Task three aims to optimize the design of a carbon cycle observation system for Africa. It does this by considering the cost and accuracy attributes of the available sensors, the existing sensor network, and the optimal location of new sensors of various types, in order to minimize the uncertainty for a given cost, or minimize the cost for a given uncertainty.
Task 3.1 involves information gathering. Subtask 3.1.1 gathers information about existing and planned carbon cycle observation networks in Africa, by reviewing the published and grey literature and web searches, guided by the knowledge of SEACRIFOG participants. For each network, it records the start date, current status, sensors deployed and variables capture.
Subtask 3.1.2 surveys the technical literature to establish the price and performance specifications of the various sensor approaches applied in Africa and elsewhere to the measurement of key carbon cycle variables.
Task 3.2 applies two techniques to design an optimized network. Subtask 3.2.1 uses an approach designed for planning least cost energy generation systems, by adding least cost technologies to an existing network, while satisfying given performance requirements. For instance, there is usually an optimum mix of low cost but relatively imprecise sensors, with a high cost, high-precision sensors. The approach is applied to all the key carbon cycle variables, noting any synergies involved – for instance, some sensor packages deliver more than one variable.
Subtask 3.2.2 asks where new sensors should be located in order to reduce the uncertainty in the overall system by the largest amount. It runs a model of a carbon dioxide flux and transport in reverse, constrained by existing observations, to determine the location for the next sensor that reduces overall uncertainty the most. It continues this process until a given level of accuracy is reached. Locations can be excluded as being impractical, or the effects of moving them a small distance to a more practical location can be explored.