The proposal needed a bit of extra back ground, so I searched up "inverse modelling", and discovered words like "Bayesian" and "Covariance Matrix" which were right up my alley. I discovered that this was the method used to get the estimates published by the IPCC (Intergovernmental Panel on Climate Change http://www.ipcc.ch/). Global estimates are derived from hundreds of stations around the world ... but they're not so evening distributed. And so I started my PhD journey.
|Map of atmospheric carbon dioxide monitoring stations around the world. From http://www.esrl.noaa.gov/gmd/dv/site/map1.php on the 14th of Feb 2013|
The goal of the proposed project was to increase the capacity to collect these sorts of measurements in South Africa, and ultimately to be able to increase the density of the network in South Africa. The intention is also not just to become a data provider to the scientific community, but to actively engage with the data, and be able to generate our own regional estimates from the atmospheric measurements.
Since the expertise already existed around the Cape Point Station, and from our group's experience with working with scientific technology, we knew that it would be crazy to try this on our own, we decided to focus in on Cape Town. Scientific measurement equipment rarely comes all neatly packaged in a box, which when opened, automatically deploys itself and works faultlessly for the rest of your days. If only it were so simple. Setting up the monitoring sites and getting the best possible measurements would be a challenge, but fortunately the team at the Cape Point Global Atmospheric Watch station were on hand to assist.
|The Cape Point Global Atmospheric Watch Station|
|A map of the Western Cape region in South Africa, with the yellow markers pointing out the Cape Point measurement station, as well as the new sites at Robben Island and Hangklip. Map generated using Google Earth earth.google.com|
|The Robben Island lighthouse - an ideal domicile for the measurement equipment|