Add precipitation/wind/humidity maps; fix titles to clarify input vs forecast

app.py

@@ -15,6 +15,9 @@ from model_utils import run_forecast, load_model, AVAILABLE_MODELS
 from visualization import (
     get_static_maps,
     plot_temperature,
+    plot_precipitation,
+    plot_wind_speed,
+    plot_humidity,
 )
 
 logging.basicConfig(level=logging.INFO)
@@ -267,9 +270,12 @@ def do_forecast(model_display: str, progress=gr.Progress()):
     model_label = model_display.split("(")[0].strip()
     hero = _hero_html(r, cycle_str, forecast_str, model_label)
     temp_fig = plot_temperature(input_array, r, cycle_str, forecast_str)
+    precip_fig = plot_precipitation(input_array, r, cycle_str, forecast_str)
+    wind_fig = plot_wind_speed(input_array, r, cycle_str, forecast_str)
+    humid_fig = plot_humidity(input_array, r, cycle_str, forecast_str)
     status = f"Forecast complete — HRRR cycle {cycle_str}"
 
-    return hero, sat_fig, street_fig, temp_fig, status
+    return hero, sat_fig, street_fig, temp_fig, precip_fig, wind_fig, humid_fig, status
 
 
 # ── Build UI ──────────────────────────────────────────────────────────
@@ -324,6 +330,22 @@ with gr.Blocks(title="Tufts Jumbo Weather Forecast", css=CUSTOM_CSS) as demo:
             elem_classes=["map-cell"],
         )
 
+    gr.HTML('<div class="maps-heading">Current Input Fields &ensp; with 24 h Forecast at Jumbo</div>')
+
+    with gr.Row(equal_height=True):
+        precip_plot = gr.Plot(
+            label="Precipitation",
+            elem_classes=["map-cell"],
+        )
+        wind_plot = gr.Plot(
+            label="Wind Speed",
+            elem_classes=["map-cell"],
+        )
+        humid_plot = gr.Plot(
+            label="Humidity",
+            elem_classes=["map-cell"],
+        )
+
     # ── About ─────────────────────────────────────────────────────
     with gr.Accordion("About this demo", open=False):
         gr.Markdown(
@@ -340,7 +362,8 @@ with gr.Blocks(title="Tufts Jumbo Weather Forecast", css=CUSTOM_CSS) as demo:
     run_btn.click(
         fn=do_forecast,
         inputs=[model_dd],
-        outputs=[hero_html, sat_plot, street_plot, temp_plot, status_bar],
+        outputs=[hero_html, sat_plot, street_plot, temp_plot,
+                 precip_plot, wind_plot, humid_plot, status_bar],
     )
 
 

visualization.py

@@ -176,7 +176,7 @@ def plot_temperature(
 
     temp_c = forecast["temperature_c"]
     temp_f = forecast["temperature_f"]
-    label = f"Forecast {forecast_str}\n{temp_c:+.1f} °C  /  {temp_f:.0f} °F"
+    label = f"24h Forecast: {forecast_str}\n{temp_c:+.1f} °C  /  {temp_f:.0f} °F"
     ax.text(
         JUMBO_LON + 0.45, JUMBO_LAT + 0.35, label,
         fontsize=8.5, fontweight="bold", fontfamily="sans-serif",
@@ -185,7 +185,142 @@ def plot_temperature(
     )
 
     ax.set_title(
-        f"2 m Temperature — {cycle_str}",
+        f"Current 2 m Temperature (Input) — {cycle_str}",
+        fontsize=12, fontweight="600",
+        fontfamily="sans-serif", pad=8, color="#1D1D1F",
+    )
+    fig.subplots_adjust(left=0.02, right=0.95, bottom=0.02, top=0.93)
+    return fig
+
+
+def plot_precipitation(
+    input_array: np.ndarray,
+    forecast: dict,
+    cycle_str: str,
+    forecast_str: str,
+) -> Figure:
+    """Render 1-hour accumulated precipitation map with forecast annotation."""
+    fig, ax = _make_ax()
+
+    precip_field = input_array[:, :, 6]  # APCP_1hr_acc_fcst@surface (mm)
+    masked = np.ma.masked_invalid(precip_field)
+
+    im = ax.pcolormesh(
+        X_GRID, Y_GRID, masked,
+        cmap="YlGnBu", shading="auto", transform=PROJ, zorder=5,
+        vmin=0, vmax=10,
+    )
+    ax.add_feature(cfeature.COASTLINE, linewidth=0.5, color="#444", zorder=10)
+    ax.add_feature(cfeature.STATES, linewidth=0.3, edgecolor="#666", zorder=10)
+
+    cbar = fig.colorbar(im, ax=ax, shrink=0.72, pad=0.03, aspect=28)
+    cbar.set_label("mm", fontsize=10, fontfamily="sans-serif")
+    cbar.ax.tick_params(labelsize=8)
+
+    ax.plot(JUMBO_LON, JUMBO_LAT, **_MARKER)
+
+    precip = forecast["precipitation_mm"]
+    label = f"24h Forecast: {forecast_str}\n{precip:.2f} mm — {forecast['rain_status']}"
+    ax.text(
+        JUMBO_LON + 0.45, JUMBO_LAT + 0.35, label,
+        fontsize=8.5, fontweight="bold", fontfamily="sans-serif",
+        color="white", transform=ccrs.PlateCarree(), zorder=25,
+        bbox=dict(boxstyle="round,pad=0.35", fc="#1C1C1E", ec="white", alpha=0.88, lw=0.8),
+    )
+
+    ax.set_title(
+        f"Current Precipitation (Input) — {cycle_str}",
+        fontsize=12, fontweight="600",
+        fontfamily="sans-serif", pad=8, color="#1D1D1F",
+    )
+    fig.subplots_adjust(left=0.02, right=0.95, bottom=0.02, top=0.93)
+    return fig
+
+
+def plot_wind_speed(
+    input_array: np.ndarray,
+    forecast: dict,
+    cycle_str: str,
+    forecast_str: str,
+) -> Figure:
+    """Render 10 m wind speed map with forecast annotation."""
+    fig, ax = _make_ax()
+
+    u = input_array[:, :, 2]   # UGRD@10m (m/s)
+    v = input_array[:, :, 3]   # VGRD@10m (m/s)
+    speed_field = np.sqrt(u**2 + v**2)
+    masked = np.ma.masked_invalid(speed_field)
+
+    im = ax.pcolormesh(
+        X_GRID, Y_GRID, masked,
+        cmap="viridis", shading="auto", transform=PROJ, zorder=5,
+        vmin=0, vmax=20,
+    )
+    ax.add_feature(cfeature.COASTLINE, linewidth=0.5, color="#444", zorder=10)
+    ax.add_feature(cfeature.STATES, linewidth=0.3, edgecolor="#666", zorder=10)
+
+    cbar = fig.colorbar(im, ax=ax, shrink=0.72, pad=0.03, aspect=28)
+    cbar.set_label("m/s", fontsize=10, fontfamily="sans-serif")
+    cbar.ax.tick_params(labelsize=8)
+
+    ax.plot(JUMBO_LON, JUMBO_LAT, **_MARKER)
+
+    ws = forecast["wind_speed_ms"]
+    wd = forecast["wind_dir_str"]
+    label = f"24h Forecast: {forecast_str}\n{ws:.1f} m/s from {wd}"
+    ax.text(
+        JUMBO_LON + 0.45, JUMBO_LAT + 0.35, label,
+        fontsize=8.5, fontweight="bold", fontfamily="sans-serif",
+        color="white", transform=ccrs.PlateCarree(), zorder=25,
+        bbox=dict(boxstyle="round,pad=0.35", fc="#1C1C1E", ec="white", alpha=0.88, lw=0.8),
+    )
+
+    ax.set_title(
+        f"Current 10 m Wind Speed (Input) — {cycle_str}",
+        fontsize=12, fontweight="600",
+        fontfamily="sans-serif", pad=8, color="#1D1D1F",
+    )
+    fig.subplots_adjust(left=0.02, right=0.95, bottom=0.02, top=0.93)
+    return fig
+
+
+def plot_humidity(
+    input_array: np.ndarray,
+    forecast: dict,
+    cycle_str: str,
+    forecast_str: str,
+) -> Figure:
+    """Render 2 m relative humidity map with forecast annotation."""
+    fig, ax = _make_ax()
+
+    rh_field = input_array[:, :, 1]  # RH@2m_above_ground (%)
+    masked = np.ma.masked_invalid(rh_field)
+
+    im = ax.pcolormesh(
+        X_GRID, Y_GRID, masked,
+        cmap="BrBG", shading="auto", transform=PROJ, zorder=5,
+        vmin=0, vmax=100,
+    )
+    ax.add_feature(cfeature.COASTLINE, linewidth=0.5, color="#444", zorder=10)
+    ax.add_feature(cfeature.STATES, linewidth=0.3, edgecolor="#666", zorder=10)
+
+    cbar = fig.colorbar(im, ax=ax, shrink=0.72, pad=0.03, aspect=28)
+    cbar.set_label("%", fontsize=10, fontfamily="sans-serif")
+    cbar.ax.tick_params(labelsize=8)
+
+    ax.plot(JUMBO_LON, JUMBO_LAT, **_MARKER)
+
+    rh = forecast["humidity_pct"]
+    label = f"24h Forecast: {forecast_str}\n{rh:.0f}%"
+    ax.text(
+        JUMBO_LON + 0.45, JUMBO_LAT + 0.35, label,
+        fontsize=8.5, fontweight="bold", fontfamily="sans-serif",
+        color="white", transform=ccrs.PlateCarree(), zorder=25,
+        bbox=dict(boxstyle="round,pad=0.35", fc="#1C1C1E", ec="white", alpha=0.88, lw=0.8),
+    )
+
+    ax.set_title(
+        f"Current 2 m Humidity (Input) — {cycle_str}",
         fontsize=12, fontweight="600",
         fontfamily="sans-serif", pad=8, color="#1D1D1F",
     )