WindBorne has once again surpassed gold-standard physics- and AI-based weather forecasting models with a series of new accuracy gains by the latest version of its AI forecasting model, “WeatherMesh-...
WM-2’s new forecasting records can be attributed to both WindBorne’s novel pipeline of atmospheric data, as well as to the company’s proprietary AI modeling innovations
PALO ALTO, Calif.: WindBorne has once again surpassed gold-standard physics- and AI-based weather forecasting models with a series of new accuracy gains by the latest version of its AI forecasting model, “WeatherMesh-2,” or “WM-2.”
WM-2 is a global, medium-range AI-based weather model that predicts core forecasting metrics across the Earth’s surface and atmosphere, including geopotential, wind speed and direction, temperature, precipitation, cloud cover, solar radiation, pressure, and humidity. The model predicts these metrics about 8% to 24% more accurately than the Global Forecasting Service (GFS), the European Center for Medium Range Weather Forecasting (ECMWF)’s HRES, and Google DeepMind’s GraphCast over equivalent time horizons; in many cases, WM-2 maintains this accuracy lead over other gold standard models even when predicting further into the future.
WM-2 forecasts 0.25 degree global grid forecasts for 14+ days at both hourly and six-hourly intervals. WM-2 currently generates forecasts four times per day, incorporating live real-time estimates of current weather analyses from large physics-based models, along with observations collected from WindBorne’s own atmospheric balloons.
Sample March-May 2024 WM-2 performance results:
Atmospheric Data and AI Modeling Break-Throughs
WM-2’s accuracy gains can be attributed to two unique advantages:
WindBorne’s announcement comes just 10 months after the company unveiled its first groundbreaking AI-forecast model, “WeatherMesh,” in February 2024.
For a deeper look at WindBorne’s model performance across key weather variables, see WindBorne’s latest WM-2 case studies.
International Growth
WindBorne’s customer base and operations have continued to grow internationally since the company first announced WeatherMesh earlier this year. WindBorne began selling its atmospheric observational data on an operational basis to the National Oceanic and Atmospheric Administration (NOAA) two years ago, and now sells its data in both the public and private sectors. WindBorne has also started the first commercial pilots of its weather forecasting model WM-2 with partnerships in Asia and the U.S.
WindBorne’s autonomous atmospheric balloon constellation is powered by more than half a dozen international balloon launch sites, which include Palo Alto, Calif., upstate New York, and South Korea. The company has also established permanent sites in particularly under-observed regions such as sub-Saharan Africa and in Southeast Asia.
New high-resolution offering
WindBorne’s revamped, WM-2 model now offers high-resolution local forecasts anywhere in the world for plots as small as 1 km by 1 km. WindBorne achieves this level of precision through a forecasting method known as “downscaling,” in which WM-2 works in tandem with an additional specialized WindBorne model tuned to generate high-resolution forecasts.
Record-breaking speed
WM-2, which is used in live, operational environments, is able to produce complete 10-day forecasts in nine seconds and complete 14-day forecasts in 13 seconds, about 143,000 times faster than the gold standard global weather model, the ECMWF’s HRES.
This output speed is significant for public sector forecast guidance and a wide range of commercial use cases, including energy grids, energy markets, aviation, live events, and more.
WindBorne’s machine learning and AI team, which has trained in world-class teams such as Fei-Fei Li’s Stanford University Lab and the University of California, Berkeley, has grown multi-fold since WeatherMesh’s debut. In the past year, the team has expanded from the company founding team to now making up nearly a fifth of WindBorne’s 40-person full-time team.
WindBorne continues to advance its forecasting technology and scale its global data collection. Over the next year, WindBorne plans to scale the size of its forecast models, increasing the number of parameters, which enables the model to understand more nuanced relationships in the data. WindBorne will also continue expanding its datasets, both through its own atmospheric data collection, as well as through supplemental environmental data. The team will continue to invest in underlying modeling techniques to improve forecast resolution, minimizing blur and other erroneous artifacts that can be generated through deep learning prediction techniques to support even longer time-horizon lead times.
About WindBorne
WindBorne is a planetary intelligence company that provides people, governments, and industries with unprecedented environmental data and insights through a global constellation of atmospheric sensing balloons and AI-powered predictions. While others are focused on either marginal aspects of data collection or forecasting, WindBorne is revolutionizing the end-to-end planetary intelligence stack by both tackling the most urgent data gap and dramatically improving AI forecast accuracy and lead times.
Fonte: Business Wire
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