diff --git a/src/weathergen/utils/plot_training.py b/src/weathergen/utils/plot_training.py
index 5e5f9478e..1b5154a1d 100644
--- a/src/weathergen/utils/plot_training.py
+++ b/src/weathergen/utils/plot_training.py
@@ -21,7 +21,7 @@
 
 import weathergen.common.config as config
 from weathergen.train.utils import TRAIN
-from weathergen.utils.train_logger import Metrics, TrainLogger
+from weathergen.utils.train_logger import Metrics, TrainLogger, sanitize_channel_for_matching
 
 _logger = logging.getLogger(__name__)
 
@@ -420,8 +420,17 @@ def plot_loss_per_stream(
     prop_cycle = plt.rcParams["axes.prop_cycle"]
     colors = prop_cycle.by_key()["color"] + ["r", "g", "b", "k", "m", "y"]
 
+    if channels is not None:
+        channels_sanitized = [sanitize_channel_for_matching(c) for c in channels]
+    else:
+        channels_sanitized = channels
+
     for err in errs:
-        for channel in channels:
+        channels_to_use = channels if channels else [None]
+        channels_sanitized_to_use = channels_sanitized if channels_sanitized else [None]
+        for channel, channel_sanitized in zip(
+            channels_to_use, channels_sanitized_to_use, strict=True
+        ):
             for stream_name in stream_names:
                 _fig = plt.figure(figsize=(10, 7), dpi=PLOT_DPI_VALUE)
 
@@ -456,7 +465,7 @@ def plot_loss_per_stream(
                                 if (
                                     col_split[1].lower() == stream_name.lower()
                                     and col_split[2].lower() == err.lower()
-                                    and col_split[3] == channel
+                                    and col_split[3] == channel_sanitized
                                 ):
                                     data_cols += [col]
                                     title_col = col if title_col is None else title_col
@@ -464,7 +473,7 @@ def plot_loss_per_stream(
                                 if (
                                     col_split[1].lower() == stream_name.lower()
                                     and col_split[2].lower() == err.lower()
-                                    and col_split[3] == channel
+                                    and col_split[3] == channel_sanitized
                                     and int(col_split[4]) in forecast_steps
                                 ):
                                     data_cols += [col]
@@ -603,6 +612,11 @@ def plot_loss_per_run(
     if errs is None:
         errs = ["mse"]
 
+    if channels is not None:
+        channels_sanitized = [sanitize_channel_for_matching(c) for c in channels]
+    else:
+        channels_sanitized = channels
+
     plot_dir = Path(plot_dir)
 
     modes = [modes] if type(modes) is not list else modes
@@ -631,7 +645,7 @@ def plot_loss_per_run(
                 if (
                     len(col_split) >= 4
                     and col_split[2].lower() == err.lower()
-                    and col_split[3] in channels
+                    and col_split[3] in channels_sanitized
                 ):
                     data_cols += [col]
 
diff --git a/src/weathergen/utils/train_logger.py b/src/weathergen/utils/train_logger.py
index d7501a1cd..4d958f412 100644
--- a/src/weathergen/utils/train_logger.py
+++ b/src/weathergen/utils/train_logger.py
@@ -194,6 +194,10 @@ def read_metrics(
     # TODO: this should be a config option
     df = read_metrics_file(metrics_path)
 
+    # Sanitize LossPhysical column names to replace dots in channel names with underscores
+    new_columns = {col: sanitize_loss_physical_column(col) for col in df.columns}
+    df = df.rename(new_columns)
+
     if cols_patterns is not None:
         for col_pattern in cols_patterns:
             cols += [col for col in df.columns if col_pattern in col]
@@ -269,6 +273,38 @@ def _key_stddev(st_name: str) -> str:
     return f"stream.{st_name}.stddev_avg"
 
 
+def sanitize_loss_physical_column(col: str) -> str:
+    """Replace dots in channel names with underscores for LossPhysical columns.
+
+    Adapts column names like:
+        LossPhysical.EERIE_OCEAN.mse.avg_thetao_2.5.0
+    to:
+        LossPhysical.EERIE_OCEAN.mse.avg_thetao_2_5.0
+
+    The format is: LossPhysical.{stream}.{error}.{channel}[.{forecast_step}]
+    """
+    if not col.startswith("LossPhysical."):
+        return col
+    parts = col.split(".")
+    if len(parts) < 4:
+        return col
+
+    if len(parts) > 4 and parts[-1].isdigit():
+        channel_parts = parts[3:-1]
+        forecast_step = parts[-1]
+        sanitized_channel = "_".join(channel_parts)
+        return f"LossPhysical.{parts[1]}.{parts[2]}.{sanitized_channel}.{forecast_step}"
+    else:
+        channel_parts = parts[3:]
+        sanitized_channel = "_".join(channel_parts)
+        return f"LossPhysical.{parts[1]}.{parts[2]}.{sanitized_channel}"
+
+
+def sanitize_channel_for_matching(channel: str) -> str:
+    """Replace dots with underscores for matching against sanitized column names."""
+    return channel.replace(".", "_")
+
+
 def prepare_losses_for_logging(
     loss_hist: list,
     losses_unweighted_hist: list[dict],