ClearEdge runs a Kalman-filtered ensemble model across multiple independent meteorological sources — delivering bias-corrected, confidence-weighted temperature forecasts for 10 US cities, daily.
Every model run, ClearEdge ingests forecasts from six independent meteorological sources — including NWS, ECMWF, and regional ensemble models. No single source dominates.
A Kalman filter continuously corrects each source's historical bias. Models that run warm in winter get adjusted. Models with higher variance get weighted down. The result is a sharper signal.
Final temperature predictions are probability-weighted across all sources. Model spread becomes your confidence interval. Tight spread means high confidence. Wide spread means hold.
Stop relying on a single weather API. ClearEdge blends six independent sources through a Kalman filter — giving you tighter predictions, real confidence intervals, and Kalshi edge signals no single model can produce.
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