In [7]:
import xarray as xr
import os
import earthaccess
import getpass
import requests
from pydap.net import create_session
%matplotlib inline
# Create search query for 1980-01-01 Cloud OPeNDAP URL
results = earthaccess.search_data(
short_name="M2T1NXSLV",
version='5.12.4',
temporal=('1980-01-01', '1980-01-01'), # This will stream one granule, but can be edited for a longer temporal extent
bounding_box=(-180, 0, 180, 90)
)
# Parse out URL from request, add to OPeNDAP URLs list for querying multiple granules with constraint expressions
opendap_urls = []
for item in results:
for urls in item['umm']['RelatedUrls']: # Iterate over RelatedUrls in each request step
if 'OPENDAP' in urls.get('Description', '').upper(): # Check if 'OPENDAP' is in the Description
# Extract OPeNDAP URL, replace
url = urls['URL'].replace('https', 'dap4')
# Subset T2M, lat, lon, and time
# To view all variables, comment out these two lines
ce = "?dap4.ce=/{}%3B/{}%3B/{}%3B/{}".format("T2M", "lat", "lon", "time")
url = url + ce
# Add URL to list
opendap_urls.append(url)
# Use netrc file to authenticate
my_session = create_session()
# Uncomment the following block to use the .edl_token method instead of a netrc file
'''
# Set file path to root
token_file_path = os.path.join(os.path.expanduser("~"), ".edl_token")
# Read the token from the .edl_token file
with open(token_file_path, 'r') as token_file:
token = token_file.read().strip() # Ensure to strip any newlines or extra spaces
my_session = create_session(session_kwargs={"token": token})
'''
try:
# Load dataset object and metadata, but don't open the values yet
# NOTE: When opening HDF files, the group to be accessed must be specified with the "group=" parameter.
# E.g., for GPM IMERG, group="Grid" must be entered or an error will occur
# Remove the session parameter if you are just using a .netrc file to authenticate
ds = xr.open_mfdataset(opendap_urls, engine="pydap", session=my_session)
except OSError as e:
print('Error', e)
print('Please check that your .edl_token file exists and is valid, or that your username/password were entered correctly.')
raise
# Define latitude and longitude bounds for CONUS
lat_min, lat_max = 25, 50 # Latitude bounds
lon_min, lon_max = -125, -66 # Longitude bounds
# Subset the dataset based on lat/lon bounds, which is performed server-side
ds_conus = ds.sel(lat=slice(lat_min, lat_max), lon=slice(lon_min, lon_max))
# Plot the first timestep of the 2-meter temperature variable from the subsetted dataset
ds_conus['T2M'].isel(time=0).plot(cmap='coolwarm')
Out[7]:
<matplotlib.collections.QuadMesh at 0x17df34dc0>
