Applying NOAA and AI weather forecasting models to supply chains

by Jon Davis, Kate Szura, Jenny Dissen, and Adrienne Simonson

AI is becoming more important in weather forecasting models, especially for business-critical weather forecasting. Access to accurate and reliable weather and climate data is crucial for every industry, but especially for supply chain risk management. Being able to anticipate severe storms, monitor temperature fluctuations along designated routes, and make informed decisions can make all the difference between delayed shipments resulting in damaged goods or the satisfaction of happy customers. 

With severe weather increasing in frequency due to climate change, having access to accurate and reliable forecasts has become paramount. The annual rate of storms exceeding $1 billion in damages within the United States averaged 8.1 events between 1980-2022. Last year, there were 28 billion-dollar damage weather events in the U.S. – an all-time record totaling $92.9 billion. 

Everstream Analytics leverages National Oceanic and Atmospheric Administration (NOAA) weather data via Amazon Web Services (AWS) to produce the most precise, predictive risk intelligence for data-driven supply chain decision-making. 

How Everstream uses NOAA weather data  

Everstream has analyzed weather data across end-to-end supplier networks for over a decade to help clients uncover risk, assure supply quality, and maintain uninterrupted logistics. Everstream’s Applied Meteorology and Climate Team uses massive amounts of weather and climate data to generate risk scores that inform immediate and long-term strategies for sourcing, operational siting, and delivery logistics. 

Producing the most accurate and relevant risk scores requires massive amounts of data from proprietary and open sources. Everstream’s forecast data alone accesses and uses over 20 billion data points daily. These observations come from the National Weather Service within NOAA and the European Weather Service. Using artificial intelligence (AI) and machine learning (ML), Everstream pulls the needed datasets from various sources and produce tailored risk scores at the scale and speed required to mitigate supply chain risk from a global standpoint. 

Central to Everstream’s data-driven weather insights approach are NOAA datasets, specifically the Global Forecast System (GFS) and the Global Ensemble Forecast System (GEFS), hosted on the cloud through NOAA Open Data Dissemination (NODD) and accessed via Amazon Web Services (AWS). Everstream combines these with data from the European Center for Medium-Range Weather Forecasts (ECMWF) and analyze them to help clients keep goods and services reliably moving by road, rail, or ship. 

Driving impact and results through data analysis via the cloud 

It is one thing to see data, but another to live it. Risks incurred along supply chains not only impact companies providing the services and goods but also impact the customers and introduce costs that eventually get passed downstream to consumers. Having access to accurate and reliable weather and climate data supports risk mitigation and cost savings across the end-to-end supply chain. 

Companies including Google, Schneider Electric, Unilever, and Campbell’s rely on Everstream’s risk insights to mitigate weather and climate risks. One example of how Everstream helps clients protect products and revenue is through logistics planning guidance. Using NOAA’s forecast data as part of the analysis, Everstream guides Unilever on when to use refrigerated trucks, and the best timing and routes to protect temperature-sensitive products. NOAA’s weather and climate data also supports Everstream’s climate recommendations, such as where to build or move plant operations as climate change increases water and heat stress risks in certain regions.  

Our risk scoring and analyses extend beyond land to sea with Everstream’s acquisition of Bluenode. The new Bluenode division applies AI and data cleansing technologies to intermodal data from 160 countries to provide end-to-end risk assessment and optimization solutions.  

Access to NOAA’s invaluable weather and climate data is instrumental in driving substantial impacts on a global scale. This access reduces costs across entire supply chains, benefiting both companies and their customers. Furthermore, the ability to access this data via the cloud ensures the rapid dissemination of reliable information, facilitating informed decision-making for all stakeholders involved. 



Jon Davis is the Chief Meteorologist at Everstream Analytics; Kate Szura is the Communications Lead for NOAA Open Data Dissemination (NODD); Jenny Dissen is the CISESS Engagement Lead for NOAA Open Data Dissemination (NODD); Adrienne Simonson is the Director for NOAA Open Data Dissemination (NODD). 

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