Add example for efficient handling of large weather datasets

[AjayKumar0403]

Description

This PR adds an example demonstrating how to efficiently handle large weather datasets in the Weather Routing Tool.

What is included

• Loading datasets using chunking (Dask)
• Subsetting and interpolation of data
• Saving processed data in NetCDF and Zarr formats
• Basic performance comparison between storage formats

Motivation

While working with weather datasets, I observed that handling large NetCDF files can lead to increased memory usage and slower processing.

This example provides a simple reference for using chunked processing and alternative storage formats to improve scalability and performance.

Expected Benefit

• Helps users work with large datasets more efficiently
• Demonstrates scalable data handling techniques
• Improves usability for real-world weather data scenarios

Note

This PR does not modify any core functionality and only adds an example and documentation.