diff --git a/chasemapper/__init__.py b/chasemapper/__init__.py
index b8a7fc2..7640920 100644
--- a/chasemapper/__init__.py
+++ b/chasemapper/__init__.py
@@ -8,4 +8,4 @@
 
 # Now using Semantic Versioning (https://semver.org/)  MAJOR.MINOR.PATCH
 
-__version__ = "1.5.3"
+__version__ = "1.5.4"
diff --git a/horusmapper.cfg.example b/horusmapper.cfg.example
index b3a3d4b..045387e 100644
--- a/horusmapper.cfg.example
+++ b/horusmapper.cfg.example
@@ -149,6 +149,7 @@ ascent_rate_averaging = 10
 # GFS dataset already present and available. 
 # If you will be using the 'Download Model' button, then leave this at False, and Offline predictions
 # will be enabled once a valid model is available.
+# Downloading of a new model can also be triggered by running: curl http://localhost:5001/download_model
 offline_predictions = False
 
 # Predictory Binary Location
@@ -160,9 +161,9 @@ gfs_directory = ./gfs/
 
 # Wind Model Download Command
 # Optional command to enable downloading of wind data via a web client button.
-# Example: (this will require copying the get_wind_data.py script to this dirctory)
+# Example:
 # model_download = python3 -m cusfpredict.gfs --lat=-33 --lon=139 --latdelta=10 --londelta=10 -f 24 -m 0p50 -o gfs
-# The gfs directory (above) will be cleared of all .dat files prior to the above command being run.
+# The gfs directory (above) will be cleared of all data files once the new model is downloaded.
 model_download = none
 
 
diff --git a/horusmapper.py b/horusmapper.py
index e6c532f..4a9b35a 100644
--- a/horusmapper.py
+++ b/horusmapper.py
@@ -486,7 +486,8 @@ def run_prediction():
             current_payloads[_payload]["pred_path"] = []
             current_payloads[_payload]["pred_landing"] = []
             current_payloads[_payload]["burst"] = []
-            logging.error("Prediction Failed.")
+            logging.error("Prediction Failed, possible invalid or missing dataset.")
+            flask_emit_event("predictor_model_update", {"model": "Dataset invalid."})
 
         # Abort predictions
         if (
@@ -550,9 +551,10 @@ def run_prediction():
                     "Abort Prediction Updated, %d data points." % len(_pred_path)
                 )
             else:
-                logging.error("Prediction Failed.")
                 current_payloads[_payload]["abort_path"] = []
                 current_payloads[_payload]["abort_landing"] = []
+                logging.error("Prediction Failed, possible invalid or missing dataset.")
+                flask_emit_event("predictor_model_update", {"model": "Dataset invalid."})
         else:
             # Zero the abort path and landing
             current_payloads[_payload]["abort_path"] = []
@@ -678,6 +680,22 @@ def download_new_model(data):
         flask_emit_event("predictor_model_update", {"model": _status})
 
 
+@app.route("/download_model")
+def download_new_model_2():
+    """ Trigger a download of a new weather model via a GET request """
+    global pred_settings, model_download_running
+
+    logging.info("Web Client Initiated request for new predictor data via /download_model.")
+
+    if pred_settings["pred_model_download"] == "none":
+        logging.info("No GFS model download command specified.")
+        return "No model download cmd."
+    else:
+        _model_cmd = pred_settings["pred_model_download"]
+        _status = predictor_spawn_download(_model_cmd, model_download_finished)
+        return _status
+
+
 # Data Clearing Functions
 @socketio.on("payload_data_clear", namespace="/chasemapper")
 def clear_payload_data(data):