Climate science meets virtual reality
"It was a balmy 18 degrees in Masterton today..." When the TV weather presenter reports on the temperatures around the country, do you add a couple of degrees because you know that the climate of your location is typically warmer than Masterton?
This handy logic, called spatial interpolation, is probably something most of us use more often than we might realise.
It would be useful to have climate stations with long records of data everywhere they were needed. For obvious reasons this is impossible. However, using spatial interpolation techniques we can create "virtual" climate stations at almost any location on land in New Zealand. A systematic grid of these virtual stations across the country provides a base network of climate information to assist our understanding of climate related problems.
The virtual station data are estimated from actual data values recorded at about 300 climate stations throughout the country. The interpolation scheme takes into account the distance from the nearest recording sites and the topographic differences between the recording sites and the virtual station sites, for example, differences in elevation, aspect, slope, and distance from the sea.
The adjacent map shows the grid-pattern location of NIWA’s virtual climate stations (shown as red dots) in the Wairarapa. The grid points are about 5 km apart (actual spacing is 0.05° of latitude and longitude), and cover the entire country. Daily climate data have been calculated back to 1972 for most variables (rainfall goes back to 1960), and are updated every month (i.e., the data currently go up to the end of August 2005).
Maps and data derived from the virtual climate network for all New Zealand are available from NIWA.
So the next time the TV weather presenter says, "... with winds gusting to 100 km/h in Tapanui", you could know more accurately what that might mean for where you live.
Otago vineyard approaching harvest maturity. Temperature data interpolated from long-term climate sites to new orchard locations can provide estimates of historical variability in crop harvest dates. Cover photo: Steve LeGal