I am currently grappling with situating a global phenomenon like clouds and atmosphere. This brought me to the difficulties in actually collecting these kinds of measurements. There are all sorts of gaps both spatially and temporally which complicates taking averages and looking at trends.
Studying the Science of Global Atmospheric Research
There are many problematic aspects of studying global phenomena, like atmospheric and oceanic temperatures, aerosols, and clouds. Many of the problems arise from data records that are inconsistent temporally and/or spatially. There can be a number of reasons for these inconsistencies. A common temporal problem is switching methodology of observations or switching instruments. It is very difficult to have a reliable long term record when the data comes from multiple sources. Artefacts and misleading trends are found in long term records when techniques have changed. Spatial problems in data collection comes in the form of data “holes” and geographic variation. Often data holes occur in developing regions where funding research is not a priority. They can also occur in places that are difficult to collect data at. Sometimes these issues can be resolved, but often not. This data is very important when looking at climate change and are encapsulated in climate models. Without reliable data, we have no chance in accurately representing future climate changes.