HARD-lib 1.0.1

Harmony Analysis Ready Dataset

Pre-requisites

1. Create an ECMWF account to access the ERA5 CDS API (for setup go to cds.climate.copernicus.eu). This is needed for wind-field information.

2. Create an Alaskan Satellite Fascility (ASF) account so that you may querry their API using asf_search. Store your ASK credentials in a .netrc file. This will be needed to download data from ASF.

An example .netrc:

machine asf
login YOURUSERNAME
password YOURPASSWORD

Installation

Create a new environment and activate

conda create -n ENV_NAME python==3.12

conda activate ENV_NAME

Conda install GDAL (not enabled from pip)

conda install GDAL

Clone HARD repository

git clone https://gitlab.tudelft.nl/yyuan6/hard.git

Navigate to cloned folder and install an editibale version

cd HARD

pip install -e .

Usage

Python

For Python tutorials refer to the notebook tutorials in hard/Tutorial/

Command Line Interface (CLI)

To run an automated download, processing and saving exercise using a bash script go to either:

• hard/HARD/CLI/download_process_save_local_example.sh
• hard/HARD/CLI/download_process_save_DelftBlue_example.sh

Please copy the files before editing and do not track them in this git repository.

NOTE

When submitting the bash script on Delft Blue, please make sure a logs subdirectory exists in the same location as the .sh file, e.g.:

mkdir -p logs
sbatch /home/.../hard/HARD/CLI/download_process_save_DelftBlue_example.sh

To Do

ERA5

• check if ERA5 file exists before downloading
• give downlaoded era5 files descriptive names relating to aoi (so that they may be reused)
• enable using pre-downlaoded era5 files

Processing

• return the xsar object instead of arbitrary roughness field
• land masking on radar data
• add attributes to file for all processing steps and
• get land mask from xsar variable
• streamline output types so that .values and .item() can be kept to a minimum
• remove unnecessary variables after preprocessing