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Exploring Sensitivity of Infrasound Signal Predictions to Atmospheric Inputs

Description: 

Accurately predicting infrasound propagation and interpreting signal detections rely on robust atmospheric specifications. Disparities between observed signals and model predictions often manifest as unexpected detections, undetected signals, or mismatches in travel times and source directions. These challenges emphasize the importance of understanding the sensitivity of propagation models to variations in atmospheric inputs. The current de facto source of atmospheric data (G2S) provides geographically and temporally averaged specifications. However, radiosondes collect data at specific times and locations that may be more accurate. This study investigates how incorporating atmospheric data collected by radiosondes influences the accuracy of model predictions. Seasonal and diurnal variations, along with other atmospheric factors, are considered in evaluating the sensitivity of model outputs. The results will be discussed to assess how such detailed measurements influence predictive accuracy and what implications this has for the broader field of infrasound monitoring. We will also discuss the potential value of integrating radiosonde measurements into modeling efforts. This work aims to provide a foundation for improving infrasound propagation predictions, thereby advancing the reliability of infrasound applications in diverse applications.

Session: Data-driven and Computational Characterization of Non-earthquake Seismoacoustic Sources [Poster]

Type: Poster

Date: 4/16/2025

Presentation Time: 08:00 AM (local time)

Presenting Author: Loring

Student Presenter: No

Invited Presentation: 

Poster Number: 82

Authors