About Me
Education
Graduate Education
- PhD, The Pennsylvania State University, Meteorology, 2015
- Advisor: Raymond Najjar
- Disertation Title: New Methods in Wavelet Analysis and Their Application to the Understanding of Hydroclimate Variability in the mid-Atlantic Region of the United States
- Email: jschulte12ATyahoo.com
Undergraduate Education
- Kean University
- B.S in meteorology with a minor in mathematics, 2010
- Advisor: Shing Yo
- Magna Cum Laude
More information about my educational history can be found in my CV
Employment History
2018-2019 - Science Systems and Applications, INC
My research while working as a research scientist at Science Systems and Applications, INC focused on the Indian Monsoon and wavelet analysis. This research was part of the SERVIR project and was supported by the NASA Applied Sciences Program Award (Award Number: NX16AN38G). I used wavelet analysis to test the hypothesis that interdecadal changes in the ENSO-Indian rainfall are related to the occurrence of ENSO flavors. I also used other new ENSO metrics to test the same hypothesis. The preliminary results supported a connection between ENSO flavors and changes in the ENSO-Indian rainfall relationship, suggesting that such changes are not solely related to noise.
2015-2017 - Stevens Institute of Technology
As a post-doctoral researcher at the Stevens Institute of Technology, I worked on several different projects under the supervision of Nickitas Georgas. The first project called Analyzing History to Project and Manage the Future was funded by the Long Island Sound Study. My role in this project was to understand the key teleconnection patterns governing the salinity and temperature variability of the Long Island Sound. This work resulted in the identification of a key teleconnection pattern called the EP/NP pattern that influences water temperature across the Long Island Sound. A new dipole index was created to quantify the evolution of this pattern.
My research as a postdoctoral scientist also included the development and operational implementation of new ensemble forecasting methods. More specifically, I developed new methods called phase-aware ensemble methods that remedy some of the drawbacks of traditional ensemble forecasting metrics such as the ensemble mean. I also studied the impact of ensemble clustering on storm surge forecasts. The new methods were operationally implemented and improved total water (surge and tide) forecasts produced from the New York Harbor Observing System (NYHOPS) model.