DART-WRF documentation

DART-WRF is a python package which allows you to

• run the weather research and forecast model (WRF),

• generate (satellite) observations from a nature run,

• and assimilate these observations in ensemble data assimilation using DART,

• on a computing cluster or on your local machine.

Installation

DART-WRF can be downloaded from github.com/lkugler/DART-WRF. To use it, you don’t need to install it, but only its requirements:

git clone https://github.com/lkugler/DART-WRF.git
pip install xarray netCDF4 docopt pysolar==0.10.0

Note that pysolar is necessary to generate synthetic satellite observations.

First steps

To get started, go through the tutorials in the tutorials section. Tutorial 1 shows you how to configure DART-WRF, generate observations and assimilate them. Tutorial 2 shows you how to run a WRF forecast with the output from data assimilation. Tutorial 3 shows you how assimilation and forecast can be run in a cycle. See also the DART-WRF overview over directory structure, in- and output files.

Tutorials

• Tutorial 1: The assimilation step
  • Configuring the hardware
  • Configuring the experiment
  • Set up the workflow
• Tutorial 2: Forecast after DA
  • 1) Initialize from sounding profiles
  • 2) Initialize a forecast from a previous forecast
  • 3) Run the Forecast
• Tutorial 3: Cycle forecast and assimilation
  • Job scheduling status
• Adding and modifying scripts
  • Recipe to add new functionality

Other helpful resources

DART documentation [here] WRF user guide [here]

API

• Index

• Module Index

• Search Page