Global Climate Data

Geospatial Climate Data

In recent years, plot specific crop models have been adapted to national and regional scales to aid policy makers with agricultural decisions concerning climate change and the resulting effects on food security and future water demands.  These models are often constrained by data to represent geospatially variable inputs as homogeneous data.  The impact of these assumptions on model effectiveness is a function of the sensitivity of the input parameter to the model, the scale of data being aggregated, and the scale of the analysis.   The impact of aggregation of geospatially variable data at the regional level is loss of calibration and validation effectiveness and thus utility for most modeling efforts.  Regional cropping systems are highly heterogeneous and model inputs should reflect as much.  Considering the vast quantities of available input data, decisions must be made about desired spatial and temporal resolution, as well as the amount of generalizations that can be made about the study in question.  This project summarized many of the existing datasets for global climate parameters, as well soil and agricultural management variables, such as irrigation.

The Sustainability Consortium helped fund this project.

Contact:
Marty Matlock, 479-575-2849, mmatlock@uark.edu