COBECORE: recovering eco-climatological data from Belgian colonial archives.

5th International Conference on Re-Analysis

Koen Hufkens1, Kim Jacobsen2, Hans Beeckman2, Piet Stoffelen3, Filip Vandelook3, Jan Van den Bulcke4, Michael Amara5, Hans Verbeeck6

1Richardson Lab, Harvard University, 2Wood Biology Service, Royal Museum for Central Africa, 3Botanic Garden Meise, 4Laboratory of Wood Technology, Ghent University, 5State Archives Belgium, 6CAVElab Computational and Applied Vegetation Ecology, Ghent University

Predictions regarding the future climate and the state of African tropical forest remain uncertain in part due to a lack of legacy data which provides the necessary climatological and ecological context for current research in the Congo Basin. Even today, the central Congo Basin is currently represented by only a few rain gauges, limiting climate forecasts across the Congo Basin. This lack of long-term (historical) climatological data leaves the central Congo Basin spatially and temporally under-represented. However, old climate records could provide valuable information in support of climate re-analysis.

The historical archives of La régie des plantations de la colonie (REPCO) and the Institut National d’Etudes Agronomique du Congo Belge (INEAC), cover six decades (1901 - 1960). Located at the State Archives of Belgium, the Royal Museum for Central Africa and the Botanic Garden Meise, they hold vast amounts of (eco-) climatological data, with great potential and relevance for basic and applied research in the central Congo Basin. Their scientific value resides in the extent of the data collected in a region where the availability of reliable baseline measurements are practically absent. The COBECORE project aims to establish baseline climatological measurements, crucial for reanalysis, by valorizing climatological legacy data through computer vision, machine learning and citizen science approaches.

Here we report on the first half year of data recovery of the first part of some 589 climatological stations spread throughout the Congo Basin. We discuss progress made in the automation of data recovery and issues regarding transcription and provide a short overview of preliminary data products.