give up trying to make restructuredtext behave well with the readme, switched to markdown

Author: ray-chew

README.md

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+[![CSAM Logo](https://ray-chew.github.io/spec_appx/_static/logo.png)](https://ray-chew.github.io/spec_appx/index.html)
+
+<h2 align="center">Constrained Spectral Approximation Method</h2>
+
+
+<p align="center">
+<a href="https://github.com/ray-chew/spec_appx/actions/workflows/documentation.yml">
+<img alt="GitHub Actions: docs" src=https://github.com/ray-chew/spec_appx/actions/workflows/documentation.yml/badge.svg>
+</a>
+<a href="https://www.gnu.org/licenses/agpl-3.0">
+<img alt="License: GNU GPL v3" src=https://img.shields.io/badge/License-AGPL_v3-blue.svg>
+</a>
+<a href="https://github.com/psf/black">
+<img alt="Code style: black" src=https://img.shields.io/badge/code%20style-black-000000.svg>
+</a>
+</p>
+
+
+The Constrained Spectral Approximation Method (CSAM) is a physically sound and robust method for approximating the spectrum of subgrid-scale orography. It operates under the following constraints:
+
+* Utilises a limited number of spectral modes (no more than 100)
+* Significantly reduces the complexity of physical terrain by over 500 times
+* Maintains the integrity of physical information to a large extent
+* Compatible with unstructured geodesic grids
+* Inherently scale-aware
+
+This method is primarily used to represent terrain for weather forecasting purposes, but it also shows promise for broader data analysis applications.
+
+---
+
+**[Read the documentation here.](https://ray-chew.github.io/spec_appx/index.html)**
+
+---
+
+## Requirements
+
+See [`requirements.txt`](https://github.com/ray-chew/spec_appx/blob/main/requirements.txt)
+
+> **NOTE:**  The Sphinx dependencies can be found in [`docs/conf.py`](https://github.com/ray-chew/spec_appx/blob/main/docs/source/conf.py).
+
+
+## Usage
+
+### Installation
+
+Make a fork and clone your remote forked repository.
+
+### Configuration
+
+The user-defined input parameters are in the [`inputs`](https://github.com/ray-chew/spec_appx/tree/main/inputs) subpackage. These parameters are imported into the run scripts in [`runs`](https://github.com/ray-chew/spec_appx/tree/main/runs). 
+
+### Execution
+
+A simple setup can be found in [`runs.idealised_isosceles`](https://github.com/ray-chew/spec_appx/blob/main/runs/idealised_isosceles.py). To execute this run script:
+
+```console
+python3 ./runs/idealised_isosceles.py
+```
+
+However, the codebase is structured such that the user can easily assemble a run script to define their own experiments. Refer to the documentation for the available APIs.
+
+## License
+
+GNU GPL v3 (tentative)
+
+## Contributions
+
+Refer to the open issues that require attention.
+
+Any changes, improvements, or bug fixes can be submitted to upstream via a pull request.
+