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Retrieving tropospheric temperature and humidity profiles over the ocean using buoy-based microwave radiometers
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DOI：10.5194/amt-19-4121-2026.png)
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Abstract
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Abstract. The acquisition of atmospheric temperature and humidity profiles over the sea is strategically vital for meteorological forecasting; marine monitoring; and national security. Achieving their real-time; stable; and routine retrieval under complex sea conditions is a critical and urgent challenge. Traditional retrieval methods rely heavily on large historical datasets. However; marine sounding stations are sparse; making data acquisition challenging. Ground-based microwave radiometers offer a unique capability for continuous; all-weather remote sensing of atmospheric thermal emission; enabling routine retrieval of temperature and humidity profiles over oceanic regions. Meanwhile; buoy platforms experience wave disturbance; causing real-time variations in zenith angle observations. Without correction; this induces significant random errors in target brightness temperature. To address these issues; this paper proposes a collaborative retrieval method. This method does not rely on large-scale historical datasets for model training and integrates platform attitude information. Our approach uses a multi-objective genetic algorithm to construct a small-scale joint prior database based on a limited amount of local radiosonde data; which serves only as an initial physical constraint for the retrieval process. It also incorporates an attitude error correction model; an empirical pressure-altitude equation; and a parallel optimization strategy. This thereby reduces dependence on extensive historical datasets. It also effectively mitigates attitude-induced brightness-temperature deviation; enhances computational efficiency; and enables real-time; routine retrieval of marine atmospheric profiles. Simulation experiments and field tests in Qingdao's Jiaozhou Bay confirm the results. Under sparse-data conditions; the temperature RMSE is 4.11 K before systematic bias correction and 2.13 K after correction; while the relative-humidity RMSE is 24.09 % before correction and 21.42 % after correction. A single static bias correction profile is proposed for operational deployment; which achieves performance comparable to the cross-validation results. This validates the method's stability and applicability in real marine environments. This research provides a potentially practical pathway for ocean areas with sparse radiosondes for real-time; stable; and routine detection of marine atmospheric parameters.
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