Monitoring atmospheric composition & climate
Input-Data Cluster

The Input-Data cluster comprises four largely independent sub-projects (D-INSITU, D-SAT, D-EMIS and D-FIRE) characterised by their role of providing the other clusters of MACC with observations of atmospheric composition and estimates of emissions, as illustrated schematically below. Although the diagram mirrors the functional architecture of MACC, there is not a complete one-to-one link between the activities within a particular cluster and the corresponding functional area, because activities are grouped into components and clusters primarily for effective management of the work.

MACC Clusters

The data flow through the four MACC Clusters

The D-INSITU and D-SAT sub-projects acquire those near-real-time in-situ and satellite data that are not already provided through the mechanisms established for numerical weather prediction. Data available only in delayed mode and reprocessed versions of data originally acquired in near-real-time are also acquired for use in MACC’s delayed-mode and reanalysis production streams. Wherever possible these sub-projects utilize or build on existing mechanisms to achieve their goals. The sub-projects include the preprocessing, such as data reformatting, needed to facilitate the subsequent use of the data in MACC. D-SAT also includes the provision of some satellite data retrievals for which established standard products are not available from another source. Other retrieval work in MACC is carried out within the GLOBAL cluster.

Anthropogenic emission datasets are being harmonised and evaluated within the D-EMIS sub-project. Methods for regular updating of emissions are developed, and work is also devoted to improvement of historical datasets for use in reanalysis and trend analysis. Parametrizations for natural emissions are adopted and evaluated in collaboration with the modelling sub-projects. Fire emissions are considered separately in sub-project D-FIRE, which implemens and develops further a near-real-time system to determine current fire conditions and associated emissions. The system is based on use of active-fire and fire-radiative-power products derived from satellite observations and use of vegetation modelling.