update config and script

hiro_downscaling_ace2s_global_output.yaml

@@ -12,7 +12,7 @@ data:
   coarse:
   - data_path: /output_directory
     engine: zarr
-    file_pattern: output_6hourly_predictions_ic0000.zarr
+    file_pattern: output_6hourly_ace2s_predictions_ic0000.zarr
   batch_size: 4
   num_data_workers: 2
   strict_ensemble: False
@@ -21,9 +21,10 @@ outputs:
   save_vars: ["PRATEsfc"]
   n_ens: 1
   max_samples_per_gpu: 32
+  # Note: for reference, 1 year of global 3km outputs is ~300 Gb per ensemble member
   time_range:
     start_time: "2023-01-01T00:00:00"
-    stop_time: "2023-12-31T18:00:00"
+    stop_time: "2023-01-08T00:00:00"
   lat_extent:
     start: -66.0
     stop: 70.0

run-hiro-ace.sh

@@ -19,4 +19,5 @@ python -m fme.ace.inference ace2s_inference_config_global.yaml
 # for faster through put more GPUs may be required
 NGPU=1
 
-torchrun --nproc_per_node $NGPU -m fme.downscaling.inference hiro_downscaling_ace2s_global_output.yaml
+# This will downscale a subselected region around the Pacific Northwest. 
+torchrun --nproc_per_node $NGPU -m fme.downscaling.inference hiro_downscaling_ace2s_pnw_output.yaml