TerraClimateDownloader QGIS Plugin

🌍 Overview

TerraClimateDownloader is a QGIS plugin that allows you to directly download and clip TerraClimate datasets (monthly climate & water balance variables, 1958–2025) via OPeNDAP. It connects to the TerraClimate THREDDS server, extracts a bounding-box subset using xarray and rioxarray, saves a temporary GeoTIFF, and then clips it to any polygon boundary in your QGIS project using GDAL.

• 📅 Supports any year from 1958–2025
• 🌡️ Supports all 14 TerraClimate variables (ppt, tmax, tmin, vap, vpd, aet, def, pdsi, pet, q, soil, srad, swe, ws)
• 📆 Single year or year range mode for multi-year downloads
• 🎨 Automatic pseudocolor styling with variable-appropriate color ramps
• 🗺️ Clips raster outputs to any vector boundary
• ✂️ Split Raster Bands tool to export multiband outputs as individual monthly or yearly files
• ⚡ Adds the result automatically to your QGIS project
• 📦 One-click dependency installer via OSGeo4W Shell
• 🔍 Available in Processing Toolbox and Plugins menu

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📦 Installation

1. Download the latest release ZIP: TerraClimateDownloader.zip

2. In QGIS:

   • Go to Plugins → Manage and Install Plugins → Install from ZIP
   • Select TerraClimateDownloader.zip
   • Enable the plugin

3. Install dependencies (first time only):

   • Go to Plugins → TerraClimate Downloader → Install Dependencies
   • Click "Install Dependencies (OSGeo4W Shell)"
   • Wait for the installation to finish in the shell window
   • Restart QGIS

4. Access the plugin from:

   • Processing Toolbox → TerraClimate Downloader → Download TerraClimate Data
   • Processing Toolbox → TerraClimate Downloader → Split Raster Bands
   • Plugins Menu / Toolbar → TerraClimate Downloader

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⚙️ Requirements

This plugin requires the following Python packages installed into your QGIS Python environment:

Package	Status	Minimum Version
xarray	Required	2023.1.0
rioxarray	Required	0.15.0
numpy	Required	1.24
netCDF4	Required	1.6.0
dask	Optional	—

Automatic Installation (Recommended)

Use the built-in installer: Plugins → TerraClimate Downloader → Install Dependencies. It opens an OSGeo4W Shell and runs the install command for you.

Manual Installation

On Windows (OSGeo4W Shell):

python -m pip install xarray rioxarray "numpy>=1.24" netCDF4 dask

On Linux/macOS:

pip3 install --user xarray rioxarray "numpy>=1.24" netCDF4 dask

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🚀 Usage

Download TerraClimate Data

1. Load a polygon boundary layer into QGIS (e.g., a country or district shapefile).
2. Run Download TerraClimate Data from the Processing Toolbox or Plugins menu.
3. Configure:
   • Input polygon layer — your area of interest
   • Climate variable — choose from 14 variables (temperature, precipitation, etc.)
   • Year mode — Single year or Year range
   • Year / End year — select your time period (1958–2025)
   • Month — -1 for all months (multiband), or 1–12 for a specific month
   • Buffer — extra area around your boundary in degrees
4. Click Run → a clipped GeoTIFF is downloaded, styled, and added to the map.

Split Raster Bands

Use this tool to break apart multiband rasters (from year range downloads) into separate files:

• Monthly mode — each band becomes its own GeoTIFF (e.g., tmax_01_Jan_2023.tif)
• Yearly mode — every 12 bands are grouped into one file per year (e.g., tmax_2023.tif)

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🎨 Automatic Styling

Downloaded rasters are automatically styled with color ramps suited to each variable:

Variable Type	Color Ramp
Temperature (tmax, tmin)	Blue → White → Red
Precipitation (ppt, q)	Yellow → Green → Blue
Drought Index (pdsi)	Red → White → Blue (centered on zero)
Moisture (aet, pet, soil, vap)	Brown → Teal
Water Deficit (def, vpd)	Green → Yellow → Red
Radiation (srad)	Purple → Yellow → White
Snow (swe)	Light Blue → Dark Blue
Wind Speed (ws)	Yellow → Dark Green

For multiband outputs, min/max is calculated across all bands so colors remain consistent when switching between months.

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🎬 Video Tutorial

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📖 Data Source

TerraClimate Dataset: Abatzoglou, J.T., S.Z. Dobrowski, S.A. Parks, K.C. Hegewisch (2018). TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Scientific Data, 5:170191. DOI:10.1038/sdata.2017.191

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🎨 Credits

• Plugin Author: Hemed Lungo (Hemedlungo@gmail.com)
• Icon: by Fusion5085 (licensed for free use)
• Dataset: TerraClimate, Abatzoglou et al. (2018)

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📜 License

This plugin is released under the MIT License. See LICENSE for details.

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🙌 Acknowledgements

Thanks to the QGIS community and GDAL/xarray developers for the tools that make this plugin possible.