April 21, 2019, The New York Times
Opinion by William B. Gail, CTO of Global Weather Corporation, Past President of the American Meteorological Society
Donald Rumsfeld famously popularized the term “unknown unknowns” in a 2002 news briefing when describing the challenges of linking Iraq to weapons of mass destruction. Troublingly, climate change may also be strewn with such unknowns, and they pose daunting tests for how we face the future.
One is choosing among policy alternatives. Should we minimize tomorrow’s risks now by reducing greenhouse gas emissions, or save money today and spend it on adapting to the effects of planetary warming once threats emerge more fully, like rising seas or prolonged droughts? The policy debate increasingly tilts toward adaptation. Continue reading this article by clicking here.
BOULDER, CO, April 9, 2019 – Global Weather Corporation, a leading provider of weather forecast data services for business applications, announced today that it has been awarded a patent for its method for improving weather forecasts by incorporating sensor data from vehicles.
Weather can vary over sub-kilometer scales, particularly in coastal areas, mountain regions, urban areas, and across valleys. This fine-scale variation is hard to predict using traditional weather models. Yet the demand for detailed weather information has grown rapidly with the proliferation of mobile devices capable of receiving weather information and with advances in highly autonomous vehicles. Users seeking reliable weather information for their specific location are often provided with forecasts from fixed-location weather station locations, not for where they actually are.
The newly patented method delivers an improved forecast that leverages the increased geographic availability of vehicle sensors capable of providing weather observations. The vehicle observations greatly augment what is available from traditional fixed-location weather stations operated by institutions and enthusiasts. The method enables a fine-scale estimate of typical, localized weather variability, from which more accurate weather forecasts can be generated.
According to Global Weather Corporation CTO and lead inventor on the patent, Bill Gail, “Many of the most demanding new weather use cases, such as driving decisions made by autonomous vehicle systems, require ever-better forecast quality and specificity. The novel methods addressed in this patent make that possible.”
CEO, Mark Flolid, added, “Our team of scientists continues to lead the industry by innovating to address the mobility industry’s toughest weather challenges. This patent is another example of Global Weather Corporation anticipating customer needs and advancing technology that will address major safety and operational issues for autonomous vehicles by forecasting hazardous road weather conditions for any road in the world.”
Global Weather Corporation
Global Weather Corporation is transforming the way weather forecasts are created for the connected world by delivering rapid innovation and disruptive solutions. We provide the world’s most accurate weather data (DaaS) for businesses that require reliable weather intelligence to prioritize safety and to support critical operations. Our heritage is in the world’s most prestigious weather research institution, the National Center for Atmospheric Research. Leveraging decades of advanced weather research, Global Weather Corporation has created the #1 ranked forecast in the world and a host of specialized forecast services that benefit the markets we serve and our partners in the global weather community. For more information, visit globalweathercorp.com.
BOULDER, CO, February 28, 2019 –Global Weather Corporation, a leading provider of weather forecast data services for the enterprise, mobility, energy, and media industries, announced today an enhancement to its RoadWX® road surface conditions forecast service. The RoadWX forecast can now distinguish between five changing road surface conditions – dry, near dry, wet, slush, ice/snow. The new condition, “near dry,” fills the important gap between non-dry and dry roads, providing more information about what lies ahead.
Bill Gail, Global Weather Corporation CTO and Co-Founder, noted, “The new ‘near dry’ road condition helps identify more precise, transitional conditions when road surfaces are neither clearly wet nor fully dry, such as roads that have some slightly wet portions.”
Designed for the mobility industry, RoadWX provides the world’s most complete and reliably accurate road weather forecast to increase safety and provide critical decision support information for connected and autonomous vehicles. Use cases include navigation planning, autonomous vehicle availability function, operational domain support, fleet management, and applications such as driver safety alerts. Typical users include automotive OEMs, Tier 1 location services and navigation platforms, infotainment service providers, fleet management solution providers, and driverless technology companies – all of which require locationbased road weather and road surface condition forecasts to prepare for potentially hazardous conditions on the route ahead.
Global Weather Corporation
Established in 2011, Global Weather Corporation (GWC) is a privately held data service company located in Boulder, Colorado. GWC was formed to commercialize advanced weather forecasting technology developed at the National Center for Atmospheric Research (NCAR). The company provides the world’s most accurate weather data services for businesses that require reliable weather intelligence to prioritize safety, enhance decision-making, and support critical operations. For more information, please visit globalweathercorp.com.
RoadWX is the most complete and reliably accurate road weather and road surface conditions forecast available, developed to increase safety, improve performance, and provide critical decision support information for connected, autonomous, and driverless vehicles. The RoadWX service covers every mi/km of every route, from primary to local roads, worldwide. It uses machine learning to leverage available data from vehicles, Road Weather Information System (RWIS) sites, and other sources to continuously improve forecast accuracy from the present time to 48 hours into the future. For more details, contact GWC at email@example.com, or visit globalweathercorp.com/roadwx.