Case Study: Johns Hopkins University Applied Physics Laboratory achieves enhanced data visibility and confident analysis with JMP

An atmospheric scientist recognizes the power of data visualization and analysis using JMP

Johns Hopkins University Applied Physics Laboratory needed a better way to process and analyze large meteorological data sets to understand how weather affects technology, temperature, and precipitation. Atmospheric scientist Rich Giannola turned to JMP software, using tools such as the Prediction Profiler, Distribution, Time Series, and Bubble Plot platforms to support his work on U.S. Navy programs and climate patterns like El Niño and La Niña.

With JMP, Johns Hopkins University Applied Physics Laboratory improved data visibility, validated laboratory testing with logistic regression, and used design of experiments to collect data more efficiently. JMP also helped Giannola analyze 61 years of El Niño/La Niña data, uncovering patterns such as El Niño occurring slightly more often and lasting shorter on average, while giving the team confidence that the results aligned well with NOAA and National Weather Service analyses.

Johns Hopkins University Applied Physics Laboratory

Rich Giannola

Atmospheric Scientist