Meet Michael Peterson

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Thursday, May 26, 2016

Michael is a current post-doc with HAO since 2014 in a joint appointment with RAL. He works with Art Richmond, Wiebke Deierling, and others at HAO, CISL, CU Boulder, Penneylvania State, and the UCAR Center for Science Education as part of the NSF Frontiers in Earth System Dynamics (FESD) Electrical Connections and Consequences Within the Earth System (ECCWES) collaboration. This five-year interdisciplinary project aims to create a 3D modeling framework that can represent the entire electrical system of the planet from the surface to the Ionosphere.

Michael Peterson image
Fishing in the shadow of Mt. Fuji.

Michael’s background in satellite remote sensing helps to bring an observational component to this project. As part of his doctoral work, he developed a retrieval algorithm that can compute electrical inputs from global passive microwave observations. This algorithm models electrically active clouds as a collection of charges whose strengths and locations/altitudes are determined by the observed structure of the storm. It then uses basic electrostatics to compute the electric fields and conducting currents that would result from such a cloud based on validation data taken by high-altitude aircraft. As passive microwave observations are available globally, this algorithm makes it possible to calculate the total electrical current input into the system from electrified weather across the planet.

Michael Peterson image
Skiing in a snowstorm.

Due to his satellite background, he is also interested in data science and the challenges posed by Big Data. As the meteorological record expands and becomes increasingly distributed across data centers across the country and around the world, it can be difficult to keep tabs on what datasets are available, let alone acquire and work with them. To this end, he has developed a geoinformatics software that is built specifically for geoscientific methods and standards and launched a website called The Weather Archive ( that aims to make science data useful to a diverse userbase. Using a simple modern web browser, users can interact with petabytes of scientific data and perform powerful analyses that are typically the domain of desktop software that include arbitrary cross sections, differences, and soundings. This work has recently been recognized as a finalist in both the 2015 NSF Visualization Challenge (the “Vizzies”) and Vaisala Open Weather Data Challenge.

Michael has always been interested in meteorology growing up in Minnesota and experiencing both severe weather in the summer and harsh winters near the Canadian border. Outside of his research and development work, he is exploring applications of emerging technologies such as 3D printing, systems-on-a-chip, and radio controlled or autonomous/semi-autonomous platforms for science, education, and outreach. He has built a prototype mobile submersible instrument platform that can sample the lakes in northern Minnesota where he likes to fish to provide additional information about their ecology beyond “surface-based in-situ baited sampling.” He is currently reaching the end of his time at HAO and is considering where to go next after NCAR.