Improve your data quality and verification workflow. Aggregate scores hide the stations dragging your numbers down—only station-level verification reveals them. Track your priority locations against third-party observations and competitor forecasts in one workspace.
Build a watchlist in seconds. Hunting down station codes across spreadsheets wastes your meteorologists’ most valuable hours. Add any station by code, name, or city—or pin one directly from anywhere in ForecastWatch—so every priority location stays one click away.
Diagnose the root cause, not the symptom. Aggregate accuracy scores tell you a model is underperforming; they don’t tell you where. Drill into any station across every core variable—from 24hr High/Low to MOS and Wind—to pinpoint exactly which locations are costing you accuracy.
Turn tribal knowledge into an auditable record. Model fixes made at 2am can’t live in Slack or in one meteorologist’s head. Attach timestamped notes to any station to document adjustments, data quality flags, and known site issues—so your team compounds its learnings across every shift.
ForecastWatch verifies against METAR and SYNOP observations from primary national networks—NWS, Environment Canada, DWD, AEMET, BOM, and others—the same ground truth your customers use to judge your accuracy. You can benchmark any station against both competitor forecasts and official observations in a single view.
Station scores update daily, with verification finalized once the forecast day has closed and official observations are confirmed. Historical performance extends back years, so your meteorologists can identify seasonal patterns and long-term model drift—not just react to yesterday’s miss.
Yes. Every station on your watchlist supports timestamped notes for model adjustments, siting issues, and data quality flags. Notes persist across users, shifts, and staff turnover, giving your team a permanent institutional record instead of knowledge that disappears when someone leaves.