The increasing availability of gridded, high-resolution, multivariate climatological data sets calls for innovative approaches to visualize inter-variable relations. In this study, we present a methodology, based on properties of common colour schemes, to plot two variables in a single colour map by using a two-dimensional colour legend for both sequential and diverging data. This is especially suited for climate data as the spatial distribution of the relation between different variables is often as important as the distribution of variables individually. Two example applications are given to illustrate the use of the method: one that shows the global distribution of climate based on observed temperature and relative humidity, and the other showing the distribution of recent changes in observed temperature and precipitation over Europe. A flexible and easy-to-implement method is provided to construct different colour legends for sequential and diverging data.