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Sea Fog Microphysics and Visibility Retrieval Using a 94-GHz Millimeter-Wave Radar on an Uncrewed Surface Vehicle

Rui Shi,Cuina Li,Yong Lei,Yunong Guan,Yuxiao Zhang

Published 2026 in IEEE Transactions on Geoscience and Remote Sensing

ABSTRACT

Sea fog is a frequently occurring and potentially hazardous meteorological phenomenon. To better capture its dynamic characteristics within complex marine environments, this study conducted six cruise observation experiments off the eastern coast of Huangdao Station in Shandong Province by using a millimeter-wave cloud radar operating at a frequency of 94-GHz mounted on an uncrewed surface vehicle (USV). First, a comparative analysis was performed against the 35-GHz cloud radar installed at Huangdao Station to evaluate their capability in characterizing sea fog. The results showed that both radars were capable of detecting the vertical distribution of sea fog, while the 94-GHz millimeter-wave radar exhibited higher sensitivity to capture weak fog particles during in the early stage of fog formation. Subsequently, partial least squares structural equation modeling (PLS-SEM) was employed to investigate the relationships among key meteorological variables—forward visibility, relative humidity (RHU), air temperature, wind speed—and radar echo intensity. The analysis revealed a significant interrelationship among these variables, with a path coefficient of 0.72 for their collective influence on radar echo intensity. Radar echo intensity exhibited a significant positive response to RHU and a significant negative response to forward visibility ( $p \lt 0.001$ ). In addition, forward visibility was retrived using both the generalized additive model (GAM) and extreme gradient boosting (XGBoost). The results demonstrated that XGBoost achieved substantially higher predictive accuracy, with $R^{2} \gt 0.819$ . This indicates that XGBoost more effectively captures the dynamic variability of visibility within fog-affected marine environments.

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