A data scientist trains a linear regression model to predict energy consumption from temperature. Both the training error and validation error are high and nearly equal, and a scatter plot shows the relationship between temperature and consumption is clearly U-shaped (consumption rises at both very low and very high temperatures). Which action is MOST likely to improve model performance?