A model-data intercomparison of CO2 exchange across North America

For the conterminous United States, PRISM and Daymet[1] are perhaps the most commonly used interpolated datasets. Both use similar inputs but apply different interpolation methods. Poster shows that for a wide range of conditions, PRISM is the preferred interpolation. We reached this conclusion by comparing the accuracy of predictions of annual and monthly minimum (Tmin) and maximum (Tmax) by PRISM and Daymet for the conterminous United States from 1980-2012. To evaluate comparative performance, I analyzed PRISM and Daymet temperature predictions of ground station temperatures by calculating the logs odds ratio (LOR), mean absolute error (MAE), and bias. In all the comparative performance analyses, PRISM was the better model. The monthly results followed the same trend as the annual average results. I found a spatial performance difference across the entirety of the conterminous United States with the largest difference on the coasts and in the mountainous western regions.