Example to load data from NRDA

pip install rocrate cmcrameri

import requests
import tempfile
import json
import os
from rocrate.rocrate import ROCrate
from rocrate.model.person import Person

import xarray as xr
import pandas as pd
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import cmcrameri

# URL of the RO-Crate metadata file
url = "https://s3.nird.sigma2.no/archive-sandbox-ro/3888d382-6269-479c-9448-701ad6e3fa74_metadata/dataset_metadata_10.82969_2025.pitlyjt0.json?response-content-disposition=attachment&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=TRnFBoNN9N9QfuRYw5mX%2F20250518%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20250518T175123Z&X-Amz-Expires=60&X-Amz-SignedHeaders=host&X-Amz-Signature=f089662d8f3c95f9fcde3fc9da0d00b7ff8a7ce2d0c2b8598a94d6f06f9ef30a"
# Output directory and file path
data_dir = "../data"
metadata_path = os.path.join(data_dir, "ro-crate-metadata.json")

# Create data directory if it doesn't exist
os.makedirs(data_dir, exist_ok=True)

if not os.path.exists(metadata_path):
    # Download metadata
    response = requests.get(url)
    if response.status_code != 200:
        raise Exception(f"Failed to download metadata: {response.status_code} - {response.text}")

    # Save as data/ro-crate-metadata.json
    with open(metadata_path, "wb") as f:
        f.write(response.content)
    print(f"Metadata saved to: {metadata_path}")

crate = ROCrate(data_dir)

root_dataset = crate.root_dataset

# Print metadata
print("=== Dataset Metadata ===")
print(f"Name: {root_dataset.get('name', 'Unnamed')}")
print(f"Description: {root_dataset.get('description', 'No description')}")
print(f"DOI: {root_dataset.get('identifier', 'No DOI')}")
print(f"Author: {root_dataset.get('author', 'Unknown')}")
print(f"License: {root_dataset.get('license', {}).get('@id', 'No license')}")
print(f"Date Published: {root_dataset.get('datePublished', 'Unknown')}")
print(f"Temporal Coverage: {root_dataset.get('temporalCoverage', 'Unknown')}")
location_entity = crate.dereference(root_dataset.get('location'))
print(f"Geospatial Coverage: {location_entity.get('polygon', 'Unknown') if location_entity else 'Unknown'}")

# Process hasPart files
print("\n=== Data Files ===")
files = []
for part in root_dataset.get('hasPart', []):
    part_id = part if isinstance(part, str) else getattr(part, 'id', None)
    if not part_id:
        continue
    part_entity = crate.dereference(part_id)
    if not part_entity or "File" not in part_entity.type:
        continue
    file_url = part_entity.id
    if not (file_url.endswith(".nc") or file_url.endswith(".zarr")):
        continue
    print(f"File part of the collection: {file_url}")
    try:
        files.append(file_url)
        print(f"\n=== Dataset found and opened with xarray ({file_url}) ===")
    except Exception as e:
        print(f"Failed to open {file_url}: {e}")

dset = xr.open_dataset(files[0], engine="h5netcdf") if file_url.endswith(".nc") else xr.open_zarr(files[0])
dset

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5), subplot_kw={'projection': ccrs.PlateCarree()})

# Time points and human-readable labels
times = dset['time'].values
time_labels = [pd.Timestamp(t).strftime('%Y-%m-%d') for t in times]

# Plot for 1980-07-01
im1 = dset.sel(time=times[0]).R.plot(ax=ax1, cmap='Blues', vmin=0, vmax=100,
                                     cbar_kwargs={'label': 'Relative Humidity (%)'})
ax1.coastlines()
ax1.add_feature(cfeature.BORDERS, linestyle=':')
ax1.set_title(f"Relative Humidity ({time_labels[0]})")
ax1.set_xlabel('Longitude')
ax1.set_ylabel('Latitude')
ax1.gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False)

# Plot for 2018-07-01
im2 = dset.sel(time=times[1]).R.plot(ax=ax2, cmap='Blues', vmin=0, vmax=100,
                                 cbar_kwargs={'label': 'Relative Humidity (%)'})
ax2.coastlines()
ax2.add_feature(cfeature.BORDERS, linestyle=':')
ax2.set_title(f"Relative Humidity ({time_labels[1]})")
ax2.set_xlabel('Longitude')
ax2.set_ylabel('Latitude')
ax2.gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False)

# Adjust layout and display
plt.tight_layout()
plt.show()