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 (sigma(50)) and 95th percentile (sigma(95)) values were calculated along the time dimension. An additional method, wavenumber spectral analysis (sigma(k)), was also employed to obtain a different but comparable estimate. ass and sigma(95) 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 (similar to 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. sigma(50), sigma(95), and sigma(k) 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.