diff --git a/packages/evaluate/src/weathergen/evaluate/plotting/plotter.py b/packages/evaluate/src/weathergen/evaluate/plotting/plotter.py
index 44ec60a3b..e3cdfefa6 100644
--- a/packages/evaluate/src/weathergen/evaluate/plotting/plotter.py
+++ b/packages/evaluate/src/weathergen/evaluate/plotting/plotter.py
@@ -607,7 +607,7 @@ def animation(self, samples, fsteps, variables, select, tag) -> list[str]:
                         image_paths += names
 
                     if image_paths:
-                        image_paths=sorted(image_paths)
+                        image_paths = sorted(image_paths)
                         images = [Image.open(path) for path in image_paths]
                         images[0].save(
                             f"{map_output_dir}/animation_{self.run_id}_{tag}_{sa}_{self.stream}_{region}_{var}.gif",
diff --git a/packages/evaluate/src/weathergen/evaluate/scores/score.py b/packages/evaluate/src/weathergen/evaluate/scores/score.py
index ab322ab28..c5d4cf8d0 100755
--- a/packages/evaluate/src/weathergen/evaluate/scores/score.py
+++ b/packages/evaluate/src/weathergen/evaluate/scores/score.py
@@ -190,6 +190,7 @@ def __init__(
             "grad_amplitude": self.calc_spatial_variability,
             "psnr": self.calc_psnr,
             "seeps": self.calc_seeps,
+            "nse": self.calc_nse,
         }
         self.prob_metrics_dict = {
             "ssr": self.calc_ssr,
@@ -1199,6 +1200,34 @@ def seeps(ground_truth, prediction, thr_light, thr_heavy, seeps_weights):
 
         return seeps_values
 
+    def calc_nse(self, p: xr.DataArray, gt: xr.DataArray) -> xr.DataArray:
+        """
+        Calculate Nash–Sutcliffe_model_efficiency_coefficient (NSE)
+        of forecast data vs reference data
+        Metrics broadly used in hydrology
+        Parameters
+        ----------
+        p: xr.DataArray
+            Forecast data array
+        gt: xr.DataArray
+            Ground truth data array
+        Returns
+        -------
+        xr.DataArray
+            Nash–Sutcliffe_model_efficiency_coefficient (NSE)
+
+        """
+
+        obs_mean = gt.mean(dim=self._agg_dims)
+
+        num = ((gt - p) ** 2).sum(dim=self._agg_dims)
+
+        den = ((gt - obs_mean) ** 2).sum(dim=self._agg_dims)
+
+        nse = 1 - num / den
+
+        return nse
+
     ### Probablistic scores
 
     def calc_spread(self, p: xr.DataArray, **kwargs) -> xr.DataArray:
diff --git a/src/weathergen/utils/cli.py b/src/weathergen/utils/cli.py
index 1c7cba6a8..2bd9fe2a2 100644
--- a/src/weathergen/utils/cli.py
+++ b/src/weathergen/utils/cli.py
@@ -14,7 +14,7 @@ class Stage(enum.StrEnum):
 def get_main_parser() -> argparse.ArgumentParser:
     parser = argparse.ArgumentParser(allow_abbrev=False)
     subparsers = parser.add_subparsers(dest="stage")
-    
+
     train_parser = subparsers.add_parser(
         Stage.train,
         help="Train a WeatherGenerator configuration from the ground up.",