Though the term "aridity" becomes a misnomer, the Aridity Index (AI) is defined as the subtraction of weekly maximum temperature's departure from average from weekly precipitation's departure from average. This definition gives a negative (positive) value when the weather is warm and dry (cool and wet). Because warmer and drier than average weather tends to have a negative effect on the corn yield, the slope that occurs when corn yield deviation from trend is plotted against AI generally appears positive and allows users to associate AI less than zero with a better chance for poor yield.
For a growing season, two main items should allow for meaningful dissemination of AI information via a World Wide Web site (http://www.mesonet.agron.iastate.edu/~windmill/AIpage.html). Maps of the current week's accumulation of AI will display the spatial extent of weather warmer and drier or cooler and wetter than average. The other important item is a display of the sequential sample for each district. Such a display would allow users to follow what the AI has been doing in their district and to anticipate what level it might end up at. The display of the spatial distribution of AI is a good application for Geographic Information Systems (GIS). Using GIS allows for fast updates of the AI map for the current growing season. As for the sequential sample displays, there were 85 Midwest districts studied and it would be awkward to produce 85 time series charts each week. An alternative would be to set up the map so that each district has a link to an automatically generated chart. Automatic chart generation has been accomplished with JpGraph 1.6.3 (http://www.aditus.nu/jpgraph/). Methodology, results, and an operational 2002 product are provided on the site.
Supplementary URL: http://www.mesonet.agron.iastate.edu/~windmill/AIpage.html