Creating a reference group to have equal sample sizes for Wilcoxon signed rank test I am analyzing three years' worth of data. For some descriptive analysis, I want to know if there is a difference in the median between, $year_1$ and $year_2$ compared to $year_3$. To do this, I planned to average $year_1$ and $year_2$, creating a comparable 12-month reference group with $year_3$. I would then use the Wilcoxon signed rank test. Would this be a fair way to understand the data? The data is considered paired.

Thank you for your feedback. Let me first state, this is a preliminary analysis for a larger interrupted time series analysis in which autocorrelation is account for (using ARIMA).
Knowing this, would you still suggest the the Wilcoxon Mann-Whitney two sampled ranked sum test (from this initial phase)? And if so, it is acceptable to have unequal groups ($n=24$ and $n=12$)?Also, the rate are coming from one distinct location, which is why I first instinctively considered them paired.
Edit: or is the creation of the (pre 12-month reference group still applicable)
I appreciate your continued input and support.

The Wilcoxon signed-rank test, made almost obsolete by the rank difference test is only for naturally paired data. You do not have paired data but rather data more suitable for the Wilcoxon Mann-Whitney two-sample rank-sum test (although we are ignoring serial correlation in the data).  A better way to think about your problem is whether there is a non-flat time-trend, and it's best to use time as a continuous variable (e.g., year + fraction of year).  You can use a regression spline to relate time to response using a suitable model such as the proportional odds ordinal logistic model which generalizes the Wilcoxon two-sample test.  Resources for this model are here.
If you have the time to take serial correlation into account you can easily use a Markov process with the proportional odds model.  For example a lag-1 analysis would be a first-order Markov process.  Details are in my course notes here.
