Issue 2521 emit warning

src/parcels/_core/spatialhash.py

@@ -1,3 +1,5 @@
+import warnings
+
 import numpy as np
 
 from parcels._core.index_search import (
@@ -6,6 +8,7 @@
     curvilinear_point_in_cell,
     uxgrid_point_in_cell,
 )
+from parcels._core.warnings import FieldSetWarning
 from parcels._python import isinstance_noimport
 
 
@@ -88,6 +91,17 @@ def __init__(
                 self._zlow = np.min(_zbound, axis=-1)
                 self._zhigh = np.max(_zbound, axis=-1)
 
+                degeneracy_count = np.sum(_find_degenerate_xgrid_faces(x, y, z))
+                if degeneracy_count > 0:
+                    warnings.warn(
+                        f"Grid contains {degeneracy_count} degenerate faces that span a large portion of the "
+                        "hash grid. This is most likely due to a mesh that isn't fully defined (e.g., cells corresponding to land areas aren't defined in the mesh).
+                        If particles are tried to be advected in these undefined regions, you may experience runtime
+                        crashes due to high memory usage in the hash table.",
+                        FieldSetWarning,
+                        stacklevel=2,
+                    )
+
             else:
                 # Boundaries of the hash grid are the bounding box of the source grid
                 self._xmin = self._source_grid.lon.min()
@@ -483,6 +497,53 @@ def _dilate_bits(n):
     return n
 
 
+def _find_degenerate_xgrid_faces(x, y, z, threshold_factor=10):
+    """Identify faces in structured grids that potentially span large portions of
+    the underlying hash grid (e.g., due to the mesh being incomplete, with 0.0 stored in missing lon/lat points). Such degenerate faces can result in high memory requirements
+    for the hash table.
+
+    Detection is based on the maximum great-circle edge length of each cell.  A cell
+    is flagged as degenerate when its longest edge exceeds ``threshold_factor`` multiplied by
+    the 99th percentile of all edge lengths.
+
+    Parameters
+    ----------
+    x, y, z : ndarray, shape (ny, nx)
+        Unit-sphere Cartesian coordinates of the grid nodes.
+    threshold_factor : float, optional
+        Multiplier applied to the 99th-percentile edge length to set the threshold.
+        Default is 10.
+
+    Returns
+    -------
+    degenerate : ndarray of bool, shape (ny-1, nx-1)
+        True for each cell whose maximum edge length exceeds the threshold.
+    """
+
+    # Chord length between two sets of points on the unit sphere, shape (ny-1, nx-1)
+    def _chord(p1, p2):
+        return np.sqrt(((p1 - p2) ** 2).sum(axis=-1))
+
+    pts = np.stack([x, y, z], axis=-1)
+    c00, c01 = pts[:-1, :-1], pts[:-1, 1:]
+    c10, c11 = pts[1:, :-1], pts[1:, 1:]
+
+    # Maximum chord across all four edges and both diagonals
+    max_chord = np.maximum.reduce(
+        [
+            _chord(c00, c01),
+            _chord(c10, c11),
+            _chord(c00, c10),
+            _chord(c01, c11),
+            _chord(c00, c11),
+            _chord(c01, c10),
+        ]
+    )
+
+    threshold = threshold_factor * np.percentile(max_chord, 99)
+    return max_chord > threshold
+
+
 def quantize_coordinates(x, y, z, xmin, xmax, ymin, ymax, zmin, zmax, bitwidth=1023):
     """
     Normalize (x, y, z) to [0, 1] over their bounding box, then quantize to 10 bits each (0..1023).