 climate dataset

This dataset is for reproducing ClimODE results, which aims to model the climate efficiently with physics-inspired neural networks. It contains a 2004-2018 subset of the weatherbench data at 5.625deg granularity.

Made with :heart: from by students at USI.

Dataset Details

Dataset Sources [optional]

• Repository: https://dataserv.ub.tum.de/index.php/s/m1524895
• Paper https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels

Uses

Climate modeling and prediction

Direct Use

This dataset is used as a supporting resource in Climode-reproducibility repository, which aims to reproduce and validate the original paper authors' claims.

You can download the dataset like so:

from huggingface_hub import snapshot_download

if __name__ == '__main__':
    snapshot_download(repo_id="TornikeO/era5-5.625deg",
                    repo_type='dataset',
                    local_dir='climode/ClimODE/era5_data', 
                    allow_patterns="*")

Dataset Structure

The dataset is a set of .nc files. These can be read as follows:

import xarray as xr

# Download the dataset from TornikeO/era5-5.625deg

data = xr.open_mfdataset(
    'era5-5.625deg/geopotential_500/*.nc', 
    combine='by_coords')
data = data.resample(time="6H").nearest(tolerance="1H") # Setting data to be 6-hour cycles
data_global = data.sel(time=slice('2006','2018')).load() # select subset only

Dataset Creation

Source Data

This dataset was generated by downloading WeatherBench data

Data Collection and Processing

Dataset was downloaded and processed using python, with a simple , using automated python download script.

Citation [optional]

BibTeX:

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APA:

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Glossary [optional]

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Dataset Card Authors [optional]

The Sole author is Tornike Onoprishvili.

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