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06/08/2023

Meteomatics Partners With Spottitt To Offer High-Resolution Weather Analytics

Akemi Narindal Aoki - Digital Marketing Manager
Dr. Akemi Narindal-Aoki
Sr. Content Marketing Manager
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Meteomatics' weather data is now integrated into Spottitt’s Climate Conditions Monitoring module. This integration provides Spottitt's clients with high-resolution weather information, enabling them to monitor rapidly changing weather and climate conditions around their critical infrastructure.

Spottitt Offers Insights for the Energy, Utility and Infrastructure Sectors

Spottitt is a cloud-based solution that leverages satellite data and advanced AI models to provide insights for the energy, utility and infrastructure sectors. By analyzing data from critical infrastructure, including transmission grids, pipelines and substations, Spottitt identifies potential points of failure and assists in developing strategies to minimize downtime and mitigate the risk of catastrophic damages.

Spottitt's suite of monitoring services covers a wide range of needs, including:

  • vegetation
  • 3rd party
  • pipeline leak
  • climate conditions
  • biodiversity
  • land and assets
  • motion
  • flood
  • photovoltaics and wind site selection
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Meteomatics’ Weather Data Integrated Into the Climate Conditions Monitoring Module

Extreme weather events, such as heatwaves, severe cold snaps, heavy rainfall and windstorms pose significant threats to infrastructure, leading to equipment damage, power outages, wildfires and safety risks for power grids and utility pipelines. Additionally, the performance and efficiency of renewable energy systems are dependent on weather conditions.

Spottitt's Climate Conditions Monitoring module offers operators regular insights into the environmental conditions impacting their assets. Leveraging a combination of satellite data, AI technology and high-resolution weather data from Meteomatics, Spottitt monitors key parameters including wind speed, temperature, precipitation, wind direction and gust speed, relative humidity, and many more.

Meteomatics’ Weather Data Is Downscaled to a 90 Meter Resolution

To deliver the most accurate weather information, Meteomatics’ Weather API collects and combines data from various sources, including global and regional weather models, satellite imagery, radar and weather stations. The data is then post-processed using Meteomatics’ proprietary 90 meter downscaling technology: data from the weather models are combined with model data from NASA's 90 meter digital terrain model and refined to produce higher local accuracy.

Spottitt will retrieve a large dataset of historical weather data from Meteomatics’ Weather API and ingest it directly into the Spottitt Metrics Factory, also known as Spottitt MF, the company’s analytics system. The availability of comprehensive parameters, combined with a 90-meter downscaling technique, gives users a detailed understanding of the average weather conditions at specific asset locations and effectively assess weather risks.

As Spottitt’s CEO and Co-Founder Lucy Kennedy stated:

“Spottitt clients are looking to get a complete and detailed picture of the past, present and future risks in and around their assets, in these days of climate change that very much includes weather. Being able to take this data down to 90 meter resolution thanks to our partnership with Meteomatics is very exciting”.

By integrating Meteomatics’ weather data into Spottitt MF, we have successfully combined high-resolution weather modeling with advanced analytical tools. This integration is a significant development that enables users to effectively quantify and mitigate the growing risks associated with weather events.

Lucy kennedy
Lucy Kennedy
CEO & Co-Founder
Spottitt
Spottitt clients are looking to get a complete and detailed picture of the past, present and future risks in and around their assets. Being able to take weather data down to 90 meter resolution thanks to our partnership with Meteomatics is very exciting.
Rob Hutchinson
Rob Hutchinson
Sales Manager & Meteorologist

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