Congratulations!Successful Master’s Thesis Presentation by Meredith Avison

15 May 2025

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Meredith's thesis "Seasonal Predictability of Agriculturally Relevant Climate Extremes in the Central United States" was supervised by Dr. Leonard Borchert and Prof. Dr. Jana Sillmann.

The United States is the largest producer of corn in the world. Fifteen percent of this production is exported, which means disruptions in yield have a global impact. Yield disruptions have been associated with simultaneous heat extremes. It is possible to predict heat extremes in North America several months in advance with significant accuracy through seasonal climate prediction. Therefore, there is potential for these predictions to be an early warning for lower yields in the following year for corn farmers and agricultural decision makers. However, studies of heat extreme prediction in the United States have not explored their potential to provide critical information to corn producers. This project aims to fill this gap by assessing seasonal climate predictions of relevant heat extremes and determining sources of predictability to improve those predictions. Predictions of relevant climate extremes to corn production from the German Climate Forecasts Systems (GCFS) model ensemble showed poor skill and were not consistent enough to provide to users. However, this research identified a source of predictability for growing seasons with higher heat in the 500 hPa geopotential height wave pattern. During these growing seasons, members that have good skill predicting the number of heat days also showed a similar 500 hPa geopotential height pattern to reanalysis. Subselecting members by exploiting this fact and the connection between heat and the Pacific Decadal Oscillation improved heat prediction skill, specifically in temporal correlation. This susbselection also improved accuracy in identifying whether a growing season was more susceptible to these heat extremes relevant to corn production.