diff --git a/config/streams/era5_1deg_forecasting/era5.yml b/config/streams/era5_1deg_forecasting/era5.yml
index ae8e2da53..fce350a59 100644
--- a/config/streams/era5_1deg_forecasting/era5.yml
+++ b/config/streams/era5_1deg_forecasting/era5.yml
@@ -13,7 +13,7 @@ ERA5 :
   stream_id : 0
   source_exclude : ['w_', 'skt', 'tcw', 'cp', 'tp']
   target_exclude : ['w_', 'slor', 'sdor', 'tcw', 'cp', 'tp']
-  geoinfo_channels : ['lsm', 'slor', 'sdor', 'insolation', 'cos_local_time', 'sin_local_time', 'cos_julian_day', 'sin_julian_day']
+  # geoinfo_channels : ['lsm', 'slor', 'sdor', 'insolation', 'cos_local_time', 'sin_local_time', 'cos_julian_day', 'sin_julian_day']
   loss_weight : 1.
   location_weight : cosine_latitude
   masking_rate : 0.6
diff --git a/src/weathergen/train/loss_modules/loss_module_latent_diffusion.py b/src/weathergen/train/loss_modules/loss_module_latent_diffusion.py
index a89c9d6b8..0918c1732 100644
--- a/src/weathergen/train/loss_modules/loss_module_latent_diffusion.py
+++ b/src/weathergen/train/loss_modules/loss_module_latent_diffusion.py
@@ -94,8 +94,9 @@ def compute_loss(self, preds: dict, targets: dict, **kwargs) -> LossValues:
             for _, _, loss_fct_name in self.loss_fcts
         }
 
-        pred_tokens_all = [pl["latent_state"].z_pre_norm for pl in preds.latent if pl]
+        pred_tokens_all = [pl["latent_state"].z_pre_norm for pl in preds.latent if ("latent_state" in pl)]
         target_tokens_all = [latent["diffusion_latent"] for latent in targets.latent if latent]
+        assert len(pred_tokens_all) == len(target_tokens_all), "Mismatch between predicted and target token lengths"
 
         eta = torch.tensor(
             [targets.aux_outputs["noise_level_rn"]], device=self.device, dtype=torch.float32
diff --git a/src/weathergen/train/trainer.py b/src/weathergen/train/trainer.py
index 25f62309f..26ed6af59 100644
--- a/src/weathergen/train/trainer.py
+++ b/src/weathergen/train/trainer.py
@@ -72,6 +72,9 @@ def _expand_targets_to_match_preds(preds, targets_and_auxs: dict) -> None:
     """
     n_pred = len(preds.physical)
     for t_aux in targets_and_auxs.values():
+        # if the first entry is None (e.g. when forecast_offset > 0), then remove it
+        if not t_aux.physical[0]:
+            t_aux.physical = t_aux.physical[1:]
         n_tgt = len(t_aux.physical)
         if n_tgt == n_pred or n_tgt == 0:
             continue
diff --git a/src/weathergen/utils/validation_io.py b/src/weathergen/utils/validation_io.py
index e6bbebe8d..45ea832b7 100644
--- a/src/weathergen/utils/validation_io.py
+++ b/src/weathergen/utils/validation_io.py
@@ -63,6 +63,8 @@ def write_output(
 
     # TODO Maybe stopping at forecast_steps explained #1657
     for t_idx in timestep_idxs:
+        if cf.training_config.forecast.offset == 1:
+            t_idx = t_idx - 1
         preds_all += [[]]
         targets_all += [[]]
         targets_coords_all += [[]]