Uncertainty in Long-Term Atmospheric Data Records from MSU and AMSU

Abstract:

The temperature of the Earth’s atmosphere has been continuously observed by satellite-borne microwave sounders since late 1978. These measurements, made by the Microwave Sounding Units (MSUs) and the Advanced Microwave Sounding Units (AMSUs) yield one of the longest truly global records of Earth’s climate. To be useful for climate studies, measurements made by different satellites and satellite systems need to be merged into a single long-term dataset. Before and during the merging process, a number of adjustments made to the satellite measurements. These adjustments are intended to account for issues such as calibration drifts or changes in local measurement time. Because the adjustments are made with imperfect knowledge, they are therefore not likely to reduce errors to zero, and thus introduce uncertainty into the resulting long-term data record. In this presentation, we will discuss a Monte-Carlo-based approach to calculating and describing the effects of these uncertainty sources on the final merged dataset. The result of our uncertainty analysis is an ensemble of possible datasets, with the applied adjustments varied within reasonable bounds, and other error sources such as sampling noise taken into account. The ensemble approach makes it easy for the user community to assess the effects of uncertainty on their work by simply repeating their analysis for each ensemble member.