how to measure Model performance in a uni-variate time series data?

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i have univariate time series data sets of water levels named as: observed data and simulated data .
i want to transform the simulated data in a way that it represents the variability and mean of the observation.
i.e. need to fix simulated data as may be like 95% variability and the mean of the obsrvation.
Or even better, how can i apply a transfer function that would transform the simulation into the observation?
i have joined them in a timetable. the data is attached as a mat file . first column is timestamp, second is observed data, and third column is simulated data.
please guide me how can i present the simulated /model performance?
what other measures should i consider for this ?
i have calculated RMSE,and nasch sutcliffe efficiency coefficient as well,(files of codes are attached). but its hard to interpret the results.
i need some guidance on this too.
looking forward for your guidance.
bushra raza
bushra raza on 15 Apr 2020
thank you for the reply.
i have raised similar question with more clarity i guess on
i am still eager to show 95% variability of simulated data versus observed data.
i dont know about simulation model, but i just have its values.
if simulated data represent the past years records say 1963-2016 well, then it means simulated data can be used for future projections. as simulated data is upto 2099.

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