Any scientific investigation requires data. Having more data points of higher resolution produces a more thorough and meaningful result. Perhaps you are familiar with the example of the blindfolded men trying to discover an elephant. One man feels the elephant’s trunk and thinks it is a snake. Another feels its leg and thinks it is a tree, and the third feels the tail and thinks it is a rope. Science is much the same way – adding more data points often produces a new conclusion, or helps reveal details or clues to processes and phenomena.
I mentioned previously that the Maricopa County Flood Control District receives data from many neighborhood rain gauges. In years past, a single weather station in each city and town recorded the official weather. Having such few weather stations limited what information could be gleaned from the data. When the weather stations in each town are far apart, considerable interpretation is needed to understand what is happening between stations. Neighborhood gauges help fill holes in the data map and allow for a more thorough understanding of a rain event. From the flood control district’s standpoint, having such a network of rain gauges helps them know how much rain is falling in certain areas, and manage storm water accordingly.
This weather station is at Osborn and 64th St in Scottsdale, ID #4605. Real-time data from this station is available from the Flood Control District’s website, and is free to the general public. Amateur weather watchers and other scientific entities can use this data to satisfy their curiosities or for their own studies. Automated data loggers record more than just weather. Real-time information about stream discharge, groundwater data, and even traffic is available in many areas.
Even with an expanded network of rain gauges, some studies require even higher resolution or an accurate measurement in a location that is too far from the nearest gauge. A former colleague of mine once used a simple data logging gauge similar to this one from Ben Meadows because knowing the exact rainfall amount in his study area was important. In his case, he wanted to know the effects of rainfall upon erosion for his particular study area, and the 3-mile difference in rainfall between the nearest gauge and his study area would have invalidated his conclusions.