Frequent value locality is a type of locality based on the observation that a small set of values is accessed very frequently. Several works have exploited it to construct different architectural schemes, such as memory and cache designs or bus and network optimizations. Although these previous works consider different criteria to establish what is a frequent value and what is not, they assume that these frequent values are constant for the whole program, or they analyze the dynamic properties at a granularity too high to take advantage of them. In this paper, we observe that the frequent values change dynamically during the program execution, presenting what we call temporal frequent value locality, and its potential depends on the granularity of the observation. Furthermore, we instrument and analyze the dynamic patterns of the SPEC2006 benchmarks using two realistic schemes, and we compare them with other classical frequent value locality proposals. The results show that temporal frequent value locality has the potential to be used successfully in architectural optimizations. We also simulate our scheme for main memory bandwidth compression, achieving an increase of 63% (up to 285%) in the effective bandwidth, the double of the best tested state-of-the-art compression algorithm.