Our blog brings technical analysis, seasonal summaries, and practical guidance based on local observations and model evaluations. Contributors include our meteorologists and partner researchers who explain the reasoning behind forecasts, evaluate performance against ground truth, and share preparedness recommendations. We aim to help readers interpret probabilistic guidance and apply it to everyday planning. Each post includes data context and links to methods where appropriate, so users can understand forecast confidence and limitations.
Springtime storm timing depends on upstream fronts and local terrain. This article explains indicators we track and how to interpret short-term model blends to anticipate heavy rainfall windows and gusty winds for planning outdoor activities.
Sustained heat affects vulnerable populations. We summarize threshold-based actions, hydration guidance, and monitoring strategies for organizations managing events or facilities during elevated temperatures.
Local wind can diverge from large-scale forecasts. We describe diagnostic methods and station clusters used to correct neighborhood-level wind forecasts and reduce operational surprises.
Forecast verification is central to model improvement and user trust. We maintain continuous verification across multiple lead times and regions, comparing ensemble medians and probabilistic thresholds against ground truth from stations and partner sensors. Verification metrics include mean absolute error, Brier score for categorical events, and hit-miss statistics for alerts. Regular evaluation highlights systematic biases, which we correct using post-processing and local adjustment algorithms. Transparency is important, so we publish summary accuracy reports illustrating seasonal behavior, regional differences, and model improvements. For enterprise customers, tailored verification reports and SLA metrics are available to demonstrate operational reliability and guide threshold design for alerting systems.
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Indicators to watch and how we blend short-range models for timing heavy precipitation.
Actionable guidance for events and facilities during extended high temperatures.
Diagnostic approaches to improve neighborhood-level wind forecasts.