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This is script to download and proccess NCEI-GSD observation data

Author

Quang-Van Doan

Description

A Python library for downloading and processing Global Summary of the Day (GSD) data from NCEI-NOAA.

Copyright (c) 2024 Quang-Van Doan

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Installation

Here's a step-by-step manual to install and use the nceigsd_datatools repository from GitHub on your local machine:

MInstall nceigsd_datatools Locally

1. Check Prerequisites

Make sure you have the following installed:

  • Python 3.7+
  • pip (Python package manager)
  • git (version control)

To check, run in terminal:

python --version
pip --version
git --version

If missing:

2. Clone the Repository

Use git to clone the repository to your computer:

git clone https://github.com/AtmosSciTools/nceigsd_datatools.git

This will create a folder named nceigsd_datatools.

3. Navigate to the Project Directory

cd nceigsd_datatools

4. Install the Package

pip install .

5. Usage

from nceigsd import NCEIGSDProcessor

processor = NCEIGSDProcessor(
    start_year=2010,         # start year
    end_year=2012,           # end year
    area=[18, 23, 102, 107], # lat1, lat2, lon1, lon2
    output_dir="output/test_output"  # download directory
)

processor.download_data()                    # Run data download and processing
processor.plot_station_locations() # Plot station locations with categories
processor.plot_availability_heatmaps()  # Plot heatmaps (if seaborn is available)

check test/test.ipynb

Test downloaded results

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