Satellite data validation: a parametrization of the natural variability of atmospheric mixing ratios

High-resolution model data are used to estimate the statistically typical mixing ratio variabilities of trace species as a function of distance and time separation. These estimates can be used to explain the fact that some of the differences between observations made with different observing systems are due to the less-than-perfect co-location of the measurements. The variability function is approximated by a two-parameter regression function, and lookup tables of the natural variability values as a function of distance separation and time separation are provided. In addition, a reparametrization of the variability values as a function of latitudinal gradients is proposed, and the seasonal independence of the linear approximation of such a function is demonstrated.

Automated summary

This study uses high-resolution model data to investigate the impact of distance and time separation on the variability of trace species' mixing ratios. The results show that the differences between observations are primarily caused by imperfect co-location of the measurements. The variability function is approximated using a regression function with two parameters and lookup tables are provided. A reparametrization of the variability values based on latitudinal gradients is proposed, and the seasonal independence of this function is demonstrated.