The use of radar to provide rainfall estimates is becoming more attractive, especially with the number of rain-gauges in operation reducing year on year in many countries. However, while radars give very good spatial representations of rainfall, they tend to underestimate rainfall when compared to rain-gauges, for the selected area. To improve the accuracy of radar estimates, they are usually adjusted by comparing the radar and rain-gauge estimates. Most of the adjustment methods consist of either using a value that may or may not vary with distance from the radar, or by varying the Z–R relationship. With the exception to the methods that involve varying the Z–R relationship, the effects of rainfall intensity on the adjustment factor are ignored. Two new methods that take into account the variability in the intensity of rainfall are proposed: one that varies the adjustment value based on discrete intensity bins and the other varies continuously. The proposed method is shown to be better than uniform adjustment in both calibration and validation in split-sample tests.