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Exercise 4140. Points 3, theme: Interpolation

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The worksheet andmeid_pole in the attached file contains names and coordinates of 13 Estonian weather stations with missing snow cover duration data. Predict snow cover duration for these stations using the observed data from other stations in the same worksheet using Inverse distance weighted interpolation.
  1. Present the root mean squared error (RMSE) of this prediction.
  2. Compare values and standard deviations (SD) of predicted and observed values on worksheet andmed_on.
  3. Explain why is variability in observed and interpolated values so different.
Data: lumikatte_kestus.xlsx


  • Find Interpolation from the SDC.
  • Select Calculate single points and method Inverse distance weighted (figure).
  • Copy existing snow cover data as [X] [Y] [Value] from the worksheet andmeid_pole in the attached file to Given locations.
  • Copy to Target locations the stations with no snow cover data (as [Station name] [X] [Y]).
  • Press Calculate.
  • Copy results to the sheet andmed_on.
  • Open Difference tests and check RMSE.
  • Copy the observed values to one cell and the interpolated values to other.
  • Press Calculate and find sample SD and RMSE values from the results. You can also use Excel function STDEVP() to find the sample SD.
There is no need to present direct interpolation results.

The exercise is compiled by Taavi Virro and Kalle Remm.
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