Cloud Sea Forecast

Problem Being Solved

Cloud-sea forecasting is not just checking whether fog exists. Mountain observation points around Beijing differ widely in elevation, fog base, fog top, dew-point temperature, atmospheric transparency, and sunrise viewing angles, so relying on intuition or a single model can easily misjudge the result. cloud-sea addresses this by taking a date or a simple phrase, fetching multi-source weather data, and estimating cloud-sea probability, sunrise quality, fog type, and travel risk in a readable report.

How It Works and Where It Fits

The workflow centers on LCL and fog-top logic. It uses Open-Meteo to retrieve ECMWF, CMA, and ENS data, then fuses them to calculate dew_point_2m, LCL, fog base height, and fog_top_msl. The scoring also considers wind speed, humidity, visibility, PM2.5, and AOD. The skill distinguishes between ordinary cloud-sea prediction, sunrise cloud-sea analysis, multi-site comparison, and data verification tasks, and produces Markdown and HTML reports.

It is best suited to cloud-sea and sunrise planning in northern China mountain areas, especially the official 16 peaks and common observation points. Keep in mind that results depend on live API data and still carry uncertainty; low-elevation Great Wall sections, urban station data, haze, and precipitation risk can materially affect visibility and safety, so it should not be treated as a deterministic forecast.