We estimated the surface uplift (heave) rate due to steam-assisted gravity drainage (SAGD) at the Hangingstone oil sand field in Alberta, Canada, by stacking differential synthetic aperture radar (SAR) interferograms. To improve accuracy, a Landsat-7 Enhanced Thematic Mapper Plus intensity image was coregistered with the SAR intensity image. We examined three interferogram filtering methods and identified one that provided the desired effect of light filtering in areas of low noise and heavier filtering in high-noise areas. Based on our analysis of interferogram coherences, site-specific decorrelation highly depends on local seasonal changes. Stacking was performed to estimate the surface uplift rate while removing atmospheric and seasonal effects. The amounts of the uplift rate and slope change estimated by means of InSAR analysis reached a maximum of 3.6 cm/yr and 0.003%, respectively, for the period of 2007-2008. Comparison of the magnitude and patterns of the estimated surface uplift demonstrated that the uplift estimated from InSAR analysis agrees well with that obtained by conventional geodetic (GPS) surveys from a network of 54 monuments. Surface slope changes due to SAGD that we detected by using InSAR over one year in this oil sand field were small, so destruction of surface facilities by uplift is unlikely in the short term.

A coupled ocean-atmosphere mode, namely the El Niño event, took place in the tropical Pacific during 2015 – 2016. The event developed in spring (April – May 2015), peaked in late fall to early winter (November – December 2015) and terminated in spring (April – May 2016). The intensity of the event, indicated by the Niño3.4 index, is classified as a strong event. Compare to the previous events, the 2015/2016 El Niño event is one of the strongest event during the last two decades. This study examined the evolution of the event and highlighted some of the important aspects of its influence on the Indonesian climate.