About ANUSPLIN

Method overview

Australian National University Spline¹ (ANUSPLIN) software comprises interpolation methods which can be used to create gridded observational datasets (“surfaces”) from station-based observations taken at irregularly spaced intervals. ANUSPLIN uses a curve fitting technique (thin plate smoothing splines), along with latitude, longitude and elevation information which allows the method to include the effect of topography effectively². ANUSPLIN has been used to produce the target dataset NRCANmet used in the downscaling of the CMIP5 and CMIP6 climate model ensembles to create CanDCS-U5 and CanDCS-U6, respectively.

How the method works

ANUSPLIN makes use of thin-plate smoothing splines³ to create a statistical model to transform climate variable information (e.g., temperature and precipitation) from the point locations of station observations to a gridded climate surface. 

The spline interpolation process utilises the correlations between the station location coordinates (latitude, longitude and elevation) and the values of the climate variable in question. Including the location’s elevation permits the calculation of the relationship between a particular climate variable and height (also known as the lapse rate). This relationship is then used to help infill information between station locations.

The interpolated climate “surface” is fitted automatically within the software so that the difference between the values of the gridded climate surface and those at the point locations is minimised. It can be thought of as similar to laying a blanket over a surface and adjusting it to fit more tightly in some locations (i.e., the weather station location) than others.

The resulting climate “surface” can be used with location and elevation information from a digital elevation model (DEM) to create gridded climate data at the same spatial resolution as the DEM.

When to use it

ANUSPLIN is an operationally efficient method to create spatially continuous surfaces of observation variables.

ANUSPLIN is useful for interpolating station observations of climate data. It is important that the latitude, longitude and elevation (if using) are accurately located.¹

Gridded climate data created using ANUSPLIN are more robust where the observing station network is dense. There will be less confidence in gridded data in areas where the station network is sparse, for example, in areas of northern Canada.

Observations which are interpolated using ANUSPLN, such as the dataset NRCANmet are used for a wide variety of applications across Canada.