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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:

Example of one of the time series

However the observations all of these time series is unequally distributed (growing trend with years).

Distribution of observations for the time series shown above

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?

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