Why we care about GOES-R

By : Emmett Soldati |December 19, 2016 |weather-report |0 Comment


It has been 6 years since the U.S. sent a geostationary (one that moves with the rotation of the Earth) satellite into orbit for the purpose of atmospheric observation and data collection.  On November 19th, the National Oceanic and Atmospheric Administration (NOAA) launched the next generation Geostationary Operational Earth Satellite (GOES-R) into orbit.  Satellite imaging technology has greatly improved since the mid-2000s.  So too have the algorithms to derive weather phenomena on the ground based on the radiation measured and cloud images captured from the satellite. Weather observations from space are getting better.

For those customers and organizations whose business depends greatly on understanding the atmosphere, ‘better’ means two things – higher resolution and faster updates.  For the meteorological activity we can observe and extrapolate from these satellites, date from the GOES-R satellite will increase geospatial resolution up to 4 times, and refresh rates (timeliness) will be as frequent as 30 seconds.  Finer and faster data is good, but businesses, such as large insurance companies or agro corporations, need to put that data into context – to analyze it in the environments they operate in to make better, and faster, decisions.



As an atmospheric risk solutions company, Weather Analytics identifies and procures the best-in-class sources of data to address challenges posed by weather and environmental activity.  We leverage, cleanse, and enhance data from multiple public and private sources – and produce our own geophysical data with in-house meteorological experts.  As a solutions company, with a SaaS model to help customers assess and mitigate large global risks in real-time, we know the problems our clients need to solve and how best to deliver actionable insights.  With the enhancements to the meteorological data in the Western Hemisphere that GOES-R will provide, Weather Analytics is ‘at-the-ready’ to provide our clients with the value these upgrades bring.


dexter-logoFirst and foremost, Dexter, the leading weather claims forensics tool, will see an added feature in late 2017 –  lightning detection.  U.S. users of Dexter already receive the highest-resolution verification of weather perils from reliable and quality-controlled sources available – including precision hail, rain, and wind gust reporting.  Dexter’s lightning product is slated to launch in the middle of 2017. As GOES-R is the first total and continuous geostationary satellite to house a lightning imager, the data provided will enhance our user-friendly weather tracker platform – for easy reporting, verification, and claims analysis for lightning strikes.




wildfireWildfires are on the rise globally, and the recent events in the Southeastern United States show us that climatological factors are changing the hot-zones for risk of spread here at in the U.S.  Combining multiple meteorological and topographical data sources, Weather Analytics began developing its comprehensive Wildfire Awareness solution earlier in 2016 – including Wildfire Vulnerability Mapping, damage assessments, and analyzing Fire Weather changes across the globe over the last four decades.  With the enhanced fire signatures captured by the GOES-R Advanced Baseline Imager, Weather Analytics will be able to deliver more timely, and higher resolution, footprints of burn during and after a major fire event.


beacon-logoHurricane forecast models are slated to improve following the enhanced (and rapidly-refreshed) imagery of tropical storms and cyclones.  This is a salient feature of the GOES-R and will provide a major upgrade to numerical weather prediction systems, including those run by governmental organizations..  Good news for Weather Analytics subscribers to Beacon Hurricane, our real-time machine-learning hurricane forecast dashboard.  Weather Analytics scientists have spent 12 months designing the world’s most intelligent multi-model hurricane ensemble – leveraging known hurricane forecast data from the top 3 forecasting agencies – NOAA’s National Centers for Environmental Prediction (NCEP), the European Center for Medium-Range Weather Forecasting (ECMWF), and Environment Canada.  Using machine-learning techniques similar to those used by Amazon, Weather Analytics algorithmically studies and tracks the accuracy of over 90 model forecasts from these agencies and blends them to provide the most-accurate real-time hurricane prediction.  As the underlying models improve by including GOES-R imagery, so too will the resulting Beacon Hurricane forecast.  With added geospatial analytics such as landfall probabilities calculation and maximum probable loss estimates for assets, as well as automated early warning systems tied to forecasted winds and rain, Beacon Hurricane is and will continue to be the new baseline for preparing for and responding to catastrophic tropical cyclone damage.


These are the few of the ways our customers will see, and experience, improvements to their risk mitigation tactics.  Weather Analytics is on a very fast growth rate – with proprietary scientific content expanding into new domains each quarter.  By the time the GOES-R data becomes operational (middle to end of 2017), we’ll likely have developed new solutions to even better leverage these scientific data feeds – ranging from pollution detection, visibility indices, and higher accuracy precipitation metrics.