I have daily weather data for almost 50 years for a weather station, and I want to predict the next 100 days' weather. I use python and all of the tools I've used so far (pmdarima.auto_arima, statsmodels.ARIMA, etc) run either infinitely or just crash my Colab or Jupyter notebook. What would be the best way to forecast this data with ARIMA?
The ACF and PACF plots also generally give such results that I cannot interpret meaningful p,d,q orders. For instance, adf-test gives p-value 0.000 for the seasonal part and this is its PACF and PACF plots:
adf-test suggests the seasonal part is stationary but PACF plot still gives significant lag values even up to 35 (which would make running an ARIMA model longer). Any advice would be appreciated.