# Can I remove outliers from a residual plot? Or does this compromise the validity of my model?

I used the function auto.arima to predict sales for the next year. When using only 3 years of the dataset, my results were not good. When I go back 10 years, it improved. However, in order for me to have a normal distribution of the residuals, or have the ACF inside the confidence interval that considers the errors as 0, I need to remove a few outliers. My question is: can I even remove outliers from a residuals plot? Because if I do remove then, it seems like I am removing the points that shows the biggest flaws of my model and I am not sure if it continues to be valid then.

s <- ts(data\$sales, frequency = 12)
fit <- auto.arima(s)
checkresiduals(fit)