Interpolating gridded datasets in R: UV-B data

In my most recent published paper, I analysed the effects of incoming solar UV-B radiation on the geochemistry of Atlas cedar pollen, focused on the Middle Atlas Mountains in Morocco. The study area was relatively small, with sample sites fairly close together.

The UV-B data was obtained from the glUV: Global UV-B radiation dataset, which combines data from NASA's Ozone Monitoring Instrument (OMI) onboard the Aura spacecraft, into grid cells containing average erythemally weighted estimates of daily UV-B radiation. You can read full details of the methods used in the associated research paper (Beckmann et al. 2014) (Available open access).

Gridded datasets are an excellent source of data for doing global or macro-scale studies. However, if working in a relatively small area, you may find that your study area is covered by just a few grid cells due to the often low resolution of gridded data. And this can sometimes make it more difficult to carry out analysis.

To overcome the problem, you can interpolate the data to increase the resolution. After interpolation, the gridded data will go from looking like the image on the left, to looking like the image on the right, which is much more detailed for the study area.

Read on to find out how to do this in R!

How pollen geochemistry can tell us about historic UV-B levels

Pleased to see that my latest research paper is now available online at The Holocene. Thanks to all of my co-authors: Will Fletcher, Pete Ryan, Alistair Seddon, Roy Wogelius and Rachid Ilmen, and thanks to the reviewers for their feedback. The paper and all associated research data is available for free and is open access. The data can also be accessed for free from Mendeley Data:

This research investigates the pollen geochemistry of Atlas cedar, and what it could tell us about incoming Ultraviolet-B radiation (UV-B) on historic timescales in North Africa.

So, what is pollen? what is pollen geochemistry? what is UV-B? and why is any of this important?

Read on to understand this research in plain English!