I am building a time-series forecasting model to predict some patterns in climatological data.
The dataset consists of many (2 mln) time series which look for example as:
However the observations all of these time series is unequally distributed (growing trend with years).
Although I am still considering my approach (LSTM, exponential smoothing, etc.), I will have to deal with this unequal distribution of observations. Is there a golden standard for equalizing time series observations?