I've been working with ICON, ICON-EU and GFS forecasts, and it seems like the temperature results are "close" for the same location, 6 hour forecasts and 120 hour forecasts - MAE: 5.7 and 6.87 respectively. Is it usually the case and if it is, I would like to find out the reasons briefly.
I'm fetching forecasts from global models every 6 hours. Forecasts are in the range of 0-144 hours, hourly incremented. I calculated the error metric by using only 6 hour forecasts vs 120 hour forecasts.
Dataset example below: You can see that models forecast the next 144 hours in every run and I fetch every 6 hours so base_run_timestamp increments every 6 hours. (Base_run_timestamp is when the models made their forecasts and forecasted_timestamp is pretty self-explanatory)
Note: I realized this is a consistent error for my observation point, I applied simple linear regression and the error went straight down to ~1°C so high error is irrelevant.