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climate: era5 surface temperature data December 2024
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veronikasamborska1994 committed Dec 10, 2024
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2 changes: 1 addition & 1 deletion dag/climate.yml
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# Copernicus Climate Change Service - Surface temperature.
#
data://meadow/climate/2023-12-20/surface_temperature:
- snapshot://climate/2024-11-05/surface_temperature.zip
- snapshot://climate/2024-12-05/surface_temperature.zip
- snapshot://countries/2023-12-27/world_bank.zip
data://garden/climate/2023-12-20/surface_temperature:
- data://meadow/climate/2023-12-20/surface_temperature
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Expand Up @@ -137,11 +137,12 @@ def run(dest_dir: str) -> None:
f"It wasn't possible to extract temperature data for {len(small_countries)} small countries as they are too small for the resolution of the Copernicus data."
)
# Define the start and end dates
da["date"] = pd.to_datetime(da["date"].astype(str), format="%Y%m%d")
da["valid_time"] = pd.to_datetime(da["valid_time"].astype(str), format="ISO8601")
print(da["valid_time"])

# Now you can access the 'dt' accessor
start_time = da["date"].min().dt.date.astype(str).item()
end_time = da["date"].max().dt.date.astype(str).item()
start_time = da["valid_time"].min().dt.date.astype(str).item()
end_time = da["valid_time"].max().dt.date.astype(str).item()

# Generate a date range from start_time to end_time with monthly frequency
month_middles = pd.date_range(start=start_time, end=end_time, freq="MS") + pd.offsets.Day(14)
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2 changes: 1 addition & 1 deletion snapshots/climate/2024-11-19/total_precipitation.py
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"""Script to create a snapshot of the monthly averaged surface temperature data from 1950 to present from the Copernicus Climate Change Service.
"""Script to create a snapshot of the precipitation data from 1950 to present from the Copernicus Climate Change Service.
The script assumes that the data is available on the CDS API.
Instructions on how to access the API on a Mac are here: https://confluence.ecmwf.int/display/CKB/How+to+install+and+use+CDS+API+on+macOS
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56 changes: 56 additions & 0 deletions snapshots/climate/2024-12-05/surface_temperature.py
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"""Script to create a snapshot of the monthly averaged surface temperature data from 1950 to present from the Copernicus Climate Change Service.
The script assumes that the data is available on the CDS API.
Instructions on how to access the API on a Mac are here: https://confluence.ecmwf.int/display/CKB/How+to+install+and+use+CDS+API+on+macOS
More information on how to access the data is here: hhttps://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=overview
The data is downloaded as a NetCDF file. Tutorials for using the Copernicus API are here and work with the NETCDF format are here: https://ecmwf-projects.github.io/copernicus-training-c3s/cds-tutorial.html
"""


import tempfile
from pathlib import Path

# CDS API
import cdsapi
import click

from etl.snapshot import Snapshot

# Version for current snapshot dataset.
SNAPSHOT_VERSION = Path(__file__).parent.name


@click.command()
@click.option("--upload/--skip-upload", default=True, type=bool, help="Upload dataset to Snapshot")
def main(upload: bool) -> None:
# Create a new snapshot.
snap = Snapshot(f"climate/{SNAPSHOT_VERSION}/surface_temperature.zip")
snap
# Save data as a compressed temporary file.
with tempfile.TemporaryDirectory() as temp_dir:
output_file = Path(temp_dir) / "era5_monthly_t2m_eur.nc"

client = cdsapi.Client()

dataset = "reanalysis-era5-single-levels-monthly-means"
request = {
"product_type": ["monthly_averaged_reanalysis"],
"variable": ["2m_temperature"],
"year": [str(year) for year in range(1940, 2025)],
"month": ["01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12"],
"time": "00:00",
"area": [90, -180, -90, 180],
"data_format": "netcdf",
"download_format": "zip",
}

client.retrieve(dataset, request, output_file)

# Upload snapshot.
snap.create_snapshot(filename=output_file, upload=upload)


if __name__ == "__main__":
main()
26 changes: 26 additions & 0 deletions snapshots/climate/2024-12-05/surface_temperature.zip.dvc
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meta:
origin:
title_snapshot: ERA5 Monthly Averaged Data on Single Levels from 1940 to Present - Monthly Averages of 2m Surface Temperature
title: ERA5 monthly averaged data on single levels from 1940 to present
description: |-
ERA5 is the latest climate reanalysis produced by ECMWF, providing hourly data on many atmospheric, land-surface and sea-state parameters together with estimates of uncertainty.

ERA5 data are available in the Climate Data Store on regular latitude-longitude grids at 0.25° x 0.25° resolution, with atmospheric parameters on 37 pressure levels.

ERA5 is available from 1940 and continues to be extended forward in time, with daily updates being made available 5 days behind real time

Initial release data, i.e., data no more than three months behind real time, are called ERA5T.
producer: Contains modified Copernicus Climate Change Service information
version_producer: 2
citation_full: |-
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on 19-Nov-2024)
url_main: https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=overview
date_accessed: 2024-12-05
date_published: 2019-12-04
license:
name: Copernicus License
url: https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=overview
outs:
- md5: 63aa98ba0272c654be00eaa4779c253d
size: 1396486999
path: surface_temperature.zip

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