In the last several decades there has been a rapid development in the number of sophisticated environmental monitoring networks. As a result, a huge stream of data is available, but screening and analysis of this data have become increasingly problematic. Using data on atmospheric concentrations of CO2 as an example, we show how mathematical modeling can help to organize this stream of data and to uncover important trends hidden in the natural inherent variations of the system.