Accuracy of radar interferometry is often hindered by the atmospheric phase screen (APS). To address this limitation, the geostatistical approach known as Kriging has been employed to predict APS from sparse observations for compensation purposes. In this article, we propose an enhanced Kriging approach to achieve more accurate APS predictions in ground-based radar interferometry applications. Specifically, the Kriging system is augmented with a time-series measure through correlation analysis, effectively leveraging spatio-temporal information for APS prediction. The validity of the introduced Kriging method in the APS compensation framework was tested with Ku-band ground-based radar datasets collected over two different mountainous sites. A comparison of this method with simple Kriging (SK) reveals a noticeable improvement in APS prediction accuracy and temporal phase stability.