Update docs/community/contributing-emulators.md

Co-authored-by: Sophie Arana <[email protected]>

Author: mastoffel

docs/community/contributing-emulators.md

@@ -6,6 +6,7 @@ This guide explains how to contribute new emulator models to `AutoEmulate`.
 
 All emulators in AutoEmulate are implemented as `scikit-learn` estimators, making them compatible with scikit-learn's cross-validation, grid-search, and pipeline functionality. Have a look at the [scikit-learn estimator developer guide](https://scikit-learn.org/1.5/developers/develop.html#rolling-your-own-estimator) for more details on how to implement a new estimator.
 
+**Note**: AutoEmulate is designed primarily for static data analysis, leveraging its integration with scikit-learn. If you are contributing an emulator for time-series data, keep in mind that it may not perform optimally without additional handling of temporal dependencies, particularly during cross-validation and evaluation.
 ### Core Requirements
 
 Each emulator class must: