JPSS-1: The Next-Generation Weather Satellite that Provides Advanced Weather Forecasts

Joint Polar Satellite System 1 (JPSS-1), is the first among the four NOAA’s (National Oceanic and Atmospheric Administration) series of operational environmental satellites that provides advanced weather prediction and environmental monitoring. JPSS-1 is designed to take global measurements of atmospheric, land and sea conditions, and monitoring environmental changes that will help predict weather forecast. It circles the earth fourteen times a day from pole to pole making observations that will help predict severe weather events several days beforehand. With the launch of JPSS-1 in the polar orbit we can now be assured of an improved three-to-seven-day advanced forecasts.

JPSS-1 uses the most sophisticated satellite instrumentation having a six-time increased global observation resolution to monitor and report a wide range of environmental information. Its ability to see through cloud cover enables JPSS-1 to map precipitation, ice and snow cover, humidity and temperature, and even look beneath storms to sound a more accurate advanced warning in the event of hurricanes, tornadoes and blizzards. Alongside, it will closely monitor the weather parameters that affect the vegetation impacting our crops that provide us food. JPSS-1 also assesses hazards such as droughts, forest fires, volcanic eruption, floods, poor air quality, ozone concentration and coastal water levels. With a high resolution Visible Infrared Imaging Radiometer Suite (VIIRS), JPSS-1 can pinpoint the center of the hurricane which is very much essential when arriving at the hurricane models.

What is of prime importance to us is how the JPSS-1 is able to provide the long duration seven-day advanced weather forecasts. Accuracy of these weather forecasts are critical as they play a central role in preparedness and capacity planning for various companies and governmental entities, including electric and gas utilities, and transportation companies. It is also essential to understand the relationship between a company’s infrastructure and their service capabilities under different weather conditions. Weather forecasted by JPSS-1 becomes all the more important as many of these companies have a critical need to know the forecast or how bad the weather will be 1-6 days out and in some cases even longer duration, so as to plan-out their internal exercises.

Macrosoft’s proprietary Mine-Weather platform provides the framework for companies to perform their own independent analysis on the accuracy of weather forecasts they rely on. What is more important for clients is doing evaluation for the specific types of weather events. It is here that the weather forecast services provided by JPSS-1 is of particular interest to us. Mine-Weather compares the forecasted data with the actual data using a set of scoring algorithms to determine the accuracy of the forecasted data. As the forecasted data will be provided from JPSS-1 we can be assured that the differential with the actual data will be minimal which is crucial for the performance of Mine-Weather.

Independent evaluation of how good specific weather forecasts are in the face of different type of weather events are important to a particular company. So, what companies require is not the overall weather forecast accuracy over a period, but rather the data quality of the forecast for a specific weather variable and within certain ranges of a weather variable most important to a specific company.

Mine-Weather allows clients to segment out the specific time periods and weather variables of interest. With JPSS-1 one can be assured of a more accurate forecast data essential for clients to probe the accuracy of the forecasts for these specific segments. Please go through our White Papers to learn more about the advanced capabilities Mine-Weather offers and how it will benefit clients in assessing the accuracy of outage prediction models.

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About the Author

Dr. Ronald Mueller

Ron is CEO and Founder of Macrosoft, Inc.. Ron heads up all company strategic activities, and directs day-to-day work of the Leadership Team at Macrosoft. Ron is also Macrosoft’s Chief Scientist, defining and structuring Macrosoft’s path forward on new technologies and products, such as Cloud; Big Data; and AI. Ron has a Ph.D. in Theoretical Physics from New York University, and worked in physics for over a decade at Yale University, The Fusion Energy Institute in Princeton, NJ, and at Argonne National Laboratory. Ron also worked at Bell Laboratories in Murray Hill, NJ., where he managed a group on Big Data, including very early work on neural networks. Ron has a career-long passion in ultra-large-scale data processing and analysis including: predictive analytics; data mining, machine learning and neural networks.

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