FAQ


How to setup Python for using NAAD direct access (DAP)

You need to install Pydap, requests and lxml in your Python environment (if not installed already):
# pip install Pydap requests lxml

How to use direct access (DAP) in Python: Example

To get direct access to the NAAD, you need to connect to the server first. It can be accomplished by using setup_session from the pydap library. To get the file handler, use setup_session from the same library. So the final code will look like:

from pydap.client import open_url
from pydap.cas.get_cookies import setup_session

# connect to the NAAD database
session = setup_session("https://naad.ocean.ru/accounts/login/",
	username="USER_NAME",
	password="USER_PASSWORD"
	)

# get the file handler
dataset = open_url('https://naad.ocean.ru/dapserver/LoRes/Invariants/NAAD77km_isor.nc',
	session=session)

# read the variable
var = dataset['isor']

# print the array sizes
print(var.shape)

Here we accessed the NAAD database, read the static variable isor from the NAAD LoRes dataset and printed the shape of the array.

Design and development: Alexander Gavrikov, Andrey Muratov; Support: naad-at-ocean.ru; 2020
Open access

Access to the NAAD data is now available through the Data Access Protocol (DAP). Details are in the Download section.

The NAAD LoRes (77km) has been uploaded

All variables listed in the Variables section have been uploaded for the LoRes (77 km) run of the NAAD dataset. The NAAD HiRes (14 km) is currently uploading. Access to the data will be provided within a few weeks.

Revised list of variables provided

The short list of potentially the most demanded variables is now in the Variables section both for LoRes and HiRes datasets. It will soon be available for download. The long list will be provided later.