PSSC Labs
Request a Quote

Tag: weather modeling

How Technology Helps to Forecast Weather and Reduce Wildfire Ignitions

By marketing@site-a.com

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.site-a.com/solutions/hpc-cluster/

Source: https://www.prnewswire.com/news-releases/pssc-labs-and-atmospheric-data-solutions-deliver-hpc-clusters-to-forecast-weather-and-reduce-wildfire-ignitions-300588776.html?tc=eml_cleartim

HPC Systems for Weather Modeling

By marketing@site-a.com

Numerical Weather Prediction (NWP) data is the form of weather modeling data that most professionals and consumers are most familiar with. NWP takes current observations of weather measurements and utilizes this data to create weather forecasts. Many systems assisting researchers in ingesting, analyzing, and storing this data do so with the help of weather modeling applications like Weather Research and Forecasting (WRF).

Weather Modeling and Forecasting Process

Weather forecasters utilize mathematical equations that factor in the physics behind the variables that influence weather – solar radiation, orbital distance from the sun, pressure, wind, temperature, and moisture – among others. These observations are obtained from sensors or satellites and then fed into the equations in a process that’s referred to as data assimilation. This data is then fed into a few different slots that assist in the process of specifying weather for future points.

There are three primary used synoptics forecast models: The North American Mesoscale Model (NAM), the Global Forecast System (GFS), and the Nested Grid Model (NGM).

North American Mesoscale Model (NAM)

The NAM model refers to a numerical weather prediction model run by National Centers for Environmental Prediction for short-term weather forecasting. Currently, the Weather Research and Forecasting Non-hydrostatic Mesoscale Model (WRF-NMM) model is run as the NAM, thus, three names (NAM, WRF, or NMM) typically refer to the same model output. 

Weather Research and Forecasting (WRF)

The WRF model is a mesoscale numerical weather prediction system for both operational forecasting and atmospheric research objectives. WRF was developed through the partnerships of the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration, the Forecast Systems Laboratory (FSL), the Air Force Weather Agency (AFWA), the Naval Research Laboratory, Oklahoma University and the Federal Aviation Administration (FAA).

WRF offers two dynamical solvers for its computation of the atmospheric governing equations:  WRF-ARW (Advanced Research WRF) and WRF-NMM (nonhydrostatic mesoscale model). ARW is supported to the community by the NCAR Mesoscale and Microscale Meteorology Laboratory. NMM is supported to the community by the Developmental Testbed Center (DTC).

Global Forecast System (GFS)

The GFS is a weather forecast model that is produced by the National Centers for Environmental Prediction (NCEP). This model produces a dataset that allows for dozens of atmospheric and land-soil variables to be accessed and considered in the forecasting of weather, like temperature, wind, precipitation, soil moisture, and atmospheric ozone concentration.

The entire globe is covered by the GFS with a base horizontal resolution of 18 miles between grid points, which is used by forecasters to predict weather for out to 16 days in the future.

Hardware Recommendations

  • RAM: Determines maximum model size (DOF, degrees of freedom) that can be solved. Typically large amount of memory per processor core (4 GB+ per processor core) are the standard.
  • CPU: number of cores and clock speed determines how quickly a model can be solved. (Good metric to compare between CPU options is: Clock Speed x Number of Cores / Cost.  Higher clock speeds and large core counts enable larger weather models to be run at higher resolutions.
  • Storage: determines how much data can be held on the system, and how quickly it can be input/read.
  • GPU: Speed up complex solutions. NVIDA GPUs are often utilized.
  • Interconnects: Enables high speed cluster communication and lower latencies.  100 Gb / sec network fabrics from Intel (Omnipath) and Mellanox (Infiniband) are typically a standard in weather modeling HPC environments.

High resolution models like those mentioned above required massive amounts of computing power, along with expertise and experience. That capability comes from our HPC cluster, the PowerWulf ZXR1+. At PSSC Labs, we provide our clients with the partner they need in systems design, manufacturing, and installation of custom-built HPC hardware, built to ensure that your weather model performs exactly as you’ve designed it to. We focus on providing an ultra-reliable, extreme-scale platforms for your needs.

Government agencies, public utilities, and research organizations rely on our expertise to realize their goals for mitigating and managing risk associated with severe weather and the effects of climate change.

Design your model. Design your HPC solution. Implementing a numerical weather model

By marketing@site-a.com

Implemeting a Numerical Weather Model

Download our presentation in collaboration with Scott Capps, Ph.D., Atmospheric Data Solutions, LLC on how to implement high-res numerical weather modeling solutions.

Datasheet: Experience a truly turnkey weather modeling solution from PSSC Labs

By marketing@site-a.com

Weather Modeling

Proven extreme-scale computing platform for weather modeling – serving atmospheric science and related fields for academia, public & private sector organizations, and federal agencies.

Download the Weather Modeling datasheet.

PSSC Labs to Exhibit HPC Clusters for Weather Modeling and Analyzing Wildfire Fuel Loads at American Meteorological Society Annual Meeting

By marketing@site-a.com

High Performance Computing manufacturer teams with Atmospheric Data Solutions to provide turn-key supercomputer solutions for the AMS community

LAKE FOREST, CALIF., JANUARY 06, 2018 /PRWEB/ — PSSC Labs, a developer of custom High Performance Computing (HPC) and big data computing solutions, today announced it will showcase a series of High Performance Computing (HPC) solutions that are custom-built for weather modeling and wildfire analysis at the American Meteorological Society Annual Meeting (AMS) January 7-11, 2018 at the Austin Convention Center in Austin, Texas in Booth #736 in the Main Hall.

This year, the 2018 AMS Annual Meeting theme is “Transforming Communication in the Weather, Water, and Climate Enterprise Focusing on Challenges Facing Our Sciences.” The theme aims to enhance the scientific conference with a focus on communication science and practice to ensure the strengthened success of the enterprise in the future.

Weather research is rapidly advancing aided by the technological evolution of High Performance Computing servers. PSSC Labs delivers hand-crafted HPC and big data computing solutions based on its PowerWulf HPC cluster that are customized for the AMS community. 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. Such solutions are paramount for dependable information in forecasting and air quality assessments for environmental analysts. Through the use of powerful, turn-key HPC cluster solutions for weather modeling solutions, climate scientists are able to combat wild fires such as the ones seen recently in Southern California.

PSSC Labs offers a complete hardware/software solution through its partnership with Atmospheric Data Solutions, LLC (ADS) to deliver powerful and customized supercomputing solutions for ADS’ weather modeling products. The weather modeling solutions that ADS creates include high impact weather forecast guidance products, tailored regional wildfire forecast guidance products, and utility load and outage forecasts – all requiring analysis of a large quantity of data that demands high performance computing to maximize accuracy and maximize the number of times models can be run daily.

PSSC Labs PowerWulf HPC Cluster offers a reliable, flexible, high performance computing platform for a variety of applications in the following verticals besides meteorological sciences including: Design & Engineering, Life Sciences, Physical Science, Financial Services and Machine/Deep Learning.

Source: http://www.prweb.com/releases/2018/01/prweb15058987.htm

Weather Modeling at Atmospheric Data Solutions Gets a Boost with HPC Clusters from PSSC Labs

By marketing@site-a.com

High functioning PowerWulf Cluster will help weather modeling analysis that benefit public safety and ongoing research

LAKE FOREST, CALIFORNIA (PRWEB) JULY 06, 2017

PSSC Labs, a developer of custom High Performance Computing (HPC) and Big Data computing solutions, today announced its work with Atmospheric Data Solutions, LLC (ADS) to provide powerful, turn-key HPC Cluster solutions for its weather modeling solutions.

Atmospheric Data Solutions works with various public and private agencies, including major utility providers, to develop atmospheric science products that help mitigate and manage risk from severe weather and future climate change. The weather modeling solutions that ADS create include high impact weather forecast guidance products, tailored regional wildfire forecast guidance products, and utility load and outage forecasts – all requiring analysis of a large quantity of data that demands high performance computing to maximize accuracy and maximize the number of times models can be run daily.

PSSC Labs will work with ADS to provide powerful and customized supercomputing solutions for their weather modeling products, maximizing performance while staying within the budgetary constraints of each organization utilizing the end product. In addition to deploying PSSC Lab’s PowerWulf Clusters, ADS works with PSSC Labs to ensure the installation of custom modeling software on all HPC solutions, providing a truly turn key solution that is delivered ready to use.

The PowerWulf Cluster consists of 768 Intel Xeon Processor Cores, 4 Nvidia Tesla GPU Adapters, 2.1 TB System Memory, and 40TB+ Storage, all connected via Mellanox InfiniBand Interconnects, with additional configurations available. The PowerWulf Cluster includes PSSC Labs’ CBeST Cluster Management Toolkit to simplify the management, monitoring and maintenance. PSSC Labs will continue to support the HPC Cluster by providing operating system upgrades and continued system maintenance.

“PSSC Labs was accommodating every step of the way, whether it was finding the best hardware configuration within our client’s budget or allowing our own engineers on site to work on the clusters before delivery,” said Scott Capps, Principal and Founder of ADS. “The result is that our clients can now run models four times a day, as opposed to only twice a day with previous HPC set ups, with the results from the models delivered faster, as well.”

PSSC Labs’ PowerWulf HPC Cluster offer a reliable, flexible, high performance computing platform for a variety of applications in the following verticals: Design & Engineering, Life Sciences, Physical Science, Financial Services and Machine/Deep Learning.

Every PowerWulf HPC Cluster includes a three-year unlimited phone / email support package (additional year support available) with all support provided by their US based team of experienced engineers. Prices for a custom built PowerWulf HPC Cluster solution start at $20,000. For more information, see https://www.site-a.com/solutions/hpc-cluster/

Source: http://www.prweb.com/releases/2017/07/prweb14478281.htm