Impact of time window on estimating representativeness error in sea surface salinity data

Abstract

ABSTRACT Validating satellite data using buoys presents a significant challenge due to the differing spatial and temporal representativeness of these data sources. This discrepancy introduces two critical issues in satellite data validation: the selection of the matchup window during the collocation process and the estimation of representativeness error. While numerous studies have addressed these issues independently, research on their interaction remains limited. Utilizing quadruple Sea Surface Salinity (SSS) matchup datasets, this study investigates the impact of the time window on the estimation of SSS representativeness error between two satellite observations: SMOS and SMAP. Our results reveal a clear dependence of representativeness error on the selected time windows. In the global ocean, the variance of representativeness errors within a small time window is 0.040 psu2, which is substantially greater than that of the entire dataset (0.016 psu2). In contrast, the representativeness errors within larger time windows are systematically lower than those within smaller time windows. This research also finds that this dependency is not influenced by the randomness of the matchup data, climatological Sea Surface Salinity, or geographic locations. Instead, our findings suggest that the impact of the time window on representativeness error may reflect the characteristics of satellite data across different time intervals. Satellites are more likely to capture SSS signals within smaller time windows, resulting in larger representativeness errors when comparing satellite SSS with buoy measurements. Conversely, larger time windows lead to significant mismatches between satellite observations and hinder the ability of satellites to detect SSS signals, which can result in smaller or even reversed representativeness errors.