Publication: Weather Data Grids for Agriculture Risk Management : The Case of Honduras and Guatemala
One of the major constraints for the improvement of agricultural risk management in Central America, and in particular to the development of weather index-based insurance, is the availability of complete meteorological data. Limitations with the data are related to restrictions in weather station coverage (density), and problems with the quality (errors and gaps in the information) and availability of historical records. This paper evaluates the reconstruction of historical meteorological records with gridded datasets for Honduras and Guatemala1 using the methodology in Uribe Alcantara et al. (2009).The reconstruction with synthetic series is implemented by replacing missing observations with estimations from regular grids (or gridded analyses). The development of synthetic series proposed here will facilitate, among other potential uses, the implementation of risk analysis in insurance contracts where meteorological information is limited or incomplete. This paper is organized in four sections. Section one describes the conceptual approach and methods implemented for the evaluation of the data and the development of the gridded analysis. Section two describes the results of the implementation of the gridded analysis for Honduras and Guatemala. Section three provides a brief description of possible applications of the regular grids for the development of weather insurance contracts. Section four summarizes the main conclusions.
Link to Data Set
“World Bank. 2013. Weather Data Grids for Agriculture Risk Management : The Case of Honduras and Guatemala. © Washington, DC. http://hdl.handle.net/10986/16501 License: CC BY-NC-ND 3.0 IGO.”