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Tomorrow.io
Tomorrow.io
May 7, 2019· 2 min, 57 sec
Tomorrow.io
Tomorrow.io

A Revolution in Weather Forecasting: Tomorrow.io Launches CBAM, its NWP Platform, Taking Weather Forecasting to the Next Level

BOSTON, May 7, 2019, Tomorrow.io, the leading weather technology company, is about to change how the world forecasts weather. Today the company unveiled its stealth mode Numerical Weather Prediction (NWP) division, operating from Boulder, CO, and its new NWP platform,  CBAM.

CBAM stands for Tomorrow.io’s Bespoke Atmospheric Model (or the name Tomorrow.io prefers, Tomorrow.io Bad Ass Model) and introduces two major differences to weather forecasting as we know it today: CBAM is microscale and on-demand.

Weather prediction models haven’t changed much in decades. They are designed to address the broadest needs rather than provide answers to the specific questions each industry and business have. Currently, whether a company needs to make decisions regarding renewable energy generation, the impact of snow on flight ops, or expected flooding conditions, the answers are the same. That’s because full-scale weather modeling, which is used by most weather companies, is done almost solely by governmental agencies. (In addition, existing models rely on traditional weather observations, which are sparse even in the most developed regions around the globe and therefore provide only a partial picture.)

With CBAM, Tomorrow.io is offering a new modeling capability that takes weather forecasting to the next level. CBAM takes traditional data sources, integrates them with data from the connected world, and then analyzes the data using models that provide an unprecedented level of accuracy and reliability – and therefore actionability – to weather forecasts.

What is CBAM, and why is it revolutionary?

  1. High Resolution Analysis: Today, one of the best available public models, NOAA’s High-Resolution Rapid Refresh (HRRR), works in resolutions of 3km. CBAM gets to the highest resolution that exists in the market today: tens of meters. This resolution allows us to account for things like terrain and buildings and see otherwise invisible features, such as wind turbulence around buildings.
  2. Update Frequency: HRRR updates every hour, and most other public models update every 6 hours. CBAM, in contrast, updates every few minutes.
  3. Global: HRRR and similar models are only available in a few developed countries, while the vast majority of the world remains without access to such forecasts. CBAM is Global – it can operate anytime, anywhere, from a single wind farm to the entire Indian subcontinent.
  4. On-demand: Rather than feeding everyone with outputs from the same generic model, CBAM is tailored and flexible, providing the optimal solution for each customer’s unique needs, be it location, resolution or weather variable of interest. CBAM generates customizable weather forecasts for specific domains and specific use cases.
  5. Data: Thanks to Tomorrow.io’s Weather of Things (WoT) approach, CBAM feeds from hundreds of millions of proprietary observations from the connected world, including in data-poor regions.

 

With CBAM  businesses can rely on weather forecasts to improve planning and make better decisions, regardless of where they are in the world or what information they need for their operations.

The new world-class NWP division in Boulder, CO, is run by Dr. Luke Peffers, who  worked at the Department of Defense (DoD) for 18 years. Before joining Tomorrow.io, Dr. Peffers worked at Science and Technology in Atmospheric Research (STAR) and before that at the United States Air Force Technical Applications Center (AFTAC). At AFTAC, Dr. Peffers served as the branch chief of the Meteorological Modeling and Analysis. Dr. Peffers designed and built multiple operational numerical weather prediction (NWP) and forensic analysis systems for Chemical, Biological, Radiological and Nuclear (CBRN) threat assessments including AFTAC’s operational NWP systems that are used to monitor compliance with multiple global nuclear test ban treaties. 

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