One has to appreciate the complexity of modeling such a large and dynamic system that the atmosphere is! There are cases where forecasting is more difficult. Certainly getting the temperature correct within a degree or two is one case.
Another issue is geography. I'm in middle of of USA and there is significant amount of data collected over the continental US as systems approach me. For those on the west coast I can see where forecasting is more challenging since there is far less data available to input into models (current atmosphere state 100s of kilometers out over the ocean). I'd suspect some European countries experience same situation, those further inland benefit from increased modelling data.
Reading the comments here I'm a bit surprised at how many quibble over slight details. The improvements over the past decades in forecasting models and the supercomputers that crunch the data has been significant. In most cases, like recent cold temperatures and snow fall amounts, models converge on a good solution as the event nears. This is consistent with idea that better data input yields better data out.