Climate Dataset Merging Exercise

This module checken includes a hands-on practice notebook and an answer key that walk through merging two climate datasets over a spatial domain with mismatched spatial and temporal resolution using xarray.

Learning Goals

• Stream remote NOAA reanalysis and precipitation products directly from THREDDS servers.
• Resample time coordinates and interpolate spatial grids with xr.resample and xr.interp.
• Combine harmonized variables with xr.merge, then explore the result via maps and simple diagnostics.

Repository Contents

• notebooks/merge_climate_datasets_exercise.ipynb – Student version with TODO cells and guidance for each processing step.

Environment

The Python environment you created in Module 2 (xarray-climate) already contains the required libraries for this assignment. Activate it with:

conda activate xarray-climate

or the equivalent command for your environment manager, then launch Jupyter Lab or Notebook to explore the materials.

Getting Started

1. Open the exercise notebook and work through each section, replacing the NotImplementedError placeholders.
2. The results in the last cells that generate a visualization and a dataset are the deliverables for the Check In.

Happy merging!