Remote Sensing (Jul 2024)
Seasonal Variability in the Relationship between the Volume-Scattering Function at 180° and the Backscattering Coefficient Observed from Spaceborne Lidar and Biogeochemical Argo (BGC-Argo) Floats
Abstract
The derivation of the particulate-backscattering coefficient (bbp) from Lidar signals is highly influenced by the parameter χp(π), which is defined by χp(π) = bbp/(2πβp(π)). This parameter facilitates the correlation of the particulate-volume-scattering function at 180°, denoted βp(π), with bbp. However, studies exploring the global and seasonal fluctuations of χp(π) remain sparse, largely due to measurement difficulties of βp(π) in the field conditions. This study pioneers the global data collection for χp(π), integrating bbp observations from Biogeochemical Argo (BGC-Argo) floats and βp(π) data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar. Our findings indicate that χp(π) experiences significant seasonal differences globally, peaking during summer and nadiring in winter. The global average χp(π) was calculated as 0.40, 0.48, 0.43, and 0.35 during spring, summer, autumn, and winter, respectively. The daytime values of χp(π) slightly exceeded those registered at night. To illuminate the seasonal variations in χp(π) in 26 sea regions worldwide, we deployed passive ocean color data MODIS bbp and active remote sensing data CALIOP βp(π), distinguishing three primary seasonal change patterns—the “summer peak”, the “decline”, and the “autumn pole”—with the “summer peak” typology being the most common. Post recalibration of the CALIOP bbp product considering seasonal χp(π) variations, we observed substantial statistical improvements. Specifically, the coefficient of determination (R2) markedly improved from 0.84 to 0.89, while the root mean square error (RMSE) declined from 4.0 × 10−4 m−1 to 3.0 × 10−4 m−1. Concurrently, the mean absolute percentage error (MAPE) also dropped significantly, from 31.48% to 25.27%.
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