Author: EUMETSAT
Copyright: 2024 EUMETSAT
Licence: MIT
Destination Earth - Climate Change Adaptation Digital Twin Series Plot- Data Access using DEDL HDA#
Documentation DestinE Data Lake HDA
Climate DT overview (for DESP testing period)
Author: EUMETSAT
Credit: Earthkit and HDA Polytope used in this context are both packages provided by the European Centre for Medium-Range Weather Forecasts (ECMWF).
DEDL Harmonised Data Access is used in this example.
Obtain Authentication Token#
pip install --quiet --upgrade destinelab
Note: you may need to restart the kernel to use updated packages.
import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry
import json
import os
from getpass import getpass
import destinelab as deauth
First, we get an access token for the API
DESP_USERNAME = input("Please input your DESP username or email: ")
DESP_PASSWORD = getpass("Please input your DESP password: ")
auth = deauth.AuthHandler(DESP_USERNAME, DESP_PASSWORD)
access_token = auth.get_token()
if access_token is not None:
print("DEDL/DESP Access Token Obtained Successfully")
else:
print("Failed to Obtain DEDL/DESP Access Token")
auth_headers = {"Authorization": f"Bearer {access_token}"}
Response code: 200
DEDL/DESP Access Token Obtained Successfully
Check if DT access is granted#
If DT access is not granted, you will not be able to execute the rest of the notebook.
auth.is_DTaccess_allowed(access_token)
DT Output access allowed
True
Query using the DEDL HDA API#
Filter#
We have to setup up a filter and define which data to obtain.
Choose a valid combination of => Activity + Experiment + Model (based on the year of interest)
Following activities/experiment/model & dates are possible:
ScenarioMIP/ssp3-7.0/ICON: Start date 20200101, 40 years
ScenarioMIP/ssp3-7.0/IFS-NEMO: Start date 20200101, 40 years
datechoice = "2028-06-10T00:00:00Z"
filters = {
key: {"eq": value}
for key, value in {
"class": "d1", # fixed
"dataset": "climate-dt", # fixed climate-dt access
"activity": "ScenarioMIP", # activity + experiment + model (go together)
"experiment": "SSP3-7.0", # activity + experiment + model (go together)
"model": "IFS-NEMO", # activity + experiment + model (go together)
"generation": "1", # fixed Specifies the generation of the dataset, which can be incremented as required (latest is 1)
"realization": "1", # fixed Specifies the climate realization. Default 1. Based on perturbations of initial conditions
"resolution": "high", # standard/ high
"expver": "0001", # fixed experiment version
"stream": "clte", # fixed climate
"time": "0000", # choose the hourly slot(s)
"type": "fc", # fixed forecasted fields
"levtype": "sfc", # Surface fields (levtype=sfc), Height level fields (levtype=hl), Pressure level fields (levtype=pl), Model Level (Levtype=ml)
# "levelist": "1/2/3/...", # for ml/pl/sol type data
"param": "167" # 2m Temperature parameter
}.items()
}
Make Data Request#
from tqdm import tqdm
import time
import re
from datetime import datetime
from IPython.display import JSON
#Sometimes requests to polytope get timeouts, it is then convenient define a retry strategy
retry_strategy = Retry(
total=5, # Total number of retries
status_forcelist=[500, 502, 503, 504], # List of 5xx status codes to retry on
allowed_methods=["GET",'POST'], # Methods to retry
backoff_factor=1 # Wait time between retries (exponential backoff)
)
# Create an adapter with the retry strategy
adapter = HTTPAdapter(max_retries=retry_strategy)
# Create a session and mount the adapter
session = requests.Session()
session.mount("https://", adapter)
# Define date choice and filters if needed
datechoice = "2024-07-01"
# Initialize a list to store filenames
filenames = []
# Define start and end years
start_year = 2024
start_month = 7
end_year = 2028
# Loop
for year in range(start_year, end_year + 1):
# Create a datetime object
obsdate = datetime(year, start_month, 1)
datechoice = obsdate.strftime("%Y-%m-%dT12:00:00Z")
response = session.post("https://hda.data.destination-earth.eu/stac/search", headers=auth_headers, json={
"collections": ["EO.ECMWF.DAT.DT_CLIMATE_ADAPTATION"],
"datetime": datechoice,
"query": filters
})
# Requests to EO.ECMWF.DAT.DT_CLIMATE always return a single item containing all the requested data
# print(response.json())
product = response.json()["features"][0]
# DownloadLink is an asset representing the whole product
download_url = product["assets"]["downloadLink"]["href"]
print(download_url)
HTTP_SUCCESS_CODE = 200
HTTP_ACCEPTED_CODE = 202
direct_download_url = ''
response =session.get(download_url, headers=auth_headers)
response.raise_for_status()
if (response.status_code == HTTP_SUCCESS_CODE):
direct_download_url = product['assets']['downloadLink']['href']
elif (response.status_code != HTTP_ACCEPTED_CODE):
JSON(response.json(), expanded=True)
# we poll as long as the data is not ready
if direct_download_url == '':
while url := response.headers.get("Location"):
print(f"order status: {response.json()['status']}")
response = session.get(url, headers=auth_headers, stream=True)
response.raise_for_status()
# Check if Content-Disposition header is present
if "Content-Disposition" not in response.headers:
print(response)
print(response.json())
raise Exception("Headers: \n"+str(response.headers)+"\nContent-Disposition header not found in response. Must be something wrong.")
filename = re.findall('filename=\"?(.+)\"?', response.headers["Content-Disposition"])[0]
total_size = int(response.headers.get("content-length", 0))
print(f"downloading {filename}")
with tqdm(total=total_size, unit="B", unit_scale=True) as progress_bar:
with open(filename, 'wb') as f:
for data in response.iter_content(1024):
progress_bar.update(len(data))
f.write(data)
# Add the filename to the list
filenames.append(filename)
https://hda.data.destination-earth.eu/stac/collections/EO.ECMWF.DAT.DT_CLIMATE_ADAPTATION/items/DT_CLIMATE_ADAPTATION_20240701_20240701_83b724d2dd1b7706cb8391582868f3ea08a161e9/download?provider=dedt_lumi&_dc_qs=%257B%2522activity%2522%253A%2B%2522ScenarioMIP%2522%252C%2B%2522class%2522%253A%2B%2522d1%2522%252C%2B%2522dataset%2522%253A%2B%2522climate-dt%2522%252C%2B%2522date%2522%253A%2B%252220240701%252Fto%252F20240701%2522%252C%2B%2522experiment%2522%253A%2B%2522SSP3-7.0%2522%252C%2B%2522expver%2522%253A%2B%25220001%2522%252C%2B%2522generation%2522%253A%2B1%252C%2B%2522levtype%2522%253A%2B%2522sfc%2522%252C%2B%2522model%2522%253A%2B%2522IFS-NEMO%2522%252C%2B%2522param%2522%253A%2B167%252C%2B%2522realization%2522%253A%2B1%252C%2B%2522resolution%2522%253A%2B%2522high%2522%252C%2B%2522stream%2522%253A%2B%2522clte%2522%252C%2B%2522time%2522%253A%2B0%252C%2B%2522type%2522%253A%2B%2522fc%2522%257D
order status: queued
order status: processing
order status: processing
order status: processing
downloading e03a505a-c73c-47f5-9198-be3a02e0c7b2.grib
100%|██████████| 26.2M/26.2M [00:00<00:00, 30.2MB/s]
https://hda.data.destination-earth.eu/stac/collections/EO.ECMWF.DAT.DT_CLIMATE_ADAPTATION/items/DT_CLIMATE_ADAPTATION_20250701_20250701_b6fa7817c46cb4c19472364a6f5109848a40b52d/download?provider=dedt_lumi&_dc_qs=%257B%2522activity%2522%253A%2B%2522ScenarioMIP%2522%252C%2B%2522class%2522%253A%2B%2522d1%2522%252C%2B%2522dataset%2522%253A%2B%2522climate-dt%2522%252C%2B%2522date%2522%253A%2B%252220250701%252Fto%252F20250701%2522%252C%2B%2522experiment%2522%253A%2B%2522SSP3-7.0%2522%252C%2B%2522expver%2522%253A%2B%25220001%2522%252C%2B%2522generation%2522%253A%2B1%252C%2B%2522levtype%2522%253A%2B%2522sfc%2522%252C%2B%2522model%2522%253A%2B%2522IFS-NEMO%2522%252C%2B%2522param%2522%253A%2B167%252C%2B%2522realization%2522%253A%2B1%252C%2B%2522resolution%2522%253A%2B%2522high%2522%252C%2B%2522stream%2522%253A%2B%2522clte%2522%252C%2B%2522time%2522%253A%2B0%252C%2B%2522type%2522%253A%2B%2522fc%2522%257D
order status: queued
order status: queued
order status: processing
order status: processing
order status: processing
downloading 2b2b9822-a717-42fe-8832-26295456031d.grib
100%|██████████| 24.6M/24.6M [00:00<00:00, 54.6MB/s]
https://hda.data.destination-earth.eu/stac/collections/EO.ECMWF.DAT.DT_CLIMATE_ADAPTATION/items/DT_CLIMATE_ADAPTATION_20260701_20260701_336ea16ea32bb425e1599bc03668ce822a46cc12/download?provider=dedt_lumi&_dc_qs=%257B%2522activity%2522%253A%2B%2522ScenarioMIP%2522%252C%2B%2522class%2522%253A%2B%2522d1%2522%252C%2B%2522dataset%2522%253A%2B%2522climate-dt%2522%252C%2B%2522date%2522%253A%2B%252220260701%252Fto%252F20260701%2522%252C%2B%2522experiment%2522%253A%2B%2522SSP3-7.0%2522%252C%2B%2522expver%2522%253A%2B%25220001%2522%252C%2B%2522generation%2522%253A%2B1%252C%2B%2522levtype%2522%253A%2B%2522sfc%2522%252C%2B%2522model%2522%253A%2B%2522IFS-NEMO%2522%252C%2B%2522param%2522%253A%2B167%252C%2B%2522realization%2522%253A%2B1%252C%2B%2522resolution%2522%253A%2B%2522high%2522%252C%2B%2522stream%2522%253A%2B%2522clte%2522%252C%2B%2522time%2522%253A%2B0%252C%2B%2522type%2522%253A%2B%2522fc%2522%257D
order status: queued
order status: queued
order status: queued
order status: processing
order status: processing
order status: processing
downloading 4d1931dd-d92e-4e41-be84-c9b3c39bf503.grib
100%|██████████| 26.2M/26.2M [00:00<00:00, 54.6MB/s]
https://hda.data.destination-earth.eu/stac/collections/EO.ECMWF.DAT.DT_CLIMATE_ADAPTATION/items/DT_CLIMATE_ADAPTATION_20270701_20270701_e4f64c7f8331b3d33a6dcaaa03ddbc39b15dd593/download?provider=dedt_lumi&_dc_qs=%257B%2522activity%2522%253A%2B%2522ScenarioMIP%2522%252C%2B%2522class%2522%253A%2B%2522d1%2522%252C%2B%2522dataset%2522%253A%2B%2522climate-dt%2522%252C%2B%2522date%2522%253A%2B%252220270701%252Fto%252F20270701%2522%252C%2B%2522experiment%2522%253A%2B%2522SSP3-7.0%2522%252C%2B%2522expver%2522%253A%2B%25220001%2522%252C%2B%2522generation%2522%253A%2B1%252C%2B%2522levtype%2522%253A%2B%2522sfc%2522%252C%2B%2522model%2522%253A%2B%2522IFS-NEMO%2522%252C%2B%2522param%2522%253A%2B167%252C%2B%2522realization%2522%253A%2B1%252C%2B%2522resolution%2522%253A%2B%2522high%2522%252C%2B%2522stream%2522%253A%2B%2522clte%2522%252C%2B%2522time%2522%253A%2B0%252C%2B%2522type%2522%253A%2B%2522fc%2522%257D
order status: queued
order status: queued
order status: queued
order status: processing
order status: processing
downloading f1449031-b967-42f0-8ae0-2faa02135d5e.grib
100%|██████████| 26.2M/26.2M [00:00<00:00, 41.4MB/s]
https://hda.data.destination-earth.eu/stac/collections/EO.ECMWF.DAT.DT_CLIMATE_ADAPTATION/items/DT_CLIMATE_ADAPTATION_20280701_20280701_3d63a781eb3e389cb90a683a5b0cd0a326ddd22f/download?provider=dedt_lumi&_dc_qs=%257B%2522activity%2522%253A%2B%2522ScenarioMIP%2522%252C%2B%2522class%2522%253A%2B%2522d1%2522%252C%2B%2522dataset%2522%253A%2B%2522climate-dt%2522%252C%2B%2522date%2522%253A%2B%252220280701%252Fto%252F20280701%2522%252C%2B%2522experiment%2522%253A%2B%2522SSP3-7.0%2522%252C%2B%2522expver%2522%253A%2B%25220001%2522%252C%2B%2522generation%2522%253A%2B1%252C%2B%2522levtype%2522%253A%2B%2522sfc%2522%252C%2B%2522model%2522%253A%2B%2522IFS-NEMO%2522%252C%2B%2522param%2522%253A%2B167%252C%2B%2522realization%2522%253A%2B1%252C%2B%2522resolution%2522%253A%2B%2522high%2522%252C%2B%2522stream%2522%253A%2B%2522clte%2522%252C%2B%2522time%2522%253A%2B0%252C%2B%2522type%2522%253A%2B%2522fc%2522%257D
order status: processing
order status: processing
order status: processing
downloading 99ea99dc-2b2a-42e1-934f-a48c577772df.grib
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EarthKit#
Lets plot the result file [EarthKit Documentation] https://earthkit-data.readthedocs.io/en/latest/index.html
This section requires that you have ecCodes >= 2.35 installed on your system.
You can follow the installation procedure at https://confluence.ecmwf.int/display/ECC/ecCodes+installation
import earthkit.data
import earthkit.maps
import earthkit.regrid
# Iterate over filenames
for filename in filenames:
print(filename) # For example, print each filename
data = earthkit.data.from_source("file", filename)
data.ls
earthkit.maps.quickplot(data,#style=style
)
e03a505a-c73c-47f5-9198-be3a02e0c7b2.grib
2b2b9822-a717-42fe-8832-26295456031d.grib
4d1931dd-d92e-4e41-be84-c9b3c39bf503.grib
f1449031-b967-42f0-8ae0-2faa02135d5e.grib
99ea99dc-2b2a-42e1-934f-a48c577772df.grib
