Sea surface salinity subfootprint variability estimates from regional high-resolution model simulations

Sea surface salinity (SSS) subfootprint variability (SFV) is estimated using high-resolution, realistically forced regional simulations of the Arabian Sea and western Pacific with an integration period of one year. A weighted standard deviation was calculated for footprint sizes of 100 km, 40 km, 20 km, and 10 km for all model time steps and then median (σ50) and 95th percentile (σ95) values were calculated along the time dimension. An additional method, wavenumber spectral analysis (σk), was also employed to obtain a different but comparable estimate. σ50 and σ95 maxima (>1 psu) are found in shallow waters along the continental shelves where strong river outflow is present. Open ocean values of both statistics are much lower (~0.1 psu). The wavenumber spectral analysis allowed the estimation of total SSS spatial variance over 640 km, which was then compared to the estimates obtained by integrating time-averaged SSS power spectral density (PSD) at wavelengths ≤100 km, 40 km, 20 km, and 10 km. For both geographic regions, the ratio of variance at and below each wavelength to the total variance across all estimated wavelengths is approximately 50%, 30%, 15%, and 5%, respectively. σ50, σ95, and σk magnitudes as a function of footprint size follow a power-law relationship. The observed strong decline in SSS SFV below 40 km suggests that the current effective resolution of the SMAP and SMOS satellites is advantageous for limiting the impact of SFV on the satellites' error budget. •Sea surface salinity subfootprint variability has strong geographic dependence.•The largest magnitudes are found along the continental shelves.•Deep ocean estimates are an order of magnitude lower.•A 40 km footprint neglects approximately 70% of the total spatial variance•The phenomenon has a power-law decay with decreasing footprint size.