I've found it useful (and interesting) to study the climatological normals for locations around the world, and I have shared a number of charts containing this information at climate.asianturfgrass.com.

One of the most useful plots for me is one that shows the combination of temperature and sunshine hours (light) throughout the year. Turfgrass managers have some control over nitrogen supply and plant water status, but they can't do much to modify temperature or sunshine. Therefore, turf growth is influenced by those factors, and we can compare locations by plotting light and temperature.

For example, we can see in this chart that Raleigh has similar temperature to Tokyo, although it gets slightly colder in winter at Raleigh and slightly warmer in Tokyo during summer. However, when it comes to light, Raleigh averages about 8 hours of sunshine during summer; in Tokyo the summer sunshine is 6 hours or less. Does this have some influence on ultradwarf bermudagrass performance and management? I think it must.

These are interactive charts, and one can modify which data are displayed. In this chart, I've looked at Atlanta and Tokyo, but now I've plotted C₄ growth potential (GP) against daily sunshine. One can see that the sun in Atlanta is more than 8 hours a day when growth potential is at its peak. In Tokyo the GP gets higher than it does in Atlanta but the light is 50 to 75% of that available in Atlanta.

This guide to customizing the charts shows all the options, where one can click, and what can be changed at that tab.

So we could, for example, show temperature plotted against growth potential to get an idea of how growth potential changes with temperature. And we can scroll through for each day of the year, and we can choose which cities if any are to be highlighted.

We could also show that as a bar chart, again setting the display for any date in the year.

To really make things complicated, have a look at these data as shown on a line chart.

The moving charts at climate.asianturfgrass.com were made using the googleVis package in R. Static charts were produced using the ggplot2 package. Climatological normals data shown on the charts are from the WMO data, or from national meteorological services. The Hong Kong Observatory have an easy-to-use website with climatological normals data from the WMO embedded for many world cities.