Appel à projets du programme de recherche CGIAR sur le changement climatique, l'agriculture et la sécurité alimentaire.

The objective of this call is to develop or adapt methods for reconstructing spatially- and temporally-complete, historic series of agriculturally-important meteorological variables on a daily time step, by combining available station observations with proxy data; and to evaluate daily historic meteorological data sets for the CCAFS focus regions of East and West Africa. Following the initial proof-of-concept study under this call, CCAFS hopes to secure additional resources to work with collaborating African national meteorological services to apply the methodology with their own station data, to develop and evaluate spatially- and temporally-complete gridded meteorological data sets for agricultural risk management and climate adaptation applications. An initial CCAFS-sponsored project has developed and is testing methods to reconstruct a 28-year time series of gridded (≤ 10 km) historic rainfall on a daily time step, by combining historic station observations with satellite thermal images. This call seeks to extend that work to other meteorological variables that are important for agriculture and needed for agricultural simulation modeling. 

The project will develop or adapt methods for reconstructing spatially- and temporally-complete, historic series of agriculturally-important meteorological variables, other than precipitation, on a daily time step, by combining or calibrating proxy data (e.g., remote sensing, climate model reanalysis) with available station observations; and demonstrate and evaluate resulting data sets within the CCAFS focus regions of East and West Africa. The desired variables are daily maximum and minimum temperature (required), solar irradiance; and either potential evapotranspiration, or the additional variables (dewpoint or humidity, and wind) needed to calculate potential evapotranspiration by the Penman-Monteith formula. The project will produce sufficient derived data to demonstrate the feasibility, accuracy and utility of the methodology. The project should demonstrate the ability to produce derived data that are compatible with ongoing work on precipitation, including:

Complete spatial coverage feasible over Eastern and West Africa;Temporal completeness and homogeneity for at-least 28 years;Spatial resolution no coarser than 10 km;Feasibility of combining or calibrating with the full set of station observations;Feasibility of updating with new station observations and proxy estimates.

The project will:

• Either develop and apply new methods, or apply existing methods, to combine proxy data with station observations on a daily time step.
• Identify and secure raw data sets used to estimate temperature and other relevant variables.
• Identify, secure and confirm quality of historic station data to evaluate derived data.
• Evaluate the accuracy of the derived data using sound statistical methodology.
• Evaluate the impact of the derived data on accuracy and bias of crop simulation results.

Required project outputs are a report, algorithms or software to apply the methodology, set(s) of gridded data calibrated/combined with station observations. The project report will include:

• Description of the proxy and validation data sets used. Full description of the methodology.
• Results of evaluation in terms of accuracy, and impact on crop simulation results.

Evaluation can be based on station observations anywhere in Eastern or West Africa, but evaluation in Ethiopia or the CILSS countries of West Africa is preferred for consistency with ongoing work on precipitation data.

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