How Big Data Is Changing Weather Modeling and Wildfire Analysis – Updated September 2020
LAKE FOREST, Calif., September 16, 2020 /PRNewswire/ — In early 2018, PSSC Labs, a developer of custom High Performance Computing and Big Data computing solutions, in collaboration with Atmospheric Data Solutions (ADS), partnered together to design, build and implement custom HPC Clusters that could be used to assist utility companies as well as public and private agencies in predicting, mitigating and managing risk from severe weather patterns. This type of technology is absolutely critical in helping municipalities and government agencies in being able to assist in predicting and addressing wildfires like those being experienced in 2020 which to date has resulted in the evacuation orders of over 500,000 in Oregon alone. PSSC Labs HPC clusters can be used to analyze real-time data near wildfires, like temperature, humidity, and wind speed to help experts predict the movement patterns of the fire.
PSSC Labs is currently working with a number of large utility companies to quickly implement high performance computing solutions that are focused specifically on weather modeling and that have the ability to predict the potential paths of wildfires. This powerful HPC computing combination of weather modeling and wildfire analysis has the power to potentially save lives.
Accurate severe weather and wildfire predictions require technologically advanced high performance computing servers and artificial intelligence (AI) and PSSC Labs has powerful custom solutions to help meet this need. PSSC Labs’ PowerWulf Cluster weather solutions provide cutting-edge hardware that efficiently processes large amounts of data needed to train complex AI models for valuable wildfire potential forecasts.
For example, a government website called the Santa Ana Wildfire Threat Index developed in collaboration with a major southern California utility company, the U.S. Forest Service (USFS), and ADS forecasts short-term and long-term large wildfire potential. The Santa Ana Wildfire Threat Index site advises the USFS and the public on approaching wildfire potential events using forecasted weather and wildfire-centric variables including dead and live fuel moisture, all of which are generated on PSSC Labs PowerWulf Clusters.
This highly developed solution predicted large fire potential during the busy Santa Ana wind season providing month-ahead and season-ahead forecasts that warned of above normal Santa Ana winds this past fall. The public received forecasts and recommended actions well ahead of approaching critical fire weather. The utility agency used this advanced predictive technology to create forecasts to reduce the potential for accidental wildfire ignitions in their territories.
“Big Data is playing a crucial role in weather forecasting and wildfire analysis. This advanced information is important because we cannot just look outside for the weather,” said Alex Lesser, executive vice president at PSSC Labs. “With improved technology and the ability to process large amounts of data comes better extreme weather forecasts, which can save lives.”
How HPC, Big Data and AI Impact Weather Modeling and Wildfire Analysis
Weather models require specialized computing platforms that allow parallel computations. The closer the model horizontal and vertical grid spacing, the more computational resources are needed. Timely dissemination of the high-impact forecast to stakeholders and the public also requires state-of-the-art computing hardware.
PSSC Labs works with ADS to deliver cluster servers that are individually customized to meet the specific needs of each client. Key features of the PSSC Labs PowerWulf HPC Clusters include pre-configured and fully validated blocks with the latest Intel HPC technology and all the necessary hardware, network settings, and cluster management software prior to shipping.
Thanks to the processing power of PSSC Labs clusters, AI and Big Data can now play a key role in developing forecasting and wildfire analysis solutions that can prevent casualties. ADS uses AI to find relationships in data that can transcend the current understanding. For example, ADS uses AI to forecast damage to infrastructure during severe downslope windstorms that may occur during Santa Ana wind events.
“AI solutions are being built using multi-decadal historical atmospheric and land surface data at a close-enough grid spacing. This data allows for an intelligent historical ranking of a forecast which is one of the most valuable analytics ADS can provide a stakeholder,” said Dr. Scott Capps, Principal and Founder of ADS.
“The solutions ADS are developing use a comprehensive blend of predictors that are important to large wildfire potential including dead fuel and live fuel moisture, near-surface atmospheric moisture and temperature, wind speed and gusts,” Dr. Capps, continues. “Our partnership with PSSC Labs provides us with the hardware platform to meet the demands of high performance computing in order to maximize accuracy and maximize the number of times models can be run daily.”
According to Dr. Capps, the operational month-ahead and season-ahead Santa Ana wind forecasts are the first such solution.
For more information visit https://www.pssclabs.com/solutions/hpc-cluster/
