Assessments of agricultural productivity and food security require process-based crop models to provide predictions of yields and diagnose past variations in the context of anthropogenic and climate factors. These models need detailed meteorological data as input, including precipitation, temperature, humidity, solar radiation and windspeed. This project aimed to apply existing methods to merge in situ, remotely sensed and modeled data sources in East and West Africa to produce high-quality daily meteorological data over at least 30 years. Specific objectives included: evaluation of the error structure of the dataset, its temporal and spatial characteristics and consistency and its suitability for forcing crop models, and to provide a framework for merging new data, in particular from the local stations of regional African partners, ensuring consistency across time and space and among variables, as well as the best use of information.
The work successfully created a 10 kilometre, daily meteorological dataset for East and West Africa for the period 1979–2008, based on the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP–NCAR) reanalysis (NNR), merged with observational datasets, including the monthly gridded precipitation and temperature product of the University of East Anglia’s Climate Research Unit (CRU), the NASA Langley Surface Radiation Budget (SRB) product, and station data from the Global Summary of the Day (GSOD) database.
Sheffield, J.; Chaney, N.W. Developing high-quality meteorological data for East and West Africa from merged sources. CCAFS Working Paper No. 45. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Copenhagen, Denmark (2013) 38 pp.