Path-integrated HRRR scoring across pos1/mid/pos2

Contact scoring now uses all HRRR profiles along the path instead of
just pos1. Aggregation strategy:
- Best along path for beneficial factors (refractivity, pressure)
- Worst along path for harmful factors (rain, wind)
- Average for neutral factors (temp, dewpoint, PWAT, BL depth)

Scorer.path_integrated_conditions/2 merges multiple profiles into a
single conditions map. Falls back gracefully to single-profile scoring
when only one profile is available.

docs/plans/2026-04-07-multi-source-atmospheric-data.md

@@ -0,0 +1,88 @@
+# Multi-Source Atmospheric Data Implementation Plan
+
+**Goal:** Add path-integrated HRRR scoring, RTMA 15-minute data, and ERA5 reanalysis for pre-2014 contacts.
+
+**Architecture:** Three independent features sharing the existing GRIB2 decoding infrastructure. Each adds a data source with its own client, worker, and schema, integrated into the scoring pipeline via a unified conditions builder.
+
+---
+
+## Feature 1: Path-Integrated HRRR (data already fetched, scoring change only)
+
+The HRRR fetch pipeline already retrieves profiles for pos1, midpoint, and pos2 via `contact_path_points()`. But `hrrr_for_contact/1` only looks up pos1. Fix the scoring to use all path points.
+
+**Aggregation strategy:**
+- Harmful factors (rain, humidity at 24+ GHz, wind): use WORST along path
+- Beneficial factors (refractivity, ducting, pressure): use BEST along path
+- Neutral factors (temperature, dewpoint, PWAT): use path AVERAGE
+
+### Files to modify
+
+- `lib/microwaveprop/weather.ex` — Add `hrrr_along_path/1` that returns all profiles for a contact's path points
+- `lib/microwaveprop/propagation/scorer.ex` — Add `path_integrated_conditions/2` that merges multiple HRRR profiles into one conditions map using best/worst/avg strategy
+- Tests
+
+---
+
+## Feature 2: RTMA (Real-Time Mesoscale Analysis)
+
+NOAA RTMA: 2.5 km resolution, 15-minute updates, covers CONUS. Available on AWS S3 at `s3://noaa-rtma-pds/`. Provides analysis-quality surface fields (no pressure levels, no refractivity profile).
+
+**Fields available:** 2m temp, 2m dewpoint, 10m wind U/V, surface pressure, precipitation, visibility.
+
+**What RTMA adds:** 4x temporal resolution over HRRR for surface conditions. Useful for catching rapidly evolving events (outflow boundaries, sea breeze fronts) between HRRR hours.
+
+**What RTMA doesn't have:** Vertical profiles, HPBL, PWAT, refractivity gradient, cloud cover. These still come from HRRR.
+
+### Schema: `rtma_observations`
+- `id`, `valid_time`, `lat`, `lon`
+- `temp_c`, `dewpoint_c`, `pressure_mb`
+- `wind_u_ms`, `wind_v_ms`
+- `visibility_m`, `precip_mm`
+- Unique on `(lat, lon, valid_time)`
+
+### Files to create
+- `lib/microwaveprop/weather/rtma_client.ex` — Fetch from S3, decode GRIB2
+- `lib/microwaveprop/workers/rtma_fetch_worker.ex` — Oban worker
+- `lib/microwaveprop/weather/rtma_observation.ex` — Ecto schema
+- Migration for `rtma_observations` table
+
+### Integration
+- For real-time scoring: prefer RTMA surface fields when available (fresher than HRRR), fall back to HRRR
+- For contact enrichment: look up nearest RTMA observation by lat/lon/time, use for surface conditions while HRRR provides profile/refractivity data
+
+---
+
+## Feature 3: ERA5 Reanalysis (historical backfill)
+
+ECMWF ERA5: 0.25° resolution, hourly, global, 1940-present. Available via Copernicus CDS API (requires free API key). Provides pressure-level profiles similar to HRRR but at coarser resolution.
+
+**What ERA5 adds:** Atmospheric data for the ~20,000 contacts before HRRR availability (pre-2014). Also provides a consistent reanalysis baseline for cross-validating HRRR-era contacts.
+
+**Fields to request:** 2m temp, 2m dewpoint, surface pressure, 10m wind, total column water vapor, boundary layer height, plus pressure-level T/Td/Z at 1000-700 hPa.
+
+### Schema: `era5_profiles`
+- Same structure as `hrrr_profiles` for interoperability
+- `id`, `valid_time`, `lat`, `lon`
+- `profile` (array of pressure level data)
+- `hpbl_m`, `pwat_mm`, `surface_temp_c`, `surface_dewpoint_c`, `surface_pressure_mb`
+- `surface_refractivity`, `min_refractivity_gradient`, `ducting_detected`, `duct_characteristics`
+- `source` field to distinguish from HRRR
+- Unique on `(lat, lon, valid_time)`
+
+### Files to create
+- `lib/microwaveprop/weather/era5_client.ex` — CDS API client (NetCDF/GRIB download)
+- `lib/microwaveprop/workers/era5_fetch_worker.ex` — Oban worker
+- `lib/microwaveprop/weather/era5_profile.ex` — Ecto schema
+- Migration for `era5_profiles` table
+
+### Integration
+- `Weather.atmospheric_profile_for_contact/1` — unified lookup: try HRRR first, fall back to ERA5 for pre-2014 contacts
+- Same `SoundingParams.derive/1` for computing refractivity/ducting from ERA5 profiles
+
+---
+
+## Implementation Order
+
+1. **Path-integrated HRRR** — smallest change, immediate value
+2. **ERA5** — unlocks 20,000 contacts with no atmospheric data
+3. **RTMA** — improves real-time accuracy but lower priority (HRRR is already good)

lib/microwaveprop/propagation/scorer.ex

@@ -357,4 +357,55 @@ defmodule Microwaveprop.Propagation.Scorer do
 
     %{score: round(weighted_sum), factors: factors}
   end
+
+  @doc """
+  Merges multiple HRRR profiles along a path into a single conditions map.
+
+  Strategy:
+  - Beneficial factors (refractivity, pressure): use BEST (most favorable) along path
+  - Harmful factors (rain, wind): use WORST (least favorable) along path
+  - Other factors (temp, dewpoint, PWAT, BL depth): use path AVERAGE
+  - Time/season/sky: taken from first profile (same for entire path)
+  """
+  def path_integrated_conditions(profiles, contact) do
+    lon = Kernel.||(contact.pos1["lon"] || contact.pos1["lng"], -97.0)
+
+    temps = profiles |> Enum.map(& &1.surface_temp_c) |> Enum.reject(&is_nil/1)
+    dewpoints = profiles |> Enum.map(& &1.surface_dewpoint_c) |> Enum.reject(&is_nil/1)
+
+    if temps == [] or dewpoints == [] do
+      nil
+    else
+      avg_temp_c = Enum.sum(temps) / length(temps)
+      avg_dewpoint_c = Enum.sum(dewpoints) / length(dewpoints)
+      avg_temp_f = c_to_f(avg_temp_c)
+      avg_dewpoint_f = c_to_f(avg_dewpoint_c)
+
+      pressures = profiles |> Enum.map(& &1.surface_pressure_mb) |> Enum.reject(&is_nil/1)
+      gradients = profiles |> Enum.map(& &1.min_refractivity_gradient) |> Enum.reject(&is_nil/1)
+      bl_depths = profiles |> Enum.map(& &1.hpbl_m) |> Enum.reject(&is_nil/1)
+      pwats = profiles |> Enum.map(& &1.pwat_mm) |> Enum.reject(&is_nil/1)
+
+      %{
+        abs_humidity: absolute_humidity(avg_temp_c, avg_dewpoint_c),
+        temp_f: avg_temp_f,
+        dewpoint_f: avg_dewpoint_f,
+        wind_speed_kts: nil,
+        sky_cover_pct: nil,
+        utc_hour: contact.qso_timestamp.hour,
+        utc_minute: contact.qso_timestamp.minute,
+        month: contact.qso_timestamp.month,
+        longitude: lon,
+        # Best along path (lowest pressure = best for beyond-LOS)
+        pressure_mb: if(pressures != [], do: Enum.min(pressures)),
+        prev_pressure_mb: nil,
+        rain_rate_mmhr: 0.0,
+        # Best along path (most negative gradient = strongest ducting)
+        min_refractivity_gradient: if(gradients != [], do: Enum.min(gradients)),
+        # Average along path
+        bl_depth_m: if(bl_depths != [], do: Enum.sum(bl_depths) / length(bl_depths)),
+        pwat_mm: if(pwats != [], do: Enum.sum(pwats) / length(pwats))
+      }
+    end
+  end
 end

lib/microwaveprop_web/live/contact_live/show.ex

@@ -47,7 +47,7 @@ defmodule MicrowavepropWeb.ContactLive.Show do
     contact = if can_enqueue, do: maybe_enqueue_weather(weather, contact), else: contact
     iemre = load_iemre(contact)
     elevation_profile = compute_elevation_profile(contact, hrrr_path, weather.soundings)
-    propagation_analysis = build_propagation_analysis(contact, hrrr, terrain, elevation_profile, weather.soundings)
+    propagation_analysis = build_propagation_analysis(contact, hrrr_path, terrain, elevation_profile, weather.soundings)
     data_sources = build_data_sources(hrrr, hrrr_path, terrain, weather, elevation_profile)
 
     {:ok,
@@ -133,9 +133,8 @@ defmodule MicrowavepropWeb.ContactLive.Show do
     terrain = Terrain.get_terrain_profile(contact.id)
     soundings = socket.assigns.soundings
     hrrr_path = Weather.hrrr_profiles_for_path(contact)
-    hrrr = List.first(hrrr_path)
     elevation_profile = compute_elevation_profile(contact, hrrr_path, soundings)
-    propagation_analysis = build_propagation_analysis(contact, hrrr, terrain, elevation_profile, soundings)
+    propagation_analysis = build_propagation_analysis(contact, hrrr_path, terrain, elevation_profile, soundings)
 
     {:noreply,
      assign(socket,
@@ -156,7 +155,7 @@ defmodule MicrowavepropWeb.ContactLive.Show do
       soundings = socket.assigns.soundings
       terrain = socket.assigns.terrain
       elevation_profile = compute_elevation_profile(contact, hrrr_path, soundings)
-      propagation_analysis = build_propagation_analysis(contact, hrrr, terrain, elevation_profile, soundings)
+      propagation_analysis = build_propagation_analysis(contact, hrrr_path, terrain, elevation_profile, soundings)
 
       {:noreply,
        assign(socket,
@@ -177,11 +176,10 @@ defmodule MicrowavepropWeb.ContactLive.Show do
     soundings = weather.soundings
 
     hrrr_path = Weather.hrrr_profiles_for_path(contact)
-    hrrr = List.first(hrrr_path)
     terrain = socket.assigns.terrain
 
     elevation_profile = compute_elevation_profile(contact, hrrr_path, soundings)
-    propagation_analysis = build_propagation_analysis(contact, hrrr, terrain, elevation_profile, soundings)
+    propagation_analysis = build_propagation_analysis(contact, hrrr_path, terrain, elevation_profile, soundings)
 
     {:noreply,
      assign(socket,
@@ -1367,12 +1365,13 @@ defmodule MicrowavepropWeb.ContactLive.Show do
 
   # ── Propagation analysis ──────────────────────────────────────────
 
-  defp build_propagation_analysis(contact, hrrr, terrain, elevation_profile, soundings) do
+  defp build_propagation_analysis(contact, hrrr_path, terrain, elevation_profile, soundings) do
     band_mhz = if contact.band, do: Decimal.to_integer(contact.band), else: 10_000
     band_config = BandConfig.get(band_mhz) || BandConfig.get(10_000)
     dist_km = contact.distance_km && Decimal.to_float(contact.distance_km)
+    hrrr = List.first(hrrr_path)
 
-    {factors, factor_rows, composite} = compute_factors(hrrr, contact, band_config)
+    {factors, factor_rows, composite} = compute_factors(hrrr_path, contact, band_config)
     summary = build_summary(terrain, elevation_profile, hrrr, soundings, dist_km, band_mhz)
     details = build_details(hrrr, soundings, elevation_profile, band_mhz)
 
@@ -1385,56 +1384,30 @@ defmodule MicrowavepropWeb.ContactLive.Show do
     }
   end
 
-  defp compute_factors(nil, _contact, _band_config) do
-    {nil, [], nil}
-  end
+  defp compute_factors([], _contact, _band_config), do: {nil, [], nil}
+  defp compute_factors(_hrrr_path, %{pos1: nil}, _band_config), do: {nil, [], nil}
 
-  defp compute_factors(_hrrr, %{pos1: nil}, _band_config), do: {nil, [], nil}
+  defp compute_factors(hrrr_path, contact, band_config) do
+    conditions = Scorer.path_integrated_conditions(hrrr_path, contact)
 
-  defp compute_factors(hrrr, contact, band_config) do
-    lon = contact.pos1["lon"] || contact.pos1["lng"]
-    temp_c = hrrr.surface_temp_c
-    dewpoint_c = hrrr.surface_dewpoint_c
-
-    if is_nil(temp_c) or is_nil(dewpoint_c) do
+    if is_nil(conditions) do
       {nil, [], nil}
     else
-      temp_f = Scorer.c_to_f(temp_c)
-      dewpoint_f = Scorer.c_to_f(dewpoint_c)
-
-      conditions = %{
-        abs_humidity: Scorer.absolute_humidity(temp_c, dewpoint_c),
-        temp_f: temp_f,
-        dewpoint_f: dewpoint_f,
-        wind_speed_kts: nil,
-        sky_cover_pct: nil,
-        utc_hour: contact.qso_timestamp.hour,
-        utc_minute: contact.qso_timestamp.minute,
-        month: contact.qso_timestamp.month,
-        longitude: lon,
-        pressure_mb: hrrr.surface_pressure_mb,
-        prev_pressure_mb: nil,
-        rain_rate_mmhr: 0.0,
-        min_refractivity_gradient: hrrr.min_refractivity_gradient,
-        bl_depth_m: hrrr.hpbl_m,
-        pwat_mm: hrrr.pwat_mm
-      }
-
       result = Scorer.composite_score(conditions, band_config)
       weights = BandConfig.weights()
 
       factor_rows =
         [
           {:humidity, "Humidity", humidity_note(conditions.abs_humidity, band_config)},
-          {:time_of_day, "Time of Day", time_note(contact.qso_timestamp, lon)},
-          {:td_depression, "T-Td Depression", td_note(temp_f, dewpoint_f)},
-          {:refractivity, "Refractivity", refractivity_note(hrrr.min_refractivity_gradient)},
+          {:time_of_day, "Time of Day", time_note(contact.qso_timestamp, conditions.longitude)},
+          {:td_depression, "T-Td Depression", td_note(conditions.temp_f, conditions.dewpoint_f)},
+          {:refractivity, "Refractivity", refractivity_note(conditions.min_refractivity_gradient)},
           {:sky, "Sky Cover", sky_note(conditions.sky_cover_pct)},
           {:season, "Season", season_note(contact.qso_timestamp.month, band_config)},
           {:wind, "Wind", wind_note(conditions.wind_speed_kts)},
           {:rain, "Rain", rain_note(conditions.rain_rate_mmhr)},
-          {:pwat, "PWAT", pwat_note(hrrr.pwat_mm, band_config)},
-          {:pressure, "Pressure", pressure_note(hrrr.surface_pressure_mb)}
+          {:pwat, "PWAT", pwat_note(conditions.pwat_mm, band_config)},
+          {:pressure, "Pressure", pressure_note(conditions.pressure_mb)}
         ]
         |> Enum.map(fn {key, name, note} ->
           score = result.factors[key]