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Pangu TC Adapter
================

Overview
--------

``pangu_tc`` adds a second foundation-weather reference path behind the shared tropical-cyclone evaluator.

At a Glance
-----------

.. grid:: 1 2 4 4
   :gutter: 2
   :class-container: catalog-grid

   .. grid-item-card:: Hazard Family
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         Tropical Cyclone

      .. container:: catalog-stat-note

         Public catalog grouping used for this model.

   .. grid-item-card:: Maturity
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         Experimental Adapter

      .. container:: catalog-stat-note

         Catalog maturity label used on the index page.

   .. grid-item-card:: Tasks
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         1

      .. container:: catalog-stat-note

         Track + Intensity

   .. grid-item-card:: Benchmark Family
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         :doc:`Tropical Cyclone Benchmark </benchmarks/tropical_cyclone_benchmark>`

      .. container:: catalog-stat-note

         Primary benchmark-family link used for compatible evaluation coverage.


Description
-----------

``pangu_tc`` adds a second foundation-weather reference path behind the shared tropical-cyclone evaluator.

The implementation is intentionally lightweight and should be interpreted as an adapter contract for forecast-field driven storm evaluation.

Benchmark Compatibility
-----------------------

**Primary benchmark family:** :doc:`Tropical Cyclone Benchmark </benchmarks/tropical_cyclone_benchmark>`

**Mapped benchmark ecosystems:** :doc:`IBTrACS </benchmarks/ibtracs>`

External References
-------------------

**Paper:** `Accurate medium-range global weather forecasting with 3D neural networks <https://www.nature.com/articles/s41586-023-06185-3>`_ | **Repo:** `Repository <https://github.com/198808xc/Pangu-Weather>`__

Registry Name
-------------

Primary entrypoint: ``pangu_tc``

Supported Tasks
---------------

- Track + Intensity

Programmatic Use
----------------

.. code-block:: python

   import torch
   from pyhazards.models import build_model

   model = build_model(name="pangu_tc", task="regression", input_dim=8, horizon=5)
   preds = model(torch.randn(2, 6, 8))
   print(preds.shape)

Notes
-----

- Experimental adapter: intended for shared-evaluator prototyping rather than exact weather-model parity.