I've downloaded a series of weather observations from the local weather agency - it comprises around 1,000 points spread non-uniformly across Australia, with a greater density of points located near populated areas.
I'm interested in displaying mean temperatures and monthly rainfall (separately) as smooth surfaces, so I used the Kriging function in Spatial Analyst (with the default values) to calculate this grid:
The grids will be used for visualisation purposes only. In a web map I'll display the grids to give context, but will only allow identify on the actual weather stations, in which case I'll show the original values. I guess this means the accuracy of the grids isn't of paramount importance.
- Which of the parameters on the Kriging tool do I need to understand, in order to create meaningful interpolations of rainfall, temperature and other weather factors?
- Do I need to account for effects of topography (eg, orographic rain effect) or does the kriging algorithm handle this?
- is the Geostatistical Analyst a better tool for this type of analysis? (I believe it's designed to handle biases due to geography)
- anything else I should be aware of to create a meaningful result?