top of page

Introducing HYPERR: WeatherOptics’ AI Weather Model that Reduces Forecast Error by 50%

WeatherOptics is excited to unveil its latest advancement in predictive weather technology: HYPERR, our new AI-based weather forecasting model. The WeatherOptics Hyperlocal Enhanced Rapid Refresh model significantly enhances short-term weather predictions, transforming how businesses anticipate and react to weather.

Designed for Hyperlocal Precision

HYPERR provides unprecedented hyperlocal coverage leveraging detailed probabilistic historical analysis. This robust system is designed to deliver precise forecasts down to 3 km, offering tailored insights for varied locations, including zip codes, zip-3 areas, states, and regions.

Enhanced Accuracy with Machine Learning

At the heart of HYPERR are sophisticated machine learning algorithms meticulously trained using ASOS ground-truth observations alongside short-range forecasts. 

Every 15 minutes, HYPERR updates the first six hours of the WeatherOptics forecast engine for critical parameters such as precipitation, wind, and visibility using the latest hour of radar and automated weather station observations across CONUS.

HYPERR integrates multiple high-quality data sources, including MRMS radar observations, GOES-R lightning observations, and ASOS data alongside high-resolution NWP models to provide detailed forecasts up to 180 hours in advance. This blend of data and technology ensures HYPERR offers the most reliable forecasts for WeatherOptics customers.

Where HYPERR's going to change the game is in that first six hour window where we can now deliver really granular, hyperlocal forecasts, that will allow our customers to save important shipments from being disrupted, or alert truck drivers of a pop-up thunderstorm that most other models would miss

- Jared Goldberg, co-founder and Head of Data Science at WeatherOptics.

Over the past several months, HYPERR demonstrated remarkable forecast improvements — up to a 50% reduction in root mean square error (RMSE) for six-hour precipitation forecasts and a 30% decrease in false discoveries for advisory-level winds.

WeatherOptics HYPERR model improvement over the HRRR for precipitation predictions

WeatherOptics HYPERR model improvement over the HRRR for wind gust predictions

Cutting-Edge Nowcasting with Real World Results

HYPERR's Nowcast component employs optical flow and computer vision algorithms that analyze recent radar observations to predict the movement of precipitation and lightning up to three hours ahead. 

This system is shown to improve the RMSE for three-hour precipitation forecasts by up to 20% and sharply reduce false discovery rates for moderate to heavy rainfall predictions.

We are already seeing the HYPERR model outperform standard NOAA models for real weather events happening across the United States.

During two separate flooding instances in April, HYPERR produced a more accurate forecast than NOAA’s short range HRRR model. Small changes in precipitation intensity and location of heaviest rainfall made a significant difference in real world impacts.

On April 3rd 2024, heavy rainfall prompted flash flood emergency warnings across the Pittsburgh metropolitan area. Rivers overflowed into streets and created a life threatening situation for several counties.

HYPERR was able to correctly identify the heaviest axis of rainfall across parts of OH, PA, and WV, and produced a more accurate forecast than the HRRR. 

The WeatherOptics model even generated newly formed thunderstorm predictions over northeastern OH that were not picked up by the HRRR, correctly identifying both the location and intensity. 

Later in the month, another significant flash flooding event occurred, this time across parts of TX and LA. Multiple towns in Texas declared flash-flooding emergencies with localized rainfall totals > 5 inches.

The HRRR drastically over-forecasted the event, showing widespread totals of 3-5 inches with some locations in southern Texas predicted to receive > 8 inches.

HYPERR not only correctly identified the amount of rainfall, it also accurately predicted the axis of heavy rainfall which was a curvature that cut through parts of eastern TX and into central LA. This is where the worst of the flash-flooding occurred. 

The WeatherOptics model also accurately identified an area of heavy rainfall in southern Texas that was completely missed by the HRRR. 

Empowering Industries with Accurate Forecasts

For industries such as supply chain and transportation, emergency management, retail, outdoor venues, and insurance, HYPERR is a game-changer. The enhanced accuracy of real-time weather data and actionable impact risk scores can dramatically improve operational efficiency and safety. 

HYPERR's ability to predict sudden weather developments like thunderstorms, which conventional models might miss or hyper-inflate, is particularly valuable. Its accuracy improvements of 30-40% compared to other models means our clients can trust in the reliability and precision of forecasts provided by WeatherOptics"

- Scott Pecoriello, co-founder and CEO at WeatherOptics.

Looking Ahead

As we roll out HYPERR across the WeatherOptics platform and products, our commitment remains steadfast: providing our clients with the most accurate, timely, and actionable weather information. With HYPERR, WeatherOptics is not just predicting the weather — we are redefining how industries prepare for and respond to meteorological events.

Stay updated with HYPERR, and see how WeatherOptics is setting new standards in weather forecasting, ensuring that no matter the weather, you're always prepared.

For more information on how HYPERR can benefit your business, visit our website or contact us at


bottom of page