Similar to the CUSUM location chart, the traditional CUSUM dispersion chart can be designed to optimize the detection of specified variance changes. However, this optimality property requires that the magnitude of the out-of-control variance is known exactly a priori. To get away from this requirement, this paper suggests an adaptive CUSUM procedure for signaling changes in the process variance of unknown sizes. The basic idea is to first estimate the current process variance and then dynamically adjust the CUSUM chart to match the variance estimate. A two-dimensional Markov chain model is developed to analyze the chart performance. The comparison results with the traditional CUSUM dispersion chart and other competitive procedures favor the proposed one.