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Abstract

The mixing height is a key parameter for many applications that relate surface–atmosphere exchange fluxes to atmospheric mixing ratios, e.g. in atmospheric transport modeling of pollutants. The mixing height can be estimated with various methods: profile measurements from radiosondes as well as remote sensing (e.g. optical backscatter measurements). For quantitative applications, it is important to not only estimate the mixing height itself but also the uncertainty associated with this estimate. However, classical error propagation typically fails on mixing height estimates that use thresholds in vertical profiles of some measured or measurement-derived quantity. Therefore, we propose a method to estimate mixing height together with its uncertainty. The method relies on the concept of statistical confidence and on the knowledge of the measurement errors. It can also be applied to problems outside atmospheric mixing height retrievals where properties have to be assigned to a specific position, e.g. the location of a local extreme.