Weather & Conditions

The Weather tab provides atmospheric conditions specifically analysed for astronomical observation and astrophotography. It combines two independent data sources: Open-Meteo for standard meteorological data and 7Timer for seeing and transparency forecasts.

Tab layout

Weather alerts

Module: backend/weather/weather_astro.py (alert generation)

Alerts are generated from the Open-Meteo data and include:

Alerts are translated using the i18n system and displayed in the Alerts sub-tab.

Open-Meteo weather forecast

Source: Open-Meteo - free, no API key required.

Cache TTL: 1 hour (WEATHER_CACHE_TTL in utils/constants.py).

Module: backend/weather/weather_openmeteo.py

Variables fetched

Cloud layer discrimination

The three cloud-cover layers help astrophotographers distinguish:

• Low clouds (fog, stratus) - completely block imaging.
• Mid clouds (altocumulus) - usually opaque, block imaging.
• High clouds (cirrus) - thin and sometimes transparent; imaging may still be possible.

Total cloud cover is shown as the primary go/no-go indicator.

Rate-limiting behaviour

Open-Meteo free tier allows a limited number of concurrent requests. weather/weather_openmeteo.py implements two protections:

When rate-limited, the API returns the last successful response (stale-while-error) to avoid empty screens.

Astro weather analysis

Module: backend/weather/weather_astro.py

Class: AstroWeatherAnalyzer

This module transforms raw Open-Meteo variables into astrophotography-specific metrics. It calculates conditions for up to 48 hours and caches results for 30 minutes (in-process), and the cache scheduler additionally keeps a 24 h analysis warm per location in the astro_weather shared cache (see docs/CACHE_SYSTEM.md).

The observation score (single source of truth)

observation_score (0-10) is the one overall astrophotography-quality number in the app:

observation_score = (seeing_pickering*10 + transparency_score + cloud_discrimination + tracking_stability_score) / 4 / 10 * precipitation_factor

• seeing_pickering is 1-10; the other three components are 0-100 (so transparency_score, cloud_discrimination and tracking_stability_score must all stay on that scale - a component accidentally left on a 0-1 scale silently contributes almost nothing).
• precipitation_factor (0-1) is a multiplicative veto, not an averaged component.

It is shown, unchanged, by the navbar sky widget pill, the location switcher, the Weather tab’s hourly cards (served on /api/weather/forecast as condition, x10 to a 0-100 range) and the “Score de la Nuit” hourly cards. weather/weather_openmeteo.py no longer derives its own overall score.

Seeing estimate (Pickering scale)

The seeing estimate is derived from wind speed at multiple altitudes and atmospheric stability proxies available from Open-Meteo:

Note: This is a model-derived estimate. For high-resolution planetary imaging, cross-check with the 7Timer seeing forecast below.

Transparency (limiting magnitude)

transparency_score (0-100) is estimated from cloud cover, humidity, and visibility, and is then mapped linearly onto a limiting magnitude between MAGNITUDE_LIMIT_ZENITH_MIN (4.0) and MAGNITUDE_LIMIT_ZENITH_MAX (8.0):

Dew point warning

When the difference between ambient temperature and dew point is ≤ 2 °C (DEW_POINT_WARNING_THRESHOLD), a dew alert is raised. Dew on optics ends a session; plan dew heaters accordingly.

Jet stream impact

Wind speed at 80 m and 120 m altitude is used as a proxy for jet-stream influence. High upper-atmosphere winds correlate with poor seeing even when the surface is calm.

Best astro period

AstroWeatherAnalyzer identifies the best consecutive window within the forecast where:

• Cloud cover is low
• Humidity is acceptable
• Wind is calm
• Dew margin is safe

These “best period” cards are displayed in the Astrophotography tab.

7Timer seeing forecast

Source: 7Timer ASTRO product

Cache TTL: 6 hours (CACHE_TTL_SEEING_FORECAST). On a fetch failure, the cache is left untouched (previous good forecast keeps being served) instead of being overwritten with a failure marker - a transient 7Timer outage no longer blanks the tab for the full TTL window, since the next 5-minute scheduler tick retries once the existing entry’s TTL naturally elapses.

Module: backend/astroweather/seeing_forecast_7timer.py

Class: SeeingForecastService

7Timer’s ASTRO product returns eight fields per 3-hourly timepoint: seeing, transparency, cloudcover, lifted_index, rh2m (humidity), wind10m (direction + speed class), temp2m and prec_type. All of them are decoded and surfaced - not just seeing - and combined into a single composite quality_score (0-10) per timeslot.

Seeing scale (7Timer)

Transparency scale (7Timer)

7Timer’s transparency field uses the same 1-8 shape as seeing (1 = worst, 8 = best), expressed as limiting magnitude per air mass:

Cloud cover scale (7Timer)

1-9 scale, 1 = clearest (0-6% cover), 9 = fully overcast (94-100% cover).

Wind speed scale (7Timer, 10m)

1-8 scale from calm (< 0.3 m/s) to hurricane (> 32.6 m/s), paired with a compass direction.

Composite quality score

Each forecast point’s quality_score (0-10, higher is better) combines four of the raw 7Timer fields:

Active precipitation (prec_type != none) is a hard multiplicative veto (score × 0.1) rather than an averaged component, the same convention used by weather_astro.py’s precipitation_factor: rain or snow shouldn’t be masked by otherwise-clear metrics. lifted_index is decoded and exposed but not scored, since 7Timer’s seeing value already folds atmospheric stability into its own model.

The Seeing sub-tab renders this as an hourly timeline in the same visual style as the Astrophotography tab’s “Score de la Nuit” (night-score-timeline): one card per timeslot with the combined score, a quality badge, and an icon row for every underlying metric (seeing, transparency, cloud cover, wind, humidity, precipitation).

Best windows

Two “best window” cards are computed from the forecast:

• Best Seeing Window - longest consecutive run with seeing ≤ 3 (Good or better), unchanged from the original seeing-only definition - still the relevant metric for planetary imagers.
• Best Overall Window - longest consecutive run with quality_score ≥ 6 (Good or better), reflecting the full picture (seeing + transparency + clouds + wind).

Data sources

• Open-Meteo: open-meteo.com - free, open-source weather API; no account required.
• 7Timer: 7timer.info - free astronomical weather service based on GFS model data; no account required.

API endpoints

Last updated 2026-11-13