Author: ORNL DAAC
Date: February 28, 2018
Contact for ORNL DAAC: email@example.com
Keywords: ORNL DAAC, Daymet, weather estimates, Anomalies, Normals, THREDDS, OPeNDAP, Earthdata,
In this tutorial, we will explore using the
pydap package to plot
Daymet data. Specifically, we will calculate anomalies and normals for a weather estimate such as
prcp. To learn more about how to use Jupyter Notebooks, check out this
Python 2.7 or greater. Python modules:
matplotlib. To run this notebook locally, you will also need:
jupyter. Requirements are also in requirements.txt
For scientific computing, anaconda is recommended as it come pre-installed with packages such as numpy, iPython, and matplotlib.
Most operating systems, however, come with Python. To install the necessary python libraries, you can copy the requirements.txt from this repository and run:
pip install -r requirements.txt
In this tutorial the Daymet data is separated by year rather than aggregated into one tile. You can access the Jupyter Notebook here.