The Challenge Programme on Water and Food of the Consultative Group on International Agricultural Research (CGIAR) has as one of its goals: “To undertake research to improve basic and applied knowledge on how policies, institutions, and processes of change in the global and national food and water system affect food security, livelihoods, health, and the environment “ and two of their research questions as follows:

1. How will changes in global water cycles affect food production and change the ways in which the poor, women and disadvantaged groups access ecosystem services?

2. How can global and national policies and institutions prevent or mitigate the negative impacts of changes in global water cycles on water and food security and on the livelihoods of the poor, women and the socially excluded?

To date almost all continental and global scale analyses of the water resources, agricultural and environmental systems have been based on global climatic data sets at the 0.5 by 0.5 degree gridded MONTHLY times series. A growing body of literature shows that agriculture particularly rain fed crops require daily data to accurately model water stress (droughts and floods). While some river floods are on the monthly scale, most are of the scale of daily to weekly and aquatic ecosystem systems are quite vulnerable to episodic water quality events, hourly to daily, as well as chronic exposures. The authors have recently developed a set of global water resources, agricultural and environmental system models that addresses these temporal data demands, and analyze the bio-physical and economic impacts of global change in the short and long-term (climate change). Model results from a suite of numerical experiments show significant differences in regions of the globe where rainfall demonstrates a high degree of variability between storm arrival times and under certain soil conditions. The paper will present global results of both biophysical and economic impacts and discuss the benefits of temporal downscaling of climate data.