Move weekly forecast above the comparison table; timestamps into hero

- Lead with the forecast itself: hero → weekly chart → 24h same-hour
table → radar → scoreboard → accordions. The reader sees the live
forecast first, then the side-by-side detail.
- Hero table grows a 'When' column: each row carries its own timestamp
('2:02 PM EDT, Mon May 11' for Ecowitt, '2 PM EDT, Mon May 11' for
the NWS hour). Drops the standalone 'Last Ecowitt reading…' caption
since the same info is now in the table.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

app.py

@@ -429,6 +429,8 @@ with gr.Blocks(title="Toto Weather Forecast", theme=gr.themes.Soft()) as demo:
     gr.Markdown(SUBTITLE)
 
     hero_md = gr.Markdown()
+    gr.Markdown(f"### 📅 {VIEW_WEEK['label']}")
+    week_plot = gr.Plot(label="Weekly")
     comparison_md = gr.Markdown()
     gr.HTML(
         # KOKX is the NWS radar site at Upton, NY — covers Long Island incl.
@@ -450,9 +452,6 @@ with gr.Blocks(title="Toto Weather Forecast", theme=gr.themes.Soft()) as demo:
         "<span style='opacity:0.55'>🔄 Live data + forecast auto-refresh every 15 minutes.</span>"
     )
 
-    gr.Markdown(f"### 📅 {VIEW_WEEK['label']}")
-    week_plot = gr.Plot(label="Weekly")
-
     gr.Markdown("### 🏆 How has each model done so far?")
     scoreboard_md = gr.Markdown()
     residual_plot = gr.Plot(label="Forecast residual")

src/weather_ui.py

@@ -85,17 +85,16 @@ def hero_markdown(
     if cur_temp is None or when_ts is None:
         return "_(no current readings yet)_"
 
-    when = when_ts.tz_convert(tz).strftime("%-I:%M %p %Z on %a %b %-d")
+    eco_when = when_ts.tz_convert(tz).strftime("%-I:%M %p %Z, %a %b %-d")
 
     nws_temp_str = "—"
-    nws_short = ""
+    nws_when = "—"
     glyph = "🌡"
     gap_str = ""
-    nws_hour_label = "this hour"
     if nws_first is not None and not nws_first.empty:
         idx0 = nws_first.index[0] if isinstance(nws_first, pd.DataFrame) else nws_first.name
         if isinstance(idx0, pd.Timestamp):
-            nws_hour_label = idx0.tz_convert(tz).strftime("%-I %p %Z")
+            nws_when = idx0.tz_convert(tz).strftime("%-I %p %Z, %a %b %-d")
         row = nws_first.iloc[0] if isinstance(nws_first, pd.DataFrame) else nws_first
         if isinstance(row, pd.Series):
             if "temp_f" in row and pd.notna(row["temp_f"]):
@@ -104,20 +103,15 @@ def hero_markdown(
                 sign = "+" if gap >= 0 else ""
                 gap_str = f" <span style='opacity:0.55'>(NWS off by {sign}{gap:.1f}°F)</span>"
             if "short_forecast" in row:
-                nws_short = str(row["short_forecast"])
-                glyph = emoji_for(nws_short)
+                glyph = emoji_for(str(row["short_forecast"]))
 
     table = (
-        "| Source | Temperature |\n"
-        "|---|---|\n"
-        f"| 📡 Ecowitt (measured) | **{cur_temp:.1f}°F** |\n"
-        f"| 🌎 NWS forecast for {nws_hour_label} | {nws_temp_str}{gap_str} |"
-    )
-    return (
-        f"### {glyph} {place}\n\n"
-        f"{table}\n\n"
-        f"<span style='opacity:0.55'>Last Ecowitt reading at {when}</span>"
+        "| Source | Temperature | When |\n"
+        "|---|---|---|\n"
+        f"| 📡 Ecowitt (measured) | **{cur_temp:.1f}°F** | {eco_when} |\n"
+        f"| 🌎 NWS forecast | {nws_temp_str}{gap_str} | {nws_when} |"
     )
+    return f"### {glyph} {place}\n\n{table}"
 
 
 def aligned_comparison_markdown(