The widely-used Global Positioning System (GPS) does not work underwater. This presents a severe limitation on the communication capabilities and deployment options for undersea assets such as AUVs and UUVs. To address this challenge, the Positioning System for Deep Ocean Navigation (POSYDON) program aims to develop an undersea system that provides omnipresent, robust positioning across ocean basins. To do so, it is critically important to accurately model sound waves and signals under diverse, and often uncertain, undersea environmental conditions. Probabilistic estimates of the four-dimensional variability of the fields of sound speed, salinity, temperature, and currents are thus needed. In this paper, we employ our MSEAS primitive-equation and error subspace data-assimilative ensemble ocean forecasting system during two real-time POSYDON sea exercises, one in winter 2017 and another in August 2018. We provide real-time high-resolution estimates of sound speed fields and their uncertainty, and describe the ocean conditions from submesoscales eddies and internal tides to warm core rings and larger-scale circulations. We verify our results against independent data of opportunity; in all cases, we show that our probabilistic forecasts demonstrate skill.