diff --git a/src/qp/metrics/pit.py b/src/qp/metrics/pit.py
index 9f6b1f8..e6c3bd9 100644
--- a/src/qp/metrics/pit.py
+++ b/src/qp/metrics/pit.py
@@ -46,6 +46,14 @@ def __init__(self, qp_ens, true_vals, eval_grid=DEFAULT_QUANTS):
         # For each distribution in the Ensemble, calculate the CDF where x = known_true_value
         self._pit_samps = np.array([qp_ens[i].cdf(self._true_vals[i])[0][0] for i in range(len(self._true_vals))])
 
+        # These two lines set all `NaN` values to 0. This may or may not make sense
+        # Alternatively if it's better to simply remove the `NaN`, this can be done
+        # efficiently on line 61 with `data_quants = np.nanquantile(...)`.`
+        samp_mask = np.isfinite(self._pit_samps)
+        self._pit_samps[~samp_mask] = 0
+        if not np.all(samp_mask):
+            logging.warning('Some PIT samples were `NaN`. They have been replacd with 0.')
+
         n_pit = np.min([len(self._pit_samps), len(eval_grid)])
         if n_pit < len(eval_grid):
             logging.warning('Number of pit samples is smaller than the evaluation grid size. '