🌧️ Climate Data Retrieval Scripts

Overview

This Jupyter Notebook provides code to retrieve and process meteorological datasets.

The notebook currently focuses on accessing and handling two main datasets:

• NOAA's AORC (Analysis of Record for Calibration) dataset
• NASA's NEX-GDDP-CMIP6 downscaled climate projections via the Microsoft Planetary Computer

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📁 Repository Structure

data_retrival/
├── AORC/                  # Scripts and utilities to access AORC historical climate data
├── NEX_GDDP_CMIP6/        # Scripts to retrieve CMIP6 climate projections
├── LICENSE                # MIT License
└── README.md              # This file

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📦 Datasets Included

1. AORC – Analysis of Record for Calibration

• Source: NOAA National Water Model archive
• Access Method: Public AWS S3 via fsspec and xarray
• Format: Zarr / NetCDF
• Temporal Resolution: Hourly
• Spatial Resolution: ~1 km
• Time Period: 1979–Present
• Variables:
  • Precipitation (APCP_surface)

2. NEX-GDDP-CMIP6 – NASA Earth Exchange Downscaled Climate Projections

• Source: NASA / Microsoft Planetary Computer
• Access Method: STAC API with pystac-client, xarray, and planetary_computer
• Format: NetCDF / Zarr
• Temporal Resolution: Daily
• Spatial Resolution: ~25 km (0.25°)
• Time Period: Historical (1970–2014), Projections (2015–2100)
• Variables:
  • pr: Precipitation
  • tas: Near-surface air temperature
  • tasmax: Maximum daily temperature
  • tasmin: Minimum daily temperature
  • hurs: Relative humidity
  • huss: Specific humidity
  • rlds: Downward longwave radiation
  • rsds: Downward shortwave radiation
  • sfcWind: Near-surface wind speed

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🪪 License

This project is licensed under the MIT License – see the LICENSE file for details.