diff --git a/ensemble/ensemble.py b/ensemble/ensemble.py
index 9d8b5c5..b862272 100644
--- a/ensemble/ensemble.py
+++ b/ensemble/ensemble.py
@@ -260,7 +260,7 @@ def calc_prediction(self, enX=None, save_prediction=None):
                 en_pred = []
                 pbar = tqdm(enumerate(enX), total=self.ne, **progbar_settings)
                 for member_index, state in pbar:
-                    en_pred.append(self.sim.run_fwd_sim(state, member_index))
+                    en_pred.append(deepcopy(self.sim.run_fwd_sim(state, member_index)))
             
             # Parallelization on HPC using SLURM
             elif self.sim.input_dict.get('hpc', False): # Run prediction in parallel on hpc
diff --git a/pipt/loop/assimilation.py b/pipt/loop/assimilation.py
index 9266a45..8326ba9 100644
--- a/pipt/loop/assimilation.py
+++ b/pipt/loop/assimilation.py
@@ -217,11 +217,11 @@ def run(self):
         # always store posterior forcast and state, unless specifically told not to
         if 'nosave' not in self.ensemble.keys_da:
             try: # first try to save as npz file
-                np.savez(f'{self.save_folder}/posterior_state_estimate.npz', **self.ensemble.enX)
+                np.savez(f'{self.save_folder}/posterior_state_estimate.npz', **entools.matrix_to_dict(self.ensemble.enX, self.ensemble.idX))
                 np.savez(f'{self.save_folder}/posterior_forecast.npz', **{'pred_data': self.ensemble.pred_data})
             except: # If this fails, store as pickle
                 with open(f'{self.save_folder}/posterior_state_estimate.p', 'wb') as file:
-                    pickle.dump(self.ensemble.enX, file)
+                    pickle.dump(entools.matrix_to_dict(self.ensemble.enX, self.ensemble.idX), file)
                 with open(f'{self.save_folder}/posterior_forecast.p', 'wb') as file:
                     pickle.dump(self.ensemble.pred_data, file)